An Intuitionistic Fuzzy Sets Implementation for Key Distribution in Hybrid Me...IJAAS Team
WSN is a way of handling dangerous and hostile environments safely. It replaces human existence with nodes and units that could sustain its existence under extreme circumstances. The significance of WSN arises from the importance of the data gathered through its nodes. Due to the fact of WSN that it is open air environment, security issues must be considered, for example authentication of new units and the encryption of data transmitted between these units. This research provides a new model covering two important aspects in WSN. The first aspect is the creation of the key that will be used for the current session between a pair of nodes. In this step the research introduces the intuitionistic fuzzy sets to handle the WSN criteria simultaneously and efficiently, in order to decide the exact key length required depending on the status of the network parameters. The second aspect is the distribution of the key between the units desiring communications. This phase starts by authenticating each entity to each other and to the cluster head, then one unit suggests a key and the other one confirms. It then starts communication using that key. This phase shows the hybrid cryptography applied in which the algorithm uses asymmetric encryption for authentication then uses symmetric encryption to secure the connection between the two units. Experimental results in this research could categorized also into two classes. The first class is key size model in which the proposed model compared to ordinary KNN and fuzzy model related to the determination of the key size. The proposed model shows an overall efficient way relating to decide the key size. The second class of experiments is to distribute the intermediate key efficiently; at this point the proposed model shows resilience and efficiency compared to distributing the key directly through cluster head.
Multi-stage secure clusterhead selection using discrete rule-set against unkn...IJECEIAES
Security is the rising concern of the wireless network as there are various forms of reonfigurable network that is arised from it. Wireless sensor network (WSN) is one such example that is found to be an integral part of cyber-physical system in upcoming times. After reviewing the existing system, it can be seen that there are less dominant and robust solutions towards mitigating the threats of upcoming applications of WSN. Therefore, this paper introduces a simple and cost-effective modelling of a security system that offers security by ensuring secure selection of clusterhead during the data aggregation process in WSN. The proposed system also makes construct a rule-set in order to learn the nature of the communication iin order to have a discrete knowledge about the intensity of adversaries. With an aid of simulation-based approach over MEMSIC nodes, the proposed system was proven to offer reduced energy consumption with good data delivery performance in contrast to existing approach.
A Review on Wireless Sensor Network Securityijtsrd
Wireless sensor networks are attracting more and more coverage. A number of surveillance, regulation, and tracking systems have been developed for different scenarios in recent years. Wireless Sensor Network WSN is an emerging technology that shows great promise for various futuristic applications both for mass public and military. The sensing technology combined with processing power and wireless communication makes it lucrative for being exploited in abundance in future. The inclusion of wireless communication technology also incurs various types of security threats. The intent of this paper is to investigate the security related issues and challenges in wireless sensor networks. We identify the security threats, review proposed security mechanisms for wireless sensor networks. We also discuss the holistic view of security for ensuring layered and robust security in wireless sensor networks. Vijay Kumar Kalakar | Hirdesh Chack | Syed Tariq Ali "A Review on Wireless Sensor Network Security" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-5 , August 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31815.pdf Paper Url :https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/31815/a-review-on-wireless-sensor-network-security/vijay-kumar-kalakar
Concepts and evolution of research in the field of wireless sensor networksIJCNCJournal
The field of Wireless Sensor Networks (WSNs) is experiencing a resurgence of interest and a continuous evolution in the scientific and industrial community. The use of this particular type of ad hoc network is becoming increasingly important in many contexts, regardless of geographical position and so, according to a set of possible application. WSNs offer interesting low cost and easily deployable solutions to perform a remote real time monitoring, target tracking and recognition of physical phenomenon. The uses of these sensors organized into a network continue to reveal a set of research questions according to particularities target applications. Despite difficulties introduced by sensor resources constraints, research contributions in this field are growing day by day. In this paper, we present a comprehensive review of most recent literature of WSNs and outline open research issues in this field.
Wireless Sensor Network Nodes: Security and Deployment in the Niger-Delta Oil...IJNSA Journal
Wireless sensor networks (WSN) is tending towards becoming a complete solution in communication protocols, embedded systems and low-power implementations. However, the resource constraints which includes, limited communication range, limited energy, limited computing power, limited bandwidth and the fear of intruders have limited the WSN applications. Since lightweight computational nodes that are currently being used in WSN pose particular challenge for many security applications, the whole research therefore, is the investigation of new security techniques and appropriate implementation for WSN nodes, including various trade-offs such as implementation complexity, power dissipation, security flexibility and scalability. The goal of this research is to develop a network that has efficient and flexible key distribution scheme secured enough to prevent algorithmic complexity and denial of service attacks as well as the network able to conserve energy. A review of previous research to date in the area of security for WSNs was carried out and proposals are made based on security schemes that gather data in
an energy-efficient mechanism through secured pre-allocation of keys, faster clustering routing algorithm and dynamic based rekeying implementation.
An Intuitionistic Fuzzy Sets Implementation for Key Distribution in Hybrid Me...IJAAS Team
WSN is a way of handling dangerous and hostile environments safely. It replaces human existence with nodes and units that could sustain its existence under extreme circumstances. The significance of WSN arises from the importance of the data gathered through its nodes. Due to the fact of WSN that it is open air environment, security issues must be considered, for example authentication of new units and the encryption of data transmitted between these units. This research provides a new model covering two important aspects in WSN. The first aspect is the creation of the key that will be used for the current session between a pair of nodes. In this step the research introduces the intuitionistic fuzzy sets to handle the WSN criteria simultaneously and efficiently, in order to decide the exact key length required depending on the status of the network parameters. The second aspect is the distribution of the key between the units desiring communications. This phase starts by authenticating each entity to each other and to the cluster head, then one unit suggests a key and the other one confirms. It then starts communication using that key. This phase shows the hybrid cryptography applied in which the algorithm uses asymmetric encryption for authentication then uses symmetric encryption to secure the connection between the two units. Experimental results in this research could categorized also into two classes. The first class is key size model in which the proposed model compared to ordinary KNN and fuzzy model related to the determination of the key size. The proposed model shows an overall efficient way relating to decide the key size. The second class of experiments is to distribute the intermediate key efficiently; at this point the proposed model shows resilience and efficiency compared to distributing the key directly through cluster head.
Multi-stage secure clusterhead selection using discrete rule-set against unkn...IJECEIAES
Security is the rising concern of the wireless network as there are various forms of reonfigurable network that is arised from it. Wireless sensor network (WSN) is one such example that is found to be an integral part of cyber-physical system in upcoming times. After reviewing the existing system, it can be seen that there are less dominant and robust solutions towards mitigating the threats of upcoming applications of WSN. Therefore, this paper introduces a simple and cost-effective modelling of a security system that offers security by ensuring secure selection of clusterhead during the data aggregation process in WSN. The proposed system also makes construct a rule-set in order to learn the nature of the communication iin order to have a discrete knowledge about the intensity of adversaries. With an aid of simulation-based approach over MEMSIC nodes, the proposed system was proven to offer reduced energy consumption with good data delivery performance in contrast to existing approach.
A Review on Wireless Sensor Network Securityijtsrd
Wireless sensor networks are attracting more and more coverage. A number of surveillance, regulation, and tracking systems have been developed for different scenarios in recent years. Wireless Sensor Network WSN is an emerging technology that shows great promise for various futuristic applications both for mass public and military. The sensing technology combined with processing power and wireless communication makes it lucrative for being exploited in abundance in future. The inclusion of wireless communication technology also incurs various types of security threats. The intent of this paper is to investigate the security related issues and challenges in wireless sensor networks. We identify the security threats, review proposed security mechanisms for wireless sensor networks. We also discuss the holistic view of security for ensuring layered and robust security in wireless sensor networks. Vijay Kumar Kalakar | Hirdesh Chack | Syed Tariq Ali "A Review on Wireless Sensor Network Security" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-5 , August 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31815.pdf Paper Url :https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/31815/a-review-on-wireless-sensor-network-security/vijay-kumar-kalakar
Concepts and evolution of research in the field of wireless sensor networksIJCNCJournal
The field of Wireless Sensor Networks (WSNs) is experiencing a resurgence of interest and a continuous evolution in the scientific and industrial community. The use of this particular type of ad hoc network is becoming increasingly important in many contexts, regardless of geographical position and so, according to a set of possible application. WSNs offer interesting low cost and easily deployable solutions to perform a remote real time monitoring, target tracking and recognition of physical phenomenon. The uses of these sensors organized into a network continue to reveal a set of research questions according to particularities target applications. Despite difficulties introduced by sensor resources constraints, research contributions in this field are growing day by day. In this paper, we present a comprehensive review of most recent literature of WSNs and outline open research issues in this field.
Wireless Sensor Network Nodes: Security and Deployment in the Niger-Delta Oil...IJNSA Journal
Wireless sensor networks (WSN) is tending towards becoming a complete solution in communication protocols, embedded systems and low-power implementations. However, the resource constraints which includes, limited communication range, limited energy, limited computing power, limited bandwidth and the fear of intruders have limited the WSN applications. Since lightweight computational nodes that are currently being used in WSN pose particular challenge for many security applications, the whole research therefore, is the investigation of new security techniques and appropriate implementation for WSN nodes, including various trade-offs such as implementation complexity, power dissipation, security flexibility and scalability. The goal of this research is to develop a network that has efficient and flexible key distribution scheme secured enough to prevent algorithmic complexity and denial of service attacks as well as the network able to conserve energy. A review of previous research to date in the area of security for WSNs was carried out and proposals are made based on security schemes that gather data in
an energy-efficient mechanism through secured pre-allocation of keys, faster clustering routing algorithm and dynamic based rekeying implementation.
International Journal of Computational Engineering Research(IJCER) ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
A Top-down Hierarchical Multi-hop Secure Routing Protocol for Wireless Sensor...ijasuc
This paper proposes a new top-down hierarchical, multi-hop, secure routing protocol for the wireless
sensor network, which is resilient to report fabrication attack. The report fabrication attack tries to
generate bogus reports by compromising the sensor nodes to mislead the environment monitoring
application executed by randomly deployed wireless sensor nodes. The proposed protocol relies on
symmetric key mechanism which is appropriate for random deployment of wireless sensor nodes. In the
proposed protocol, base station initiates the synthesis of secure hierarchical topology using top down
approach. The enquiry phase of the protocol provides assurance for the participation of all the cluster
heads in secure hierarchical topology formation. Further, this methodology takes care of failure of head
node or member node of a cluster. This protocol ensures confidentiality, integrity, and authenticity of the
final report of the monitoring application. The simulation results demonstrate the scalability of the
proposed protocol.
Wireless Sensor Network (WSN) is a promising field for research. As the use of this field increases, it is
required to give proper security to this field. So to ensure the security of communication of data or messages and to
control the use of data in WSN is of great importance. As sensor networks interact with responsive data and operate
in unfriendly unattended area, from the time of system design these security concerns should be addressed. The paper,
presents a modified Motesec security protocol which is a security mechanism for Wireless sensor network. In this
protocol a hash function based approach is used to detect replay attacks. For data access control key lock matching
method i.e. memory data access control policy is used to prevent unauthorized data access. Encoding and
reconstruction scheme is used to find out attacker. Flooding attack detection by comparing data rate. There is currently
massive research is present in the area of wireless sensor network security..Keywords: GPS,GCM,LBS Android.
Keywords: secure communication architecture, wireless Sensor network security.
Nowadays, managing for optimal security to wireless sensor networks (WSNs) has emerged as an active research area. The challenging topics in this active research involve various issues such as energy consumption, routing algorithms, selection of sensors location according to a given premise, robustness, and efficiency. Despite the open problems in WSNs, already a high number of applications available show the activeness of emerging research in this area. Through this paper, authors propose an alternative routing algorithmic approach that accelerate the existing algorithms in sense to develop a power-efficient crypto system to provide the desired level of security on a smaller footprint, while maintaining real-time performance and mapping them to customized hardware. To achieve this goal, the algorithms have been first analyzed and then profiled to recognize their computational structure that is to be mapped into hardware accelerators in platform of reconfigurable computing devices. An intensive set of experiments have been conducted and the obtained results show that the performance of the proposed architecture based on algorithms implementation outperforms the software implementation running on contemporary CPU in terms of the power consumption and throughput.
