The wireless sensor node is a tiny device that is used to capture environment information.
Sensor devices are used to capture temperature and pressure details from the environment. The
sensor devices are used in hospitals, home and production plants. The main components of a sensor
node are microcontroller, transceiver, external memory and power source. A wireless sensor network
(WSN) is a wireless network consisting of spatially distributed autonomous devices. Sensors are
used to cooperatively monitor physical or environmental conditions. Sensor network is equipped
with a radio transceiver or other wireless communications device. The sensor networks are deployed
with consideration of sensing and transmission coverage factors.