Requisite Trust Based Routing Protocol for WSNAM Publications
A mobile ad-hoc network (MANET) is an infrastructure less network of mobile devices connected by wireless
links. To secure a MANET in colluding nodes environment, the proposed work aims to detect and defend colluding nodes that
causes internal attacks. In order to achieve this, the work focuses on the novel algorithm of trust computation and route
detection that detects colluding nodes, without message and route redundancy during route discovery by using Requisite Trust
based Secure Routing Protocol (RTSR). The trust will be calculated in local forwarding nodes, which are used to discover the
route. The trust values from one hop neighbors are used to calculate the single trust value for each node using the constant
normalization concept. Route discovery and trust information will be stored in fixed cluster head (CH).
Secured Intrusion Protection System through EAACK in MANETSijtsrd
Achieving reliable routing has always been a major issue in the design of communication networks, due to the absence of fixed infrastructure among which mobile ad hoc networks MANETs that can take control of the most adversarial networking environment, and the dynamic network topology the nature of open transmission media. In the MANETs these characteristics also more challenging to make the design of routing protocols. The network topology varies so to determining feasible routing paths for distributing messages in a decentralized is a difficult job. Factors such as the extensive distribution of nodes and open medium, variable wireless link quality topological changes, and propagation path loss become pertinent issues and make MANET unprotected to instructions. Thus, it becomes central to develop a systematic intrusion detection scheme to secure Mobile Ad Hoc networks from intruders. In this project, we put forward and applied an efficient IDS mechanism based on Enhanced Adaptive Acknowledgment EAACK especially made for MANETs which performs better than the earlier techniques such as AACK, TWOACK and Watchdog. Mr. Ravishankar Kandasamy | M. Ajith Kumar | M. Ajith Kumar | G. Arun Kumar "Secured Intrusion Protection System through EAACK in MANETS" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30457.pdf Paper Url :https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/30457/secured-intrusion-protection-system-through-eaack-in-manets/mr-ravishankar-kandasamy
A SERVEY ON WIRELESS SENSOR NETWORK SECURITY ISSUES & CHALLENGESEditor IJCTER
A Wireless Sensor Network (WSN) is an evolving technology and getting significant attention due to its unlimited potential starts from domestic application to battlefield. Wireless
Sensor Networks(WSN) are a most challenging and emerging technology for the research due to
their vital scope in the field coupled with their low processing power and associated low energy.
Today wireless sensor networks are broadly used in environmental control, surveillance tasks,
monitoring, tracking and controlling etc. Sensor nodes are tiny, cheap, disposable and self-contained
battery powered computers, known as "motes”, which can accept input from an attached sensor,
process this input data and transmit the results wirelessly to the transit network. Due to the various
applications of WSN in homeland security and military, security is the major issue to be taken care
of. In this paper we discuss about The combination of these factors demands security for sensor
networks at design time to ensure operation safety, secrecy of sensitive data, and privacy for people
in sensor environments. Broadcast authentication is a critical security service in sensor networks; it
allows a sender to broadcast messages to multiple nodes in an authenticated way. µ TESLA and multi-level µTESLA have been proposed to provide such service for sensor networks.
A NOVEL SECURITY PROTOCOL FOR WIRELESS SENSOR NETWORKS BASED ON ELLIPTIC CURV...IJCNCJournal
With the growing usage of wireless sensors in a variety of applications including Internet of Things, the security aspects of wireless sensor networks have been on priority for the researchers. Due to the constraints of resources in wireless sensor networks, it has been always a challenge to design efficient security protocols for wireless sensor networks. An novel elliptic curve signcryption based security protocol for wireless sensor networks has been presented in this paper, which provides anonymity, confidentiality, mutual authentication, forward security, secure key establishment, and key privacy at the same time providing resistance from replay attack, impersonation attack, insider attack, offline dictionary attack, and stolen-verifier attack. Results have revealed that the proposed elliptic curve signcryption based protocol consumes the least time in comparison to other protocols while providing the highest level of security.
A Security Framework for Replication Attacks in Wireless Sensor NetworksIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
Efficient Data Aggregation in Wireless Sensor NetworksIJAEMSJORNAL
Sensor network is a term used to refer to a heterogeneous system combining tiny sensors and actuators with general/special-purpose processors. Sensor networks are assumed to grow in size to include hundreds or thousands of low-power, low-cost, static or mobile nodes. This system is created by observing that for any densely deployed sensor network, high redundancy exists in the gathered information from the sensor nodes that are close to each other we have exploited the redundancy and designed schemes to secure different kinds of aggregation processing against both inside and outside attacks.
Multi-Tiered Communication Security Schemes in Wireless Ad-Hoc Sensor NetworksIDES Editor
Networks of wireless micro-sensors for monitoring
physical environments have emerged as an important new
application area for wireless technology. Key attributes of
these new types of networked systems are the severely
constrained computational and energy resources and an ad
hoc operational environment. This paper is a study of the
communication security aspects of these networks. Resource
limitations and specific architecture of sensor networks call
for customized security mechanisms. Our approach is to
classify the types of data existing in sensor networks, and
identify possible communication security threats according
to that classification. We propose a communication security
scheme where for each type of data we define a corresponding
security mechanism. By employing this multi-tiered security
architecture where each mechanism has different resource
requirements, we allow for efficient resource management,
which is essential for wireless sensor networks.
Secure and Efficient DiDrip Protocol for Improving Performance of WSNsINFOGAIN PUBLICATION
Wireless Sensor Networks consists of a set of resource constrained devices called nodes that communicate wirelessly with each other. Wireless Sensor Networks have become a key application in number of technologies. It also measures the unit of vulnerability to security threats. Several Protocols are projected to make them secure. Some of the protocols within the sensor network specialize in securing data. These protocols are named as data discovery and dissemination protocols. The data discovery and dissemination protocol for wireless sensor networks are utilized for distributing management commands and altering configuration parameters to the sensor nodes. All existing data discovery and dissemination protocols primarily suffer from two drawbacks. Basically, they are support centralized approach (only single station can distribute data item).This approach is not suitable for multiple owner-multiple users. Second, the protocols are not designed with security in mind. This Paper proposes the first distributed knowledge discovery and dissemination protocol called DiDrip which is safer than the existing one. The protocol permits multiple owners to authorize many network users with altogether totally different priorities to at an equivalent time and directly flow into data items to sensor nodes.
Evaluation of enhanced security solutions inIJNSA Journal
Traditionally, 802.11-based networks that relied on wired equivalent protocol (WEP) were especially
vulnerable to packet sniffing. Today, wireless networks are more prolific, and the monitoring devices used
to find them are mobile and easy to access. Securing wireless networks can be difficult because these
networks consist of radio transmitters and receivers, and anybody can listen, capture data and attempt to
compromise it. In recent years, a range of technologies and mechanisms have helped makes networking
more secure. This paper holistically evaluated various enhanced protocols proposed to solve WEP related
authentication, confidentiality and integrity problems. It discovered that strength of each solution depends
on how well the encryption, authentication and integrity techniques work. The work suggested using a
Defence-in-Depth Strategy and integration of biometric solution in 802.11i. Comprehensive in-depth
comparative analysis of each of the security mechanisms is driven by review of related work in WLAN
security solutions.
This paper presents a brief study of recent advances in wireless network security issues. The paper makes a number of contributions to the wireless networking field. First, it studies the 4G mail threats and risk and their design decisions. Second, the security of 4G architecture with next generation network security and 8-security dimensions of 4G network. Third, security issues and possible threats on 4G are discussed. Finally, we proposed four layer security model which manages to ensure more secure packets transmission by taking all the necessary security measures.
COMPREHENSIVE SURVEY OF POSSIBLE SECURITY ISSUES ON 4G NETWORKSIJNSA Journal
This paper presents a brief study of recent advances in wireless network security issues. The paper makes a number of contributions to the wireless networking field. First, it studies the 4G mail threats and risk and their design decisions. Second, the security of 4G architecture with next generation network security and 8-security dimensions of 4G network. Third, security issues and possible threats on 4G are discussed. Finally, we proposed four layer security model which manages to ensure more secure packets transmission by taking all the necessary security measures.
SECURITY IN WIRELESS SENSOR NETWORKS: COMPARATIVE STUDYijcsit
The security in wireless sensor networks (WSNS) is a very important issue. These networks may be exposed
it different attacks. With this in mind, researchers propose in this area variety of security techniques for
this purpose, and this article describes security in wireless sensor networks. Discussed threats and attacks
of wireless sensor networks. The article also aims to provide the basic information related to determining
essential requirements for the protection WSNs. Lastly, we mention some security mechanisms against
these threats and attacks in Wireless Sensor Network.
International Journal of Computational Engineering Research(IJCER) ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
A Top-down Hierarchical Multi-hop Secure Routing Protocol for Wireless Sensor...ijasuc
This paper proposes a new top-down hierarchical, multi-hop, secure routing protocol for the wireless
sensor network, which is resilient to report fabrication attack. The report fabrication attack tries to
generate bogus reports by compromising the sensor nodes to mislead the environment monitoring
application executed by randomly deployed wireless sensor nodes. The proposed protocol relies on
symmetric key mechanism which is appropriate for random deployment of wireless sensor nodes. In the
proposed protocol, base station initiates the synthesis of secure hierarchical topology using top down
approach. The enquiry phase of the protocol provides assurance for the participation of all the cluster
heads in secure hierarchical topology formation. Further, this methodology takes care of failure of head
node or member node of a cluster. This protocol ensures confidentiality, integrity, and authenticity of the
final report of the monitoring application. The simulation results demonstrate the scalability of the
proposed protocol.
Wireless Sensor Network (WSN) is a promising field for research. As the use of this field increases, it is
required to give proper security to this field. So to ensure the security of communication of data or messages and to
control the use of data in WSN is of great importance. As sensor networks interact with responsive data and operate
in unfriendly unattended area, from the time of system design these security concerns should be addressed. The paper,
presents a modified Motesec security protocol which is a security mechanism for Wireless sensor network. In this
protocol a hash function based approach is used to detect replay attacks. For data access control key lock matching
method i.e. memory data access control policy is used to prevent unauthorized data access. Encoding and
reconstruction scheme is used to find out attacker. Flooding attack detection by comparing data rate. There is currently
massive research is present in the area of wireless sensor network security..Keywords: GPS,GCM,LBS Android.
Keywords: secure communication architecture, wireless Sensor network security.
Nowadays, managing for optimal security to wireless sensor networks (WSNs) has emerged as an active research area. The challenging topics in this active research involve various issues such as energy consumption, routing algorithms, selection of sensors location according to a given premise, robustness, and efficiency. Despite the open problems in WSNs, already a high number of applications available show the activeness of emerging research in this area. Through this paper, authors propose an alternative routing algorithmic approach that accelerate the existing algorithms in sense to develop a power-efficient crypto system to provide the desired level of security on a smaller footprint, while maintaining real-time performance and mapping them to customized hardware. To achieve this goal, the algorithms have been first analyzed and then profiled to recognize their computational structure that is to be mapped into hardware accelerators in platform of reconfigurable computing devices. An intensive set of experiments have been conducted and the obtained results show that the performance of the proposed architecture based on algorithms implementation outperforms the software implementation running on contemporary CPU in terms of the power consumption and throughput.
Requisite Trust Based Routing Protocol for WSNAM Publications
A mobile ad-hoc network (MANET) is an infrastructure less network of mobile devices connected by wireless
links. To secure a MANET in colluding nodes environment, the proposed work aims to detect and defend colluding nodes that
causes internal attacks. In order to achieve this, the work focuses on the novel algorithm of trust computation and route
detection that detects colluding nodes, without message and route redundancy during route discovery by using Requisite Trust
based Secure Routing Protocol (RTSR). The trust will be calculated in local forwarding nodes, which are used to discover the
route. The trust values from one hop neighbors are used to calculate the single trust value for each node using the constant
normalization concept. Route discovery and trust information will be stored in fixed cluster head (CH).
Secured Intrusion Protection System through EAACK in MANETSijtsrd
Achieving reliable routing has always been a major issue in the design of communication networks, due to the absence of fixed infrastructure among which mobile ad hoc networks MANETs that can take control of the most adversarial networking environment, and the dynamic network topology the nature of open transmission media. In the MANETs these characteristics also more challenging to make the design of routing protocols. The network topology varies so to determining feasible routing paths for distributing messages in a decentralized is a difficult job. Factors such as the extensive distribution of nodes and open medium, variable wireless link quality topological changes, and propagation path loss become pertinent issues and make MANET unprotected to instructions. Thus, it becomes central to develop a systematic intrusion detection scheme to secure Mobile Ad Hoc networks from intruders. In this project, we put forward and applied an efficient IDS mechanism based on Enhanced Adaptive Acknowledgment EAACK especially made for MANETs which performs better than the earlier techniques such as AACK, TWOACK and Watchdog. Mr. Ravishankar Kandasamy | M. Ajith Kumar | M. Ajith Kumar | G. Arun Kumar "Secured Intrusion Protection System through EAACK in MANETS" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30457.pdf Paper Url :https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/30457/secured-intrusion-protection-system-through-eaack-in-manets/mr-ravishankar-kandasamy
A SERVEY ON WIRELESS SENSOR NETWORK SECURITY ISSUES & CHALLENGESEditor IJCTER
A Wireless Sensor Network (WSN) is an evolving technology and getting significant attention due to its unlimited potential starts from domestic application to battlefield. Wireless
Sensor Networks(WSN) are a most challenging and emerging technology for the research due to
their vital scope in the field coupled with their low processing power and associated low energy.
Today wireless sensor networks are broadly used in environmental control, surveillance tasks,
monitoring, tracking and controlling etc. Sensor nodes are tiny, cheap, disposable and self-contained
battery powered computers, known as "motes”, which can accept input from an attached sensor,
process this input data and transmit the results wirelessly to the transit network. Due to the various
applications of WSN in homeland security and military, security is the major issue to be taken care
of. In this paper we discuss about The combination of these factors demands security for sensor
networks at design time to ensure operation safety, secrecy of sensitive data, and privacy for people
in sensor environments. Broadcast authentication is a critical security service in sensor networks; it
allows a sender to broadcast messages to multiple nodes in an authenticated way. µ TESLA and multi-level µTESLA have been proposed to provide such service for sensor networks.
A NOVEL SECURITY PROTOCOL FOR WIRELESS SENSOR NETWORKS BASED ON ELLIPTIC CURV...IJCNCJournal
With the growing usage of wireless sensors in a variety of applications including Internet of Things, the security aspects of wireless sensor networks have been on priority for the researchers. Due to the constraints of resources in wireless sensor networks, it has been always a challenge to design efficient security protocols for wireless sensor networks. An novel elliptic curve signcryption based security protocol for wireless sensor networks has been presented in this paper, which provides anonymity, confidentiality, mutual authentication, forward security, secure key establishment, and key privacy at the same time providing resistance from replay attack, impersonation attack, insider attack, offline dictionary attack, and stolen-verifier attack. Results have revealed that the proposed elliptic curve signcryption based protocol consumes the least time in comparison to other protocols while providing the highest level of security.
A Security Framework for Replication Attacks in Wireless Sensor NetworksIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
Efficient Data Aggregation in Wireless Sensor NetworksIJAEMSJORNAL
Sensor network is a term used to refer to a heterogeneous system combining tiny sensors and actuators with general/special-purpose processors. Sensor networks are assumed to grow in size to include hundreds or thousands of low-power, low-cost, static or mobile nodes. This system is created by observing that for any densely deployed sensor network, high redundancy exists in the gathered information from the sensor nodes that are close to each other we have exploited the redundancy and designed schemes to secure different kinds of aggregation processing against both inside and outside attacks.
Multi-Tiered Communication Security Schemes in Wireless Ad-Hoc Sensor NetworksIDES Editor
Networks of wireless micro-sensors for monitoring
physical environments have emerged as an important new
application area for wireless technology. Key attributes of
these new types of networked systems are the severely
constrained computational and energy resources and an ad
hoc operational environment. This paper is a study of the
communication security aspects of these networks. Resource
limitations and specific architecture of sensor networks call
for customized security mechanisms. Our approach is to
classify the types of data existing in sensor networks, and
identify possible communication security threats according
to that classification. We propose a communication security
scheme where for each type of data we define a corresponding
security mechanism. By employing this multi-tiered security
architecture where each mechanism has different resource
requirements, we allow for efficient resource management,
which is essential for wireless sensor networks.
Secure and Efficient DiDrip Protocol for Improving Performance of WSNsINFOGAIN PUBLICATION
Wireless Sensor Networks consists of a set of resource constrained devices called nodes that communicate wirelessly with each other. Wireless Sensor Networks have become a key application in number of technologies. It also measures the unit of vulnerability to security threats. Several Protocols are projected to make them secure. Some of the protocols within the sensor network specialize in securing data. These protocols are named as data discovery and dissemination protocols. The data discovery and dissemination protocol for wireless sensor networks are utilized for distributing management commands and altering configuration parameters to the sensor nodes. All existing data discovery and dissemination protocols primarily suffer from two drawbacks. Basically, they are support centralized approach (only single station can distribute data item).This approach is not suitable for multiple owner-multiple users. Second, the protocols are not designed with security in mind. This Paper proposes the first distributed knowledge discovery and dissemination protocol called DiDrip which is safer than the existing one. The protocol permits multiple owners to authorize many network users with altogether totally different priorities to at an equivalent time and directly flow into data items to sensor nodes.
Evaluation of enhanced security solutions inIJNSA Journal
Traditionally, 802.11-based networks that relied on wired equivalent protocol (WEP) were especially
vulnerable to packet sniffing. Today, wireless networks are more prolific, and the monitoring devices used
to find them are mobile and easy to access. Securing wireless networks can be difficult because these
networks consist of radio transmitters and receivers, and anybody can listen, capture data and attempt to
compromise it. In recent years, a range of technologies and mechanisms have helped makes networking
more secure. This paper holistically evaluated various enhanced protocols proposed to solve WEP related
authentication, confidentiality and integrity problems. It discovered that strength of each solution depends
on how well the encryption, authentication and integrity techniques work. The work suggested using a
Defence-in-Depth Strategy and integration of biometric solution in 802.11i. Comprehensive in-depth
comparative analysis of each of the security mechanisms is driven by review of related work in WLAN
security solutions.
This paper presents a brief study of recent advances in wireless network security issues. The paper makes a number of contributions to the wireless networking field. First, it studies the 4G mail threats and risk and their design decisions. Second, the security of 4G architecture with next generation network security and 8-security dimensions of 4G network. Third, security issues and possible threats on 4G are discussed. Finally, we proposed four layer security model which manages to ensure more secure packets transmission by taking all the necessary security measures.
COMPREHENSIVE SURVEY OF POSSIBLE SECURITY ISSUES ON 4G NETWORKSIJNSA Journal
This paper presents a brief study of recent advances in wireless network security issues. The paper makes a number of contributions to the wireless networking field. First, it studies the 4G mail threats and risk and their design decisions. Second, the security of 4G architecture with next generation network security and 8-security dimensions of 4G network. Third, security issues and possible threats on 4G are discussed. Finally, we proposed four layer security model which manages to ensure more secure packets transmission by taking all the necessary security measures.
SECURITY IN WIRELESS SENSOR NETWORKS: COMPARATIVE STUDYijcsit
The security in wireless sensor networks (WSNS) is a very important issue. These networks may be exposed
it different attacks. With this in mind, researchers propose in this area variety of security techniques for
this purpose, and this article describes security in wireless sensor networks. Discussed threats and attacks
of wireless sensor networks. The article also aims to provide the basic information related to determining
essential requirements for the protection WSNs. Lastly, we mention some security mechanisms against
these threats and attacks in Wireless Sensor Network.
The security in wireless sensor networks (WSNS) is a very important issue. These networks may be exposed
it different attacks. With this in mind, researchers propose in this area variety of security techniques for
this purpose, and this article describes security in wireless sensor networks. Discussed threats and attacks
of wireless sensor networks. The article also aims to provide the basic information related to determining
essential requirements for the protection WSNs. Lastly, we mention some security mechanisms against
these threats and attacks in Wireless Sensor Network.
https://www.ijmst.com/
IJMST Volume 1 Issue 1, Manuscript 4
As the popularity of mobile devices and wireless networks significantly increased over the
past years. The wireless adhoc network has now become one of the most vibrant and active
fields of communication and networking research. These networks are a new generation of
networks offering unrestricted mobility without any underlying infrastructure. As their
principle application is in disastrous environments, security is critical. Various challenges are
faced in the adhoc environment, mostly due to the resource poorness of these networks. One
man confront in the design of these networks is their vulnerability to security attacks. The
solutions for conventional networks are usually not sufficient to provide efficient adhoc
operations. Just because of its wireless nature of communication and lack of any security
infrastructure raise several security problems and threats.
In this paper, we briefly review the threats an adhoc network faces and the security goals to
be achieved. Moreover, it also presents existing security schemes used in wireless adhoc
networks in order to handle security threats.
Tactical approach to identify and quarantine spurious node participation requ...IJECEIAES
Securing Wireless Sensor Network (WSN) from variable forms of adversary is still an open end challenge. Review of diversified security apprroaches towards such problems that they are highly symptomatic with respect to resiliency strength against attack. Therefore, the proposed system highlights a novel and effective solution that is capable of identify the spurios request for participating in teh network building process from attacker and in return could deviate the route of attacker to some virtual nodes and links. A simple trust based mechanism is constructed for validating the legitimacy of such request generated from adversary node. The proposed system not only presents a security solution but also assists in enhancing the routing process significantly. The simulated outcome of the study shows that proposed system offers significantly good energy conservation, satisfactory data forwarding performance, reduced processing time in contrast to existing standard security practices.
A Survey on Security Issues to Detect Wormhole Attack in Wireless Sensor Networkpijans
Sensor nodes, when deployed to form Wireless sensor network operating under control of central authority
i.e. Base station are capable of exhibiting interesting applications due to their ability to be deployed
ubiquitously in hostile & pervasive environments. But due to same reason security is becoming a major
concern for these networks. Wireless sensor networks are vulnerable against various types of external and
internal attacks being limited by computation resources, smaller memory capacity, limited battery life,
processing power & lack of tamper resistant packaging. This survey paper is an attempt to analyze threats
to Wireless sensor networks and to report various research efforts in studying variety of routing attacks
which target the network layer. Particularly devastating attack is Wormhole attack- a Denial of Service
attack, where attackers create a low-latency link between two points in the network. With focus on survey of
existing methods of detecting Wormhole attacks, researchers are in process to identify and demarcate the
key research challenges for detection of Wormhole attacks in network layer.
Analysis of security threats in wireless sensor networkijwmn
Wireless Sensor Network(WSN) is an emerging technology and explored field of researchers worldwide
in the past few years, so does the need for effective security mechanisms. The sensing technology
combined with processing power and wireless communication makes it lucrative for being exploited in
abundance in future. The inclusion of wireless communication technology also incurs various types of
security threats due to unattended installation of sensor nodes as sensor networks may interact with
sensitive data and /or operate in hostile unattended environments. These security concerns be addressed
from the beginning of the system design. The intent of this paper is to investigate the security related
issues in wireless sensor networks. In this paper we have explored general security threats in wireless
sensor network with extensive study.
This article presents a study of the state of the art of sensor networks wireless systems, which continue to develop and present a wide variety of Applications. These networks constitute a current and emerging field of study where combines the development of computers, wireless communications and devices mobile phones and integration with other disciplines such as agriculture, biology, medicine, etc. I know presents the main concept, components, topologies, standards, applications, problems and challenges, then delves into security solutions and concludes with basic simulation tools.
THE UWB SOLUTION FOR MULTIMEDIA TRAFFIC IN WIRELESS SENSOR NETWORKSijwmn
Several researches are focused on the QoS (Quality of Service) and Energy consumption in wireless Multimedia Sensor Networks. Those research projects invest in theory and practice in order to extend the spectrum of use of norms, standards and technologies which are emerged in wireless communications.
The performance of these technologies is strongly related to domains of use and limitations of their characteristics. In this paper, we give a comparison of ZigBee technology, most widely used in sensor networks, and UWB (Ultra Wide Band) which presents itself as competitor that present in these work better results for audiovisual applications with medium-range and high throughput.
A NOVEL TWO-STAGE ALGORITHM PROTECTING INTERNAL ATTACK FROM WSNSIJCNC
Wireless sensor networks (WSNs) consists of small nodes with constrain capabilities. It enables numerous
applications with distributed network infrastructure. With its nature and application scenario, security of
WSN had drawn a great attention. In malicious environments for a functional WSN, security mechanisms
are essential. Malicious or internal attacker has gained attention as the most challenging attacks to
WSNs. Many works have been done to secure WSN from internal attacks but most of them relay on either
training data set or predefined thresholds. It is a great challenge to find or gain knowledge about the
Malicious. In this paper, we develop the algorithm in two stages. Initially, Abnormal Behaviour
Identification Mechanism (ABIM) which uses cosine similarity. Finally, Dempster-Shafer theory (DST)is
used. Which combine multiple evidences to identify the malicious or internal attacks in a WSN. In this
method we do not need any predefined threshold or tanning data set of the nodes.
Protocols for Wireless Sensor Networks and Its SecurityIJERA Editor
This paper proposes a protocol for Wireless Sensor Networks and its security which are characterized by severely constrained computational and energy resources, and an ad hoc operational environment. The paper first introduces sensor networks, and discusses security issues and goals along with security problems, threats, and risks in sensor networks. It describes crippling attacks against all of them and suggests countermeasures and design considerations. It gives a brief introduction of proposed security protocol SPINS whose building blocks are SNEP and μTESLA which overcome all the important security threats and problems and achieves security goals like data confidentiality, freshness, authentication in order to provide a secure Wireless Sensor Network
Determining an Optimal Number of Access Points Using GPS data to Secure a Wir...CSCJournals
Determination of the position enables location awareness for mobile computers in any place and persistent wireless computing. In addition utilizing location information, location aware computers can render location based services possible for mobile users. In order to design and implement a technique to identify the source network interface card, a feasibility study should be done to keep the project within the budget; also tracking of new technologies will enhance the methodology of choosing these techniques. Wireless Local Area Network (WLAN) is vulnerable to malicious attacks due to their shared medium in unlicensed frequency spectrum, thus requiring security features for a variety of applications. This paper will discuss a technique that helps in determining the best location for access points using GPS system, in order to choose the optimal number of them; which guide to localize and identify attacks with optimal IDS method and cheapest price. The other thing is to locate the intruder within the monitored area by using a hybrid technique, which came from exist techniques, by focusing on the advantages of these techniques and come with a new one to give more accurate results with less price by using available resources
Wireless Networks Security in Jordan: A Field StudyIJNSA Journal
The potential of wireless communications, has resulted in a wide expand of wireless networks. However, the vulnerabilities and threats that wireless networks are subjectedto resulted in higher risk for unauthorized users to access the computer networks.This research evaluates the deployed Wireless Network in Jordan as well as the use of the security setting of the systems and equipment used. Caution will be taken to avoid network access as only existence of the network is sought. Wardriving involve the use of freeware tools such as NetStumbler, or Kismet, which was originally developed to be used for helping network administrators make their systems more secure. Thestudy is carried out through field evaluation of the Wireless Local Area Network (WLAN)in light of the use of Wardriving, and proposessome measures that can be taken to improve securityof the wireless network by the users.
REAL TIME SECURING OF ALL-OPTICAL NETWORKS AGAINST SECURITY ATTACKS AT THE PH...IJNSA Journal
This paper deals with protecting all-optical networks (AON) from security attacks at the physical level. It firstly presents an overall high level protocol for establishment, management and on-the-fly restoration of optimal secure lightpaths established by applying constraint-based open shortest path first (OSPF) source routing using proposed security databases of components. Secondly it presents a protocol for using fiber diversity between adjacent nodes to protect against attacks on fiber links. Thirdly it presents analytical models of propagation of security attacks on optical amplifiers and switches. These models are then used to develop security envelopes around these components, to calculate security indices and on-the-fly real-time restoration of components in case of an attack. Fourthly it presents simulation results for evaluation of the performance of these on-the-fly restoration schemes. These on-the-fly restoration schemes eliminate need for tearing down of attacked lightpaths and prevent consequent loss of large amount of data.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
1. Feature Article: DOI. No. 10.1109/MAES.2020.2970262
Interference and Intrusion in Wireless Sensor
Networks
George D. O’Mahony, University College Cork, Cork, Ireland
James T. Curran, European Space Agency, Noordwijk, Netherlands
Philip J. Harris, United Technologies Research Center Ireland, Cork, Ireland
Colin C. Murphy, University College Cork, Cork, Ireland
INTRODUCTION
The use of wireless sensor networks (WSNs) in safety crit-
ical applications, such as space-based WSNs [1] and the
Internet of Things (IoT) [2], creates new challenges in
terms of security and spectral coexistence. Unlike tradi-
tional wireless networks, (e.g., Bluetooth and WiFi) the
use of WSNs in safety critical applications imposes strict
security and availability requirements on computationally
constrained devices. A diverse range of these safety criti-
cal WSN applications exist, where robustness against
harsh environments and maintaining low power operation
need to be considered. These applications include,
amongst others, wireless networked control systems [3],
space applications, for example, in-orbit demonstration of
an IEEE 802.15.4 protocol-based WSN on the Interna-
tional Space Station [4] and space wireless local area net-
works [5]. Also, due to advances in the development of
WSN architectures [6], Low Earth Orbit satellites can be
used as WSN components [7] to receive aggregated pack-
ets from WSN relay nodes. Additionally, WSNs are being
utilized in aerospace applications for aircraft control and
health management systems [8] as a first step toward fly-
by-wireless and increased monitoring capabilities. These
WSNs are extensively used in traditional monitoring and
control applications, such as, for example, environmental
and surveillance [9]. Uniquely, arrays of nanosatellites are
used in a WSN approach to enhance mobile communica-
tions through lower cost, space-based mobile phone serv-
ices [10]. In modern society, the emerging IoT [2], which
leverages WSNs, is leading to the truly connected world
and smart homes/businesses. Each of these infrastructures
and applications require protection and attack detection,
as any attack could have significant consequences for pri-
vacy and safety.
Security and availability of the communication link
are essential for any safety-critical wireless system. These
requirements are vital as WSNs develop into an indispens-
able component of modern technology. Simultaneously,
spectrum coexistence issues emerge, for example, in the
industrial, scientific, and medical (ISM) 2:4 GHz radio
frequency (RF) band. This is mainly due to (often change-
able) large number of connected devices potentially run-
ning different protocols at the same frequency, location,
and time. These spectral issues add complexity to provid-
ing the necessary security and availability in WSNs, which
are typically composed of multiple autonomous, low cost,
resource-limited, and low power sensor nodes running on
a finite energy supply and an open interface protocol for
interoperability between devices. Nodes gather data from
their environment and often collaborate to transmit the
sensed data to a centralized sink, cluster head, or relay
node. In general, WSNs need to share the frequency spec-
trum with multiple services and need to coexist with both
similar and different protocols. WSNs are self-organizing,
self-repairing, and operate a dynamic topology, which
brings both resilience to natural faults as well as a vulnera-
bility to malicious attacks. Due to their design, application
space and spectrum occupancy, a need for intrusion detec-
tion and security against both malicious and unintentional
interference is warranted.
This article uses critical WSN applications as a case
study to provide a review of WSN vulnerabilities,
Authors’ current addresses: George D. O’Mahony and
Colin C. Murphy, Department of Electrical and Electronic
Engineering, School of Engineering, University College
Cork, T12 YN60 Cork, Ireland E-mail: (george.
omahony@umail.ucc.ie, colinmurphy@ucc.ie); J. T. Curran,
European Space Agency, 2201, AZ, Noordwijk, Nether-
lands E-mail: (jamestcurran@ieee.org); P. J. Harris, United
Technologies Research Center Ireland, T23 XN53 Cork,
Ireland E-mail: (harrispj@utrc.utc.com).
Manuscript received June 5, 2019, revised December
16, 2019; accepted January 17, 2020, and ready for
publication January 27, 2020.
Review handled by Peter K. Willett.
0885-8985/20/$26.00 ß 2020 IEEE
4 IEEE A&E SYSTEMS MAGAZINE FEBRUARY 2020
Authorized licensed use limited to: James Cook University of Northern Queensland. Downloaded on April 23,2020 at 19:46:02 UTC from IEEE Xplore. Restrictions apply.
2. security, and attacks, including coexistence intrusions.
ZigBee is studied through Monte-Carlo simulations and
benchtop experiments to highlight WSN security issues
and the need for intrusion detection. An intrusion detec-
tion system (IDS) is used to identify the presence of
intruders. Commercial-off-the-shelf (COTS) devices and
standardized protocols are used due to the general trends
toward the use of COTS components in commercial IoT
networks and in space applications. Both areas, typically,
favor high redundancy, high replenishment rates over
custom-built components. Examples include the interna-
tional space station [4], intersatellite communication
modules [1], and nanosatellite swarms [11]. WSNs are
commonly deployed in environments where the spectrum
changes rapidly due to the number of connected devices,
demand, packet size or services in operation and changes
in the physical environment due to varying fading levels,
obstacles, path losses, and spurious interference. Beyond
these nonmalicious factors, critical WSN applications
may incentivize malicious attackers to intentionally dis-
rupt or compromise network operation. Presently, WSNs
are highly susceptible to attacks, especially Denial of
Service (DoS) [12] attacks and, as WSN operating envi-
ronments become more diverse and attack techniques
develop, security improvements are required. The chal-
lenges of system coexistence add even more complexity
and need to be examined, as many modern WSN proto-
cols adopt the same physical (PHY) and/or medium
access control (MAC) layers [9]. This phenomenon is
explored by investigating the IEEE 802.15.4 PHY and
MAC layers, which are utilized by ZigBee and by vari-
ous WSN protocols.
The remainder of this article is organized as follows.
The “Related Work” section gives a brief description of
related work, the “Signal Model” section outlines the sig-
nal model used as a case study, and the “Operating
Assumptions” section provides adopted assumptions. The
“Security in Wireless Sensor Networks” section summa-
ries security in WSNs, the “Attacks on Wireless Sensor
Networks” section describes various WSN attacks, and
the “Discussion: Attacks on WSNs” section discusses
specific attacks using Monte-Carlo simulations and bench-
top tests. Finally, the “Future Directions” section provides
future directions for enhancing WSN IDS design and secu-
rity and the “Conclusion” section concludes this article.
RELATED WORK
Interference and intrusion detection is not a new area in wire-
less communication systems, but it is an area which requires
expansion and enhancements to match the current trend of
WSNs. Security for WSNs is the most relevant work which
relates to this article and includes investigating applied secu-
rity techniques [9], threats to WSNs [13], how to secure
WSNs [14], and existing security issues in WSN proto-
cols [15]. Additionally, related work includes research into
WSN attacks, where Shanthi and Rajan [16] provides a brief
overview of attacks and detection methods and the work in
[17] and [18] focuses on jamming attacks and associated
detection measures only. Flexible and reliable software-
defined reactive jamming is shown to be feasible in [19],
which provides attack deployment evidence for the previous
descriptive studies. DoS attacks are outlined in [12], which
also states that security is the linchpin of good sensor network
design and detection can aide deployments. Research on
intrusion detection and IDSs include using traditional techni-
ques such as analyzing the received signal strength or packet
delivery rate [20] and machine learning algorithms devel-
oped specifically for detecting intrusions on WSNs [21].
These machine learning techniques use features such as
packet collision ratio, delivery waiting time, and power con-
sumption rate, to name but a few. Detailed surveys on intru-
sion detection in WSNs, the main concepts, and the vital
areas can be found in [22] and [23]. However, this type of
research is not confined to WSNs as it is a current research
topic across wireless networks, in general, including global
positioning system signals [24], WiFi signals [25], and the
coexistence of wireless systems [26]. This article provides its
contribution by summarizing WSN security, vulnerabilities,
interference and intrusion attacks, and detection methods. In
contrast, the literature above, typically, focuses on a specific
Credit: Forbes, Sep. 27, 2017
FEBRUARY 2020 IEEE A&E SYSTEMS MAGAZINE 5
Authorized licensed use limited to: James Cook University of Northern Queensland. Downloaded on April 23,2020 at 19:46:02 UTC from IEEE Xplore. Restrictions apply.
3. type of attack and the associated detection process. Hereafter,
critical WSN applications and an adopted WSN protocol are
used as a case study to provide a review of WSN vulnerabil-
ities, security and attacks, including coexistence intrusion.
Notably, this article discusses WSN attacks in terms of both
the unlawful transmitter and the noncompliant spectrum
user. Whilst existing research focuses on malicious spectral
intrusions in terms of jamming attacks, this article highlights
the idea of using coexisting signals as malicious intruders.
This article’s contribution is expanded by highlighting the
need to focus on WSN jamming for IoT penetration testing
and deployment security.
SIGNAL MODEL
Here, the IEEE 802.15.4 based wireless protocol for low
rate wireless personal area networks (LR-WPAN), Zig-
Bee, is the chosen signal model, since, currently, it is the
de facto standard for WSNs (as almost all available com-
mercial and research sensor nodes are equipped with Zig-
Bee transceiver chips [27]). The operating topology is
either star, mesh or peer-to-peer and, in each case, is self-
organizing, self-repairing, dynamic, and can exploit clus-
tering approaches [15]. Cluster heads are, typically, used
as relay nodes which aggregate and forward data to a cen-
tralized sink. An example is using nanosatellites as relay
nodes (cluster head), allowing access to remote areas by
using the nanosatellites as links between each cluster and
centralized sink [7]. ZigBee is constructed using the PHY
and MAC from IEEE 802.15.4 and uses a protocol-spe-
cific network layer, application support sublayer, and
application object layer [28]. Relevant PHY parameters
are shown in Table 1 and three different frequency bands
are supported: a 2.4 GHz band (16 channels), a 915 MHz
band (10 channels), and an 868 MHz band (1 channel).
Here, the 2.4 GHz band is selected and the 16 available
2 MHz wide channels, which range from
2400!2483.5 MHz and have an interchannel gap of
3 MHz, have center frequencies as per (1), where Fc and i
are the center frequency and channel number, respectively
Fc ¼ 2405 þ 5ði 11ÞMHz; for i ¼ 11; 12; . . . ;26: (1)
These frequencies are transmitted in the unlicensed
ISM frequency band and must coexist with various signals
including Bluetooth, numerous LR-WPAN, wireless local
area networks, and wireless metropolitan area networks.
Due to the unlicensed operation, global availability, and
relatively long-range, the ISM frequency band is the first
choice for wireless LAN solutions. To gain access to the
wireless channel, ZigBee uses carrier sense multiple
access with collision avoidance (CSMA/CA). Prior to
transmitting a packet, devices perform a clear channel
assessment to ensure the channel is available. This
technique is particularly vulnerable to DoS attacks and
spectrum-sharing difficulties.
ZigBee uses direct sequence spread spectrum (DSSS)
to split each outgoing byte into two 4-bit symbols, four
most significant bits and four least significant bits. Each
symbol is spread to a 32-bit pseudonoise sequence from a
predefined mapping table. Chip sequences are encoded
using offset quadrature phase-shift keying (O-QPSK) with
half-sine/normal raised cosine pulse shaping. Matlab sim-
ulations, using random payload bits, produced the exam-
ple in-phase and quadrature phase (IQ) data in Figure 1(a)
and associated IQ diagram, which illustrates the constant
envelope nature of the signal, in Figure 1(b). The equiva-
lent energy-per-bit ðEbÞ can be calculated using the period
over which one byte is broadcast ðTByteÞ and (2), where C
is the signal power in Watts.
Eb ¼
TByte C
8
J/bit (2)
The packet error rate (PER) for a ZigBee signal in a zero
mean additive white Gaussian noise (AWGN) channel was
calculated to illustrate normal operation (see Figure 2). A
range of energy-per-bit-to-noise ratios ðEb=N0Þ were applied
using a ZigBee frame (see Table 2) with a randomized pay-
load. The predicted PER was calculated using the probability
of receiving an incorrect symbol ðPeÞ, given 16 unique
DSSS pseudonoise codes and an AWGN channel. Assuming
a matched filter receiver, the symbol error probability can be
expressed as (3), where s in (4) is the variance, erfðÞ is the
error function, and L is the number of codes. The correspond-
ing PER is estimated using (5), where NBytes is the number
of bytes per packet
Pe ¼ 1
Z 1
1
eð1þyÞ2
2s2
ffiffiffiffiffiffi
2p
p
s
1
2
þ
1
2
erf
y
ffiffiffi
2
p
s
L1
dy (3)
Table 1.
ZigBee PHY Parameters
Parameter: 2.4 GHz PHY Value:
Number of channels 16
Channel spacing/width 5 MHz 2 MHz
Data | Symbol rate 250 kb/s 62:5 ksymbols/s
Chip rate 2 Mchips/s
Modulation O-QPSK
Pulse shaping Half sine/normal raised
cosine
Spreading DSSS
Maximum packet
length
133 B
Interference and Intrusion in Wireless Sensor Networks
6 IEEE AE SYSTEMS MAGAZINE FEBRUARY 2020
Authorized licensed use limited to: James Cook University of Northern Queensland. Downloaded on April 23,2020 at 19:46:02 UTC from IEEE Xplore. Restrictions apply.
4. s ¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffi
1
2EbNo
r
(4)
PER ¼ 1 ð1 PeÞ2NBytes : (5)
The results express the PER for received packets across
an AWGN channel for normal operating conditions. How-
ever, as will be discussed later, other considerations, includ-
ing miss-routing of packets, erroneous transmissions or
attacks, may occur. The predicted and simulated results
begin to differ as the PER reduces because the mathematical
model assumes the pseudonoise codes are orthogonal but, in
reality, there is a nonzero cross correlation.
OPERATING ASSUMPTIONS
Based on the literature, certain operating assumptions are
made, which focus on IDSs and how wireless networks react
to an intrusion. Traditional wireless network operation, typi-
cally transmitted packets, and attack methods were exam-
ined and the assumptions adopted herein are as follows.
1) A reliable routing protocol is used and a packet can
always reach the base station, and other nodes,
when no attacks are present [20].
2) Basic jamming hardware in use may be similar to
network nodes [20], but notably does not have to
adhere to any standards, guidelines, or rules.
3) Attackers can use advanced hardware (e.g., soft-
ware-defined radios (SDRs) and computers) without
adhering to standards, guidelines, or rules. [29]
4) The attacker can place/seize one or more basic sens-
ing nodes in the network [20]. These basic sensing
nodes have limited resources and energy supplies,
which hinder the use of complex security algo-
rithms. Control nodes contain more advanced hard-
ware and, as a result, are more difficult to seize.
5) Nodes at the edge of a jammed region can receive
messages from “jammed” nodes and relay alarms to
the controller and/or base station [30].
6) Intelligent jammers can monitor the network and
determine the protocols being used [31].
7) Nodes can be deployed in environments where the
possibility of being captured exists [16]. Captured
Figure 1.
Visual representation of transmitted ZigBee signal. (a) Simulated ZigBee O-QPSK modulated IQ data, with the IQ chip offset and chip
duration labeled. (b) IQ diagram for the transmitted ZigBee signal.
Figure 2.
Predicted and simulated PER for a ZigBee signal over a range of
energy-per-bit to noise ratios.
Table 2.
ZigBee PHY Frame
Synchronization
Header
(SHR)
PHY
Header
(PHR)
PHY
Service Data
Unit (PSDU)
Preamble SFD Length Payload CRC
4 B 1 B 1 B 0–125 B 2 B
O’Mahony et al.
FEBRUARY 2020 IEEE AE SYSTEMS MAGAZINE 7
Authorized licensed use limited to: James Cook University of Northern Queensland. Downloaded on April 23,2020 at 19:46:02 UTC from IEEE Xplore. Restrictions apply.
5. (malicious) nodes can be used to implement attacks
on the network and can gain access to sensitive
data. An example includes a black hole attack [32],
which “pulls in” network traffic by listening to route
requests and replying that it has the shortest path.
The node can, potentially, alter, reject, or replay
received packets. The “Attacks on Wireless Sensor
Networks” section discusses other attack strategies
for malicious nodes.
Application specific assumptions also exist, for example,
encryption and/or a key management system for data privacy
may be of high importance in some applications, while other
systems might implement origin authentication and data
integrity but not encryption. Certain applications may not
use any mitigation strategies, while critical applications may
use DSSS, frequency hopping spread spectrum or a frame
check sequence to fortify against external interference. Con-
sequently, an application’s environment and the prevailing
external factors will govern operating conditions.
SECURITY IN WSNS
WSN applications require security, particularly when the
networks are designed for use in hostile environments,
military, aerospace, commercial, or IoT applications [23].
Compared to other wireless networks, securing WSNs to
an appropriate level is challenging as, typically, WSNs
have certain unavoidable challenges [9], which form a
unique combination of vulnerabilities.
1) Open interface: Normally, protocols are unavoid-
ably known publicly due to the requirement for
interoperability between devices and protocols.
Wireless channels are open to anyone with suitable
equipment, enabling specific WSN attacks and
access to transmitted signals.
2) Device resources: Typically, devices are deployed,
left unattended, must operate on a finite energy sup-
ply and, for reasons of cost, have low processing
power, memory, physical storage, and speed. Gener-
ally, these constraints hinder the use of conventional
security methods.
3) Operating environments: Regularly, WSNs are
deployed without any fixed infrastructure in hostile or
remote environments, where it is difficult to have con-
tinued surveillance. Often, deployed legitimate net-
work nodes become physically available to attackers
and are susceptible to being captured. Therefore, a suf-
ficiently high probability of node secrets being discov-
ered and/or nodes being made malicious may prevail,
thereby obliging countermeasure(s). Tamper proofing
nodes is possible, but may not be appropriate/available
for all types of networks/nodes due to, for example,
cost restrictions.
4) Topology: WSN topologies can be dynamic and so
changes are expected due to variations in the chan-
nel/environment (e.g., fading levels, obstacles, path
losses, spurious interference, etc.), which may lead
to the “death” of network nodes and topology
reconfiguration.
5) Hardware availability: Reconfigurable hardware, suit-
able for attacking networks, is becoming increasingly
available/accessible to a wider set of users/potential
malicious actors, who can readily design and deploy
more computationally expensive attacks [29].
6) Deployment diversification: As WSN applications
continue to expand, the range of operating condi-
tions, use cases, and created data widen.
Inclusive of the WSN vulnerabilities above, certain
security features are required [13], [14].
1) Confidentiality: The secrecy of important data being
transmitted in the wireless channel must be main-
tained. Classical cryptography can be adopted to
encrypt critical data prior to transmission. However,
a strict key management system may prove difficult,
given WSN device resources.
2) Authenticity: Verifying packet authenticity is essen-
tial as the receiving node should be able to autono-
mously assert that the received packet has not been
modified in transit (data integrity), and from which
node the packet originated (origin authenticity).
Cryptographic schemes, such as digital signatures,
can simultaneously provide both functionalities.
Without this security aspect, attackers could spoof
node identities and spread false information through-
out a WSN.
3) Availability: WSNs need to provide services when-
ever they are required and, therefore, need to exhibit
qualities of robustness against a variety of impair-
ments, both benign and malicious. Some degree of
resilience (i.e., the ability to recovery from faults),
diagnostics (i.e., able to identify why services became
unavailable), or mitigation strategy (packet rerouting,
channel switching, etc.) is necessary. Appropriate use
of an IDS may help to ameliorate the network’s
availability.
4) Energy: Unique to WSNs, the constrained energy
levels impact upon all security plans. Typically,
nodes have a limited energy supply and, so, any
security protocol or detection mechanism needs to
take this energy constraint into account, since opti-
mizing energy usage is vital for network longevity.
5) Data freshness: Critical data circulating in a WSN
must be the most recent update and, as such, out-
dated data should not circulate in a network.
Interference and Intrusion in Wireless Sensor Networks
8 IEEE AE SYSTEMS MAGAZINE FEBRUARY 2020
Authorized licensed use limited to: James Cook University of Northern Queensland. Downloaded on April 23,2020 at 19:46:02 UTC from IEEE Xplore. Restrictions apply.
6. 6) Node ability: WSN nodes must be self-organizing,
react to node/link failures and only authorized nodes
should be allowed to operate and share information
in a WSN.
Evidently, no WSN will be 100% secure and it is
extremely difficult to design a WSN where attackers can-
not find some way in [23]. Timely mitigation strategies
are required to combat attacks that exploit the WSN vul-
nerabilities. This provides a need for security measures
which are either preventive, reactive, or detective solu-
tions [15]. Preventive measures include cryptography,
spreading codes, frequency hopping, frame check sequen-
ces, etc. [9]. An IDS identifies the presence of intruders,
so mitigation (or reactive) strategies can be implemented.
The fundamentals of intrusions and intrusion detection
were defined by James Anderson in 1980 and are; risk,
threat, attack, vulnerability, and penetration [33]. Addi-
tionally, an IDS includes the delicate balance between
detection and false-alarm rates, which can be particularly
challenging in environments where many different physi-
cal layers occupy the same spectrum. Intrusion detection
can be achieved using different methods [22], [30].
Misuse detection compares the action or behavior of
transmitting/receiving nodes to well known attack
patterns. These attack signatures form the knowl-
edge base of the IDS.
Anomaly detection defines the characteristics of
normal operation and activities and transmissions
are compared against this normal operation. The
IDS classifiers outliers, which are activities different
from normal, as intruders.
Hybrid or specification-based detection includes
IDSs which do not conform to anomaly or misuse.
Normal behavior is manually defined by human per-
ception. The focus is to determine deviations from
this normal behavior, when it is not defined by train-
ing data or machine learning algorithms. Certain
hybrid approaches can combine both anomaly and
misuse detection.
The above discussion highlights the fact that security
plays a major role in WSNs, is integral for any successful
WSN-based critical application and, typically, four pillars
of WSN security exist; vulnerabilities, requirements,
attacks, and defenses [34]. Typically, networks have
defined requirements, e.g., confidentiality, and employ
specific defense strategies (encryption) to ensure each
requirement is met. Networks, especially WSNs, have vul-
nerabilities and attacks can use these vulnerabilities to,
potentially, increase attack efficiency. A notable example
is the finite energy supply and, thus, attackers can focus
on this vulnerable point. Therefore, this implies that
the identified four pillars suit WSN security analysis. Fur-
thermore, given the three-dimensional model for reliability
provided in [35], a similar approach can be taken for secu-
rity, as provided in Figure 3, which establishes a functional
model for security using certain parameters. This model
provides a simplified visual representation of some avail-
able security setups for WSNs. The specified model analy-
ses whether a preventive, reactive, or detection approach is
used as the security mechanism, is a hop-by-hop or end-to-
end basis applied and is security event-triggered or on each
individual packet. Here, hop-by-hop refers to maintaining
security across each and every link and end-to-end refers to
only the source and destination maintaining security. Fur-
thermore, typically, reliability provides bit loss recovery
whilst security specifies bit loss prevention. Therefore, the
topics can be linked in terms of packet loss and the model
in [35] readily adapts to security.
ATTACKS ON WSNS
Attacking a WSN involves either unauthorized access to
data, data manipulation, or denial of system services.
These WSN attacks can be categorized into either passive
or active attacks [13]. Passive attack styles do not modify
information or messages but, instead, aim to learn the
transmitted confidential data. Initially, this does not appear
to have severe consequences, especially if data is
encrypted. However, over time and given enough captured
data, reverse engineering can provide the protocol in use
and grant network access or packet decryption, which
results in multiple network security consequences. In con-
trast, active attacks aim to modify/remove streams of data,
cause a DoS, disturb functionality or disguise an attack as
a legitimate node. For convenience, a selection of known
attacks on WSNs are categorized and described, where the
focus is placed on PHY and MAC layer attacks, including
jamming and congestion style intrusions. Generally, it is
envisaged that external attacks, for example, jamming,
will be implemented using an SDR approach. This hard-
ware provides the necessary ability to receive, analyze,
and transmit. The internal attacks, for example, sinkhole,
will, typically, use a WSN device that has been captured
or identified. Attack effectiveness and/or affected area,
Figure 3.
A functional simplified model for visualizing different security
options in WSNs.
O’Mahony et al.
FEBRUARY 2020 IEEE AE SYSTEMS MAGAZINE 9
Authorized licensed use limited to: James Cook University of Northern Queensland. Downloaded on April 23,2020 at 19:46:02 UTC from IEEE Xplore. Restrictions apply.
7. typically, depends on the strength of the transmitting
power or how “transparent” the approach needs to be.
CONVENTIONAL JAMMING ATTACKS
These active attacks, typically, aim to overpower the legit-
imate signal with spurious RF transmissions. While higher
jamming power increases attack effectiveness, it also
boosts detectability. As such, the adversary is typically
driven to optimize signal interference to maximize packet
loss, while minimizing total broadcast power. Such attacks
include the following.
1) The constant jammer continuously emits RF signals of
random data into the wireless medium without follow-
ing any MAC protocol, can be readily detected and is
energy inefficient. However, this jammer can be easily
implemented and causes severe damage to a WSN, as
congestion or destruction of packets can be achieved
and the channel can appear permanently busy.
2) The deceptive jammer regularly transmits protocol
specific packets into the network without pausing
between successive packets, thereby preventing nor-
mal sources from transmitting successfully. Due to
the transmission of legitimate packets, it is more
difficult to detect than a constant jammer and can
cause considerable damage in WSNs adhering to
MAC protocols, which are sensing for channel
access or the presence/absence of a signal.
3) Random jammers sporadically transmit random pack-
ets of data and conserve energy by switching between
the jamming state, when jamming signals are emitted,
and the sleeping state, when all transmissions are
ceased. This unpredictable behavior makes this jam-
mer difficult to mitigate and can cause similar levels
of damage as the constant and deceptive jammers.
4) A reactive jammer [19] operates in idle mode until
some legitimate activity is detected on the wireless
channel. An RTS/CTS jammer detects request to send
(RTS) messages and interferes with the channel to
block any clear to send (CTS) messages, thereby
denying further communications. Data acknowledg-
ment jammers corrupt acknowledgment packets after
a transmission has been sensed in the network and
misleads nodes to decide that packets were undeliv-
ered, thereby invoking a retransmission and, poten-
tially, resulting in the exhaustion of the power supply.
This is particularly effective in protocols, such as Zig-
Bee, which use CSMA/CA.
5) Specific function jammers perform explicit functions,
depending on their calibration, and cause jamming on
either a specific channel or across an entire network,
while minimizing their energy consumption or
maximizing their attack effect. For example, follow-
on jammers jam one specific frequency at a time and
maximize packet loss by continuously hopping
between the channel frequencies. These jammers can
be detected but are very effective, particularly in net-
works that use frequency hopping spread spectrum or
when identified spectrum holes [36] are used to
improve performance through spectrum sharing.
Another example is the channel-hopping jammer,
which follows a predefined pseudorandom sequence
of channels and starts jamming at different time slots
according to this sequence. By overwriting the
sequence, multiple channels can be jammed at the
same time. Finally, pulse noise jammers can be pro-
grammed to switch between different channels/band-
widths and conserve energy by temporarily halting
transmissions.
INTELLIGENT JAMMING ATTACKS
Intelligent jammers are a combination of a passive and an
active attack, as the jammer initially targets network pri-
vacy before inevitably targeting data packets. These devi-
ces are more likely to cause jamming but are harder to
implement than conventional jammers [29]. Protocol
aware and statistical jammers aim to determine the MAC
protocol being used by the victim’s network in order to
launch energy efficient attacks [31]. Protocol aware jam-
mers know the MAC layer operating rules and can deprive
legitimate nodes of access to the channel and can, poten-
tially, affect services identifying free channels or spectrum
holes, used to, potentially, enhance spectrum coexis-
tence [36]. Statistical jammers observe the packet interar-
rival time distribution and, based on its estimation, emit
pulses of jamming signals to disrupt communications
(DoS attack). Once the estimation is achieved, energy effi-
ciency can be increased through pulse jamming. Collision
makers target the identified acknowledgment packets by
inhibiting transmissions. Certain intelligent jammers iden-
tify the cluster head/sinks by monitoring the network traf-
fic and focus attacks on that specific node in an
‘‘intelligent cluster head attack.” Learning-based jam-
mers, like LearJam, have been produced to attack low
duty cycle networks where nodes sleep most of the time (a
typical WSN characteristic) and consist of a learning
phase, wherein the node transmission pattern is observed,
and an attacking phase, where these transmissions are
compromised. Therefore, clearly attackers are now able to
learn the MAC and/or protocols in use by eavesdropping
(privacy attack) on the channel for some period of time.
This attack style could, for example, be launched on tech-
niques for sensing the presence or absence of a signal
(CSMA/CA or spectrum sharing), by learning when a ser-
vice should be idle and producing “dummy” packets to
avert potential transmissions.
Interference and Intrusion in Wireless Sensor Networks
10 IEEE AE SYSTEMS MAGAZINE FEBRUARY 2020
Authorized licensed use limited to: James Cook University of Northern Queensland. Downloaded on April 23,2020 at 19:46:02 UTC from IEEE Xplore. Restrictions apply.
8. MAC LAYER JAMMING ATTACKS
These are, initially, passive attacks that react to the net-
work protocol in use by eavesdropping on or sniffing
transmitted packets to gain access to network informa-
tion. The analyzed results are used to implement active
attacks including replay attacks, spoofed packets, or
forcing a device to remain in listening mode, which
exploits CSMA/CA. These are not jamming attacks but,
instead, try to mislead WSN devices. Replay attacks
should be negated by the use of message integrity
codes. However, due to hostile deployment scenarios,
secrets may be accessible as legitimate nodes may be
physically available and, if no key management system
is in use (home personal COTS network), devices may
be available commercially and the keys extracted from
device memory.
NETWORK LAYER ATTACKS
Generally, these are active attacks that interfere with net-
work operations causing either a DoS, a privacy or an
impersonation attack.
1) Sinkhole/blackhole attacks: In this congestion-
based DoS attack, a malicious node acts like a black
hole [32] and “pulls in” all of the traffic in the net-
work. The malicious node listens to the route
requests and replies that it has the shortest path,
maximizing packet flow.
2) Selective forwarding: Networks that rely on multihop
transmissions require all nodes to faithfully forward
any received packets to the base station. In this packet
dropping DoS attack, a malicious node in the routing
path selectively drops sensitive packets.
3) Node replication attacks: In WSNs, nodes are often
deployed in unattended public environments where
continued surveillance is unrealistic. In this imper-
sonation attack, an attacker may replicate a legiti-
mate node and introduce it to the network, thereby
gaining access to the flow of packets throughout the
network. This may involve the capture and analysis
of a legitimate node in cases where some level of
cryptographic security is applied.
4) Sybil attacks: Many applications require node col-
laboration to accomplish a certain task. Applica-
tions can then implement management policies to
distribute subtasks to different nodes. In this
impersonation attack, a malicious node will pre-
tend to be more than one node at the same time,
using the identities of other legitimate nodes to
effectively cause collaboration processes to fail
and can target data aggregation, routing mecha-
nisms, etc.
5) HELLO flood attacks: Often, routing protocols need
to broadcast “HELLO” packets in order to discover
one-hop neighbors. The attacker exploits this con-
cept to attract and persuade nodes that an attacker is
their neighbor. This is especially effective if the
attacking node has a large radio range and enough
processing power to flood an entire area of a net-
work, affecting a large number of nodes and persuad-
ing these nodes to use the attacker as a relay node in
the process. Packets are lost in this energy consump-
tion DoS attack due to, for example, distances being
too large for transmission as a node will try to trans-
mit to a nonneighbor (attacker).
6) Wormhole attacks: An attacker records the packets at
one location in the network and tunnels those packets
to another area in the network using a long range wire-
less channel or optical link. Attackers offer fewer hops
and less delay and entice nodes to use the attacker to
forward packets, thereby causing collisions and
packet loss in this DoS congestion attack.
7) Spoofing: Network nodes can become malicious and
provide an attacker network access, when nodes are
physically available in environments without con-
tinued surveillance and each individual node is not
tamper proofed due to, generally, cost reasons.
Spoofing is the method of disguising a communica-
tion from an unknown source as being from a
known, trusted source. It can severely harm any
WSN, as it is both difficult to detect and effective.
A spoofing situation can involve either an attacker
successfully identifying as a network node by falsi-
fying data or by transmitting falsified data with real
credentials from a malicious node. This type of
attack is difficult to detect and requires an IDS
which can identify node anomalies.
It is clear from analyzing the above attacks that a
detection algorithm which has both centralized and dis-
tributed features is optimal as the attacks in the
“Conventional Jamming Attacks,” “Intelligent Jamming
Attacks,” and “MAC Layer Jamming Attacks” sections
could be detected in a distributed structure, while certain
attacks in the “Network Layer Attacks” section will need
to be detected in a centralized structure and others in a dis-
tributed manner; for example, a black hole may fail to
generate application-level acknowledgments that can
imply network failure, even though the attacker is sending
protocol level acknowledgments. Another very interesting
point was highlighted in [37], which stated that, in future
attacks, more than one style will likely be used at the
same time and multiple layers will be attacked in a cross-
layer approach. For example, using a sinkhole attack to
guide packets to a specific region so a jammer could jam a
larger area.
O’Mahony et al.
FEBRUARY 2020 IEEE AE SYSTEMS MAGAZINE 11
Authorized licensed use limited to: James Cook University of Northern Queensland. Downloaded on April 23,2020 at 19:46:02 UTC from IEEE Xplore. Restrictions apply.
9. SYSTEM COEXISTENCE
This section identifies intrusions from spectrum coexis-
tence and spectrum sharing fields. Intrusions from the
coexistence of systems in the same frequency range and
when protocols misuse sharing capabilities are discussed.
1) A secondary user (SU) occupying a primary user’s
(PU) spectrum and causing interference. The SU
operates for too long or when the PU is operating
and interferes with the PU’s performance. The
intention was to maximize spectrum use but the SU
became an intruder.
2) An attacker or a certain spectrum user consumes all
resources and deliberately denies spectrum sharing,
causing other equal users to suffer performance loss
or DoS.
3) Specific users being saturated by coexisting legiti-
mate signals, leading to a DoS attack.
In these examples network performance is affected and,
so, intrusions exist. Clearly, an SU occupying a PU’s channel
for too long and affecting the PU’s performance becomes an
attacker. Resources can be denied by, for example, blocking
CTS packets, and so any device operating as such inherently
becomes an intruder. In spectrum sharing, a cognitive radio
(CR) senses for the absence of a PU (spectrum holes) [38]
and a user could block the discovery of these spectrum holes,
becoming an attacker in the process. This coexistence issue
will be examined in the “Discussion: Attacks on WSNs”
section using Monte-Carlo simulations and a spectrum ana-
lyzer in the ISM band.
DISCUSSION: ATTACKS ON WSNS
Particular WSN attacks and coexistence issues are dis-
cussed here by examining the ZigBee signal model,
described in the “Signal Model” section, and the PER,
which, typically, describes the success of an attack as a
successful intrusion can be attributed to resulting packet
losses. This subarea of attacks introduced in the “Attacks
on WSNs” section are of particular interest for the expand-
ing IoT sector, which leverages WSNs, and spectrum
usage. Intentional jamming and spectral coexistence serve
as an introduction into IoT penetration testing, where both
potential attackers and coexisting with other protocols and
systems are evaluated. Taking this approach can, poten-
tially, identify application weaknesses in terms of the
operating wireless channel, environment, and spectrum.
Furthermore, this focus on ZigBee’s PHY and MAC
depicts the performance of the IEEE 802.15.4 PHY and
MAC, which are implemented across a variety of WSN
protocols. Figure 4 contains a Matlab simulated subgroup
of jamming attacks and, to highlight the difficulties of a
congested spectrum, ISM band coexistence issues. The
effects of a constant jamming continuous wave (CW) jam-
mer, an AWGN jammer, an intelligent matched protocol
jammer (which here refers to a ZigBee signal and frame
structure (see Table 2) being used by an intruder to attack
a ZigBee network) and IEEE 802.11b coexistence are
demonstrated. The CW and matched protocol jamming
attacks were first discussed in [29], along with a practical
demonstration of the matched protocol interference. The
approach was practically tested using a ZigBee network of
five XBee nodes and an SDR. The SDR artificially created
an IEEE 802.15.4 signal and frame structure in Matlab/
Simulink to produce the matched protocol interference,
which caused a working network to fail. This was an
example of a learning-based jammer where the packet
structure was identified by eavesdropping on the open
interface of the WSN.
The CW response represents a simple jamming attack as
a sine wave is injected into the spectrum (added to signals
during simulations). The jammer-to-signal ratio (JSR) is
Figure 4.
ZigBee PERs for CW, matched, offset matched and 802.11b coexistence interference for a range of JSRs.
Interference and Intrusion in Wireless Sensor Networks
12 IEEE AE SYSTEMS MAGAZINE FEBRUARY 2020
Authorized licensed use limited to: James Cook University of Northern Queensland. Downloaded on April 23,2020 at 19:46:02 UTC from IEEE Xplore. Restrictions apply.
10. significantly higher for a disruptive PER and, therefore,
would be detectable in the spectrum. The CW response rep-
resents the operational mode of many jammers in the
“Conventional Jamming Attacks” section as it is, generally,
spurious interference. The matched protocol jammer simula-
tions show that it is more of a threat to WSNs than conven-
tional CW techniques, while adjacent channels (ZigBee
5 MHz) have little to no effect. At a JSR of 0 dB, the matched
interference causes a PER of approximately 0.18 and the sig-
nal structure matches expected signals in the channel. There-
fore, the matched interference is a threat at low JSR values
while simultaneously being difficult to detect. In both the
CW and matched protocol cases, once jamming power rises
above a certain threshold, substantial numbers of packets
will be lost, but this threshold is much lower when the inter-
ference is protocol specific. The AWGN interference is
included to show the difficulty in differentiating noisy con-
gested networks from attacks. The AWGN attack (white
noise across the spectrum centered on the channel) has more
of an effect on the signal than a CW jammer at JSR above
11 dB. Detecting these attacks would typically be based on
classical spectrum analysis exploiting higher signal powers
and offset spurs. However, matched signal interference,
which causes more damage than CW, is more difficult to
detect as packets resemble those of the network, meaning
that traditional spectrum approaches may not be appropriate.
This amplifies the need for IDSs to utilize extra available
analysis tools, for example, machine learning, as attackers
can discover and mimic WSN protocols and noisy environ-
ments can resemble attack situations.
The IEEE 802.15.4 based protocols (ZigBee) coexist
with various signals in the ISM RF band, including WiFi
(IEEE 802.11b). This phenomenon was simulated for the
802.11b 1 Mb/s DSSS protocol offset by 2, 3, and 7 MHz,
as these offsets relate to the offsets seen by a ZigBee signal
compared to the center of an 802.11b signal. For example,
802.11b channel 11 (2.462 GHz) and ZigBee channels 21
(2.455 GHz), 22 (2.460 GHz), and 23 (2.465 GHz). The
simulations show that other services can act as interference
(PER 0.1), given a high enough JSR (16.5 dB). These
coexistence issues were experimentally benchtop tested
using an XBee ZigBee peer-to-peer network, multiple PCs
and the Tektronix real time spectrum analyzer 306B using
a Siretta ZigBee stubby antenna. WiFi signals (campus
WiFi) and/or Bluetooth signals (local devices) were
provided by enabling laptops, phones, and speakers in the
vicinity around one XBee transceiver. The main hardware
utilized is provided in Figure 5, where the components are
close together for photographic convenience only, as the
transmitting and receiving XBee devices were sufficiently
separated during testing. Spectrum graphs are developed
using Tektronix’s digital phosphor technology (DPX),
which runs on the SignalVu-PC software package and
acquires signals in real time. DPX performs hardware digi-
tal signal processing and rasterizing of samples into pixel
information, which can be plotted in real time and as a bit-
map image (instead of a conventional line trace). This
allows signals to be distinguished at the same frequency
and a color scheme is used to identify signals which are
more frequent than others. Here, the 2475 MHz ZigBee
channel was used and a spectral DPX image is shown in
Figure 6(a), where the dark blue is the highest level and
corresponds to how frequent the signal is. All transmitted
and received packets were monitored by using DIGI’s
XCTU software, which provides a graphical user interface
for packet monitoring. Each transmission required an
acknowledgment packet, stating either “Delivery Status:
Success” for a successful transmission or “Delivery Status:
Address not found“ for an unsuccessful transmission. Real
time coexistence issues are visualized in Figure 6(b) and
(c), where the ZigBee signal coexisted with WiFi only and
WiFi/Bluetooth, respectively. Figure 6(d) provides the
spectral analysis for when packets were dropped in the net-
work. These unsuccessful transmissions were due to the
interference caused by multiple devices using WiFi and
Bluetooth in the vicinity of the intended XBee receiver.
This differs from Figure 6(c) due to both the higher power
interference signals at 2:475 GHz and recurring number of
transmissions, given by the fuller nature and more intense
color of the DPX image. Compared to Figure 6(c), Figure 6
(d) has approximately 6 dBm higher coexisting signals
and, due to a higher volume of connected devices, more fre-
quent ISM band transmissions. Essentially, these benchtop
tests provided visual proof of the spectrum coexistence
issues, the noisy environments, and legitimate signal intru-
sions which exist in WSNs. The undelivered packets,
which occurred under extreme coexistence circumstances,
provided evidence that environments and coexisting sig-
nals can be seen as both unintentional and, in malicious
cases, intentional interference. Therefore, the detection of
both intentional and unintentional interference is important
for providing a holistic IDS and adequate security.
Figure 5.
Hardware used in experimental setup to highlight the issues in a
congested spectrum and to produce the DPX spectrum graphs for
the signals of interest.
O’Mahony et al.
FEBRUARY 2020 IEEE AE SYSTEMS MAGAZINE 13
Authorized licensed use limited to: James Cook University of Northern Queensland. Downloaded on April 23,2020 at 19:46:02 UTC from IEEE Xplore. Restrictions apply.
11. Furthermore, other attacks (see the “Network-Layer
Attacks” section) on the upper layers of the protocol stack
can be detected by analyzing both the routing process and
network properties. However, detection can become skewed
if the attackers are subtle about their operation. For example,
monitoring network operation and implementing a sinkhole
attack that sporadically drops critical packets, which may
mimic PER levels resulting from a noisy environment, or a
wormhole attack tunneling only one of every N packets.
With the threat of legitimate nodes being captured, detection
and security mechanisms need to account for malicious
nodes in the network. Finally, it is clear that an attacker is
either an “outlaw” who breaks spectrum laws (excessive
radiated power) or a “noncompliant” operator who adheres
to broadcast power limitations but simply refuses to follow
protocol operation (service refusing to give up resources).
Additionally, each layer, from the PHY upwards is vulnera-
ble and it is clear that intrusion detection and security are
complex processes and cannot simply focus on one aspect
but, rather, must examine the whole process from transmis-
sion to reception, and everything in between.
FUTURE DIRECTIONS
Security and intrusion detection, both intentional and unin-
tentional, is integral for the future of successful WSN
deployments, especially in critical applications, like aero-
space, space-based WSNs, IoT, and using nanosatellites as
relay nodes. Security and IDSs cannot simply focus on par-
ticular attack strategies, they must also consider coexistence
issues as intrusions and need to recognize that hostile noisy
environments exist. Due to the flexible topology, open inter-
face and power limitations of these WSNs, this is a complex
challenge and needs to be solved to allow WSNs to be used
in safety critical applications and to safely exploit COTS
devices and standardized protocols. Based on the aforemen-
tioned pillars of security (vulnerabilities, requirements,
attacks, and defenses) and attack discussion, future work lies
in security development in terms of intrusion detection, both
intentional and unintentional, and mitigation. Attack effects
on WSNs and the associated signals and analysis of why
each specific security technique is used will be beneficial.
Additionally, the data from the PHY layer has potential to be
investigated as the radio architectures are usually very simi-
lar between wireless standards and so, by concentrating on
the PHY symbol stream and related measurements, the pos-
sibility of designing a transferable solution exists. This future
work entails both a reactive and detection approach, which
has potential to be environment specific. As the wireless
channel is a nonlinear phenomenon, an approach which can
model nonlinearities and adapt to new models is recom-
mended. From this perspective, a feature/featureless-based
machine learning algorithm focused on received samples in
Figure 6.
DPX visualization of the ISM RF Spectrum during the benchtop experiments. (a) DPX image showing the ZigBee signal at 2475 MHz.
(b) DPX image showing coexistence of ZigBee with 802.11 WiFi. (c) DPX image showing coexistence of ZigBee with 802.11 WiFi and
Bluetooth. (d) DPX image showing the spectral environment when ZigBee packets were lost.
Interference and Intrusion in Wireless Sensor Networks
14 IEEE AE SYSTEMS MAGAZINE FEBRUARY 2020
Authorized licensed use limited to: James Cook University of Northern Queensland. Downloaded on April 23,2020 at 19:46:02 UTC from IEEE Xplore. Restrictions apply.
12. the PHY is seen as an appropriate continuation from this arti-
cle. The focus lies in the development of a detection strategy,
which can distinguish between good operating and interfer-
ence intensive channels, while classifying the cause. A
machine learning approach seems applicable due to previous
work in nonlinear time series [39].
CONCLUSION
This article discussed interference and intrusions in WSNs in
terms of the four pillars of security; vulnerabilities, require-
ments, attacks, and defenses. An extensive overview of both
WSN security issues and WSN attacks were provided and
two main types of adversaries were defined; the outlaw, who
breaks the spectrum laws, and the noncompliant operator,
who adheres to laws but does not follow protocol rules. By
utilizing ZigBee, certain attacks were simulated, using Mat-
lab, and it was shown that matched protocol interference was
more of a threat than conventional CW jamming and, also,
harder to detect. This implies that traditional interference
detection schemes might be inadequate, as intruder signals
can be indistinguishable from legitimate ones. A real-time
analysis of coexisting signals causing interference and DoS
expanded this point and highlighted the two main types of
adversaries. Therefore, the work in this article implies that
WSN can be vulnerable to interference and/or intrusions, but
techniques can be used to add resilience and detectability.
To conclude, this article highlighted that if WSNs are to
become integrated into modern society and to be used fre-
quently in critical applications, like the IoT and aerospace,
enhancements to both security and the detection of inten-
tional and unintentional intrusions is necessary. Detection
strategies need to advance and look at aspects outside the
norm, for example, received raw bits, while maintaining the
optimization of device resources. Future designs should
encapsulate security at the beginning of the design process
and incorporate an IDS and utilize all layers from the PHY
upwards. The IDS should be able to characterize the intru-
sion and be able to distinguish between intentional and unin-
tentional intrusions.
ACKNOWLEDGMENTS
This work was supported in part by the Irish Research
Council (IRC) and in part by United Technologies
Research Center Ireland (UTRC-I) under the postgraduate
Enterprise Partnership Scheme 2016, award number
EPSPG/2016/66.
REFERENCES
[1] T. Vladimirova, C. P. Bridges, J. R. Paul, S. A. Malik, and M.
N. Sweeting, “Space-based wireless sensor networks: Design
issues,” in Proc. IEEE Aerosp. Conf., 2010, pp. 1–14.
[2] C. P. Kruger and G. P. Hancke, “Implementing the Inter-
net of Things vision in industrial wireless sensor
networks,” in Proc. 12th IEEE Int. Conf. Ind. Informat.,
2014, pp. 627–632.
[3] P. Park, S. C. Ergen, C. Fischione, C. Lu, and
K. H. Johansson, “Wireless network design for control
systems: A survey,” IEEE Commun. Surv. Tut., vol. 20,
no. 2, pp. 978–1013, Apr.–Jun. 2018.
[4] H. J. Beesterm€
oller et al., “Wireless-sensor networks in
space technology demonstration on ISS,” in Proc. Dresd-
ner Sensor-Symp., 2015, pp. 99–102.
[5] S. Li, B. Chen, and L. Yu, “A modified 802.11 protocol
applicated in space wireless local area network,” in Proc.
Int. Conf. Comput. Des. Appl., 2010, vol. 2, pp. 585–588.
[6] N. Celandroni, E. Ferro, A. Gotta, G. Oligeri, C. Roseti,
and M. Luglio, “A survey of architectures and scenarios in
satellite-based WSN,” Int. J. Satell. Commun. Netw.,
vol. 31, pp. 1–38, 2012.
[7] A. Addaim, A. Kherras, and Z. Guennoun, “Design of WSN
with relay nodes connected directly with a LEO nano-
satellite,” Int. J. Comput. Commun. Eng., vol. 3, no. 5,
pp. 310–316, 2014.
[8] R. K. Yedavalli and R. K. Belapurkar, “Application of
wireless sensor networks to aircraft control and health
management systems,” J. Control Theory Appl., vol. 9,
no. 1, pp. 28–33, 2011.
[9] G. D. O’Mahony, P. J. Harris, and C. C. Murphy,
“Investigating the prevalent security techniques in wireless
sensor network protocols,” in Proc. 30th IEEE Irish
Signals Syst. Conf., 2019, pp. 1–6.
[10] T. Bowler, “The low-cost mini satellites bringing mobile
to the world,” 2018.
[11] M. Marszalek, M. Rummelhagen, and F. Schramm,
“Potentials and limitations of IEEE 802.11 for satellite
swarms,” in Proc. IEEE Aerosp. Conf., 2014, pp. 1–9.
[12] A. D. Wood and J. A. Stankovic, “Denial of service in
sensor networks,” IEEE Comput. Mag., vol. 35, no. 10,
pp. 54–62, Oct. 2002.
[13] A. Tyagi, J. Kushwah, and M. Bhalla, “Threats to security
of wireless sensor networks,” in Proc. 7th Int. Conf. Cloud
Comput., Data Sci. Eng., 2017, pp. 402–405.
[14] Y. Zhou, Y. Fang, and Y. Zhang, “Securing wireless sensor
networks: A survey,” IEEE Commun. Surv., vol. 10, no. 3,
pp. 6–28, Jul.–Sep. 2008.
[15] I. Tomi and J. A. Mccann, “A survey of potential security
issues in existing wireless sensor network protocols,” IEEE
Internet Things J., vol. 4, no. 6, pp. 1910–1923, Dec. 2017.
[16] S. Shanthi and E. G. Rajan, “Comprehensive analysis of
security attacks and intrusion detection system in wireless
sensor networks,” in Proc. IEEE 2nd Int. Conf. Next
Gener. Comput. Technol., 2016, pp. 426–431.
[17] A. Mpitziopoulos, D. Gavalas, C. Konstantopoulos, and
G. Pantziou, “A survey on jamming attacks and counter-
measures in WSNs,” IEEE Commun. Surv. Tut., vol. 11,
no. 4, pp. 42–56, Oct.–Dec. 2009.
O’Mahony et al.
FEBRUARY 2020 IEEE AE SYSTEMS MAGAZINE 15
Authorized licensed use limited to: James Cook University of Northern Queensland. Downloaded on April 23,2020 at 19:46:02 UTC from IEEE Xplore. Restrictions apply.
13. [18] M. Li, I. Koutsopoulos, and R. Poovendran, “Optimal
jamming attacks and network defense policies in wireless
sensor networks,” in Proc. 26th IEEE Int. Conf. Comput.
Commun., 2007, pp. 1307–1315.
[19] M. Wilhelm, I. Martinovic, J. B. Schmitt, and V. Lenders,
“Short paper: Reactive jamming in wireless networks—
How realistic is the threat?,” in Proc. 4th ACM Conf.
Wireless Netw. Secur., Jun. 2011, pp. 47–52.
[20] D. Liu, J. Raymer, and A. Fox, “Efficient and timely jam-
ming detection in wireless sensor networks,” in Proc.
IEEE 9th Int. Conf. Mobile Ad-Hoc Sensor Syst., 2012,
pp. 335–343.
[21] Z. Yu and J. J. P. Tsai, “A framework of machine learning
based intrusion detection for wireless sensor networks,” in
Proc. IEEE Int. Conf. Sensor Netw., Ubiquitous, Trustwor-
thy Comput., 2008, pp. 272–279.
[22] O. Can and O. K. Sahingoz, “A Survey of intrusion detec-
tion systems in wireless sensor networks,” in Proc. 6th Int.
Conf. Model., Simul. Appl. Optim., 2015, pp. 1–6.
[23] A. Abduvaliyev, A.-S. K. Pathan, J. Zhou, R. Roman, and
L. W.-C. Wong, “On the vital areas of intrusion detection
systems in wireless sensor networks,” IEEE Commun.
Surv. Tut., vol. 15, no. 3, pp. 1223–1237, Jul.–Sep. 2013.
[24] G. D. O’Mahony, S. O’Mahony, J. T. Curran, and
C. C. Murphy, “Developing a low-cost platform for GNSS
interference detection,” in Proc. Eur. Navig. Conf., 2015,
pp. 1–8.
[25] O. Pu~
nal, I. Aktas, C.-J. Schnelke, G. Abidin, K. Wehrle,
and J. Gross, “Machine learning-based jamming detection
for IEEE 802.11: Design and experimental evaluation,” in
Proc. IEEE 15th Int. Symp. World Wireless, Mobile Multi-
media Netw., 2014, pp. 1–10.
[26] A. Sikora and V. F. Groza, “Coexistence of IEEE 802.15.4
with other systems in the 2.4 GHz-ISM-band,” in Proc.
IEEE Instrum. Meas. Technol. Conf., 2005, pp. 1786–1791.
[27] B. Stelte and G. D. Rodosek, “Thwarting attacks on Zig-
Bee—Removal of the KillerBee stinger,” in Proc. 9th Int.
Conf. Netw. Service Manage., 2013, pp. 219–226.
[28] ZigBee Alliance, “ZigBee specification,” ZigBee docu-
ment 053474r20, 2012.
[29] G. D. O Mahony, P. J. Harris, and C. C. Murphy,
“Analyzing the vulnerability of wireless sensor networks
to a malicious matched protocol attack,” in Proc. 52nd
IEEE Int. Carnahan Conf. Secur. Technol., 2018, pp. 1–5.
[30] A. D. Wood, J. A. Stankovic, and S. H. Son, “JAM: A
jammed-area mapping service for sensor networks,” in
Proc. 24th IEEE Real-Time Syst. Symp., 2003, pp. 286–297.
[31] T. Hamza, G. Kaddoum, A. Meddeb, and G. Matar, “A
survey on intelligent MAC layer jamming attacks and
countermeasures in WSNs,” in Proc. IEEE 84th Veh.
Technol. Conf., 2016, pp. 1–5.
[32] N. Ahmed, S. S. Kanhere, and S. Jha, “The holes problem in
wireless sensor networks: A survey,” ACM SIGMOBILE
Mobile Comput. Commun. Rev., vol. 9, no. 2, pp. 4–18,
2005.
[33] J. P. Anderson, “Computer security threat monitoring
and surveillance,” James P Anderson Company, Fort
Washington, PA, USA, 1980.
[34] I. S. Kocher, C.-O. Chow, H. Ishii, and T. A. Zia, “Threat
models and security issues in wireless sensor networks,” Int.
J. Comput. Theory Eng., vol. 5, no. 5, pp. 830–835, 2013.
[35] M. A. Mahmood, W. K. Seah, and I. Welch, “Reliability
in wireless sensor networks: A survey and challenges
ahead,” Comput. Netw., vol. 79, pp. 166–187, 2015.
[36] S. Dehnie, V. Chakravarthy, Z. Wu, C. Ghosh, and H. Li,
“Spectrum coexistence issues: Challenges and research
directions,” in Proc. IEEE Mil. Commun. Conf., 2013,
pp. 1681–1689.
[37] A. Tayebi, S. Berber, and A. Swain, “Wireless sensor net-
work attacks: An overview and critical analysis,” in Proc.
7th Int. Conf. Sens. Technol., 2013, pp. 97–102.
[38] A. S. Rawat, P. Anand, H. Chen, and P. K. Varshney,
“Collaborative spectrum sensing in the presence of byzan-
tine attacks in cognitive radio networks,” IEEE Trans.
Signal Process., vol. 59, no. 2, pp. 774–786, Feb. 2011.
[39] M. I. Alhajri, N. T. Ali, and R. M. Shubair, “Classification
of indoor environments for IoT applications: A machine
learning approach,” IEEE Antennas Wireless Propag.
Lett., vol. 17, no. 12, pp. 2164–2168, Dec. 2018.
Interference and Intrusion in Wireless Sensor Networks
16 IEEE AE SYSTEMS MAGAZINE FEBRUARY 2020
Authorized licensed use limited to: James Cook University of Northern Queensland. Downloaded on April 23,2020 at 19:46:02 UTC from IEEE Xplore. Restrictions apply.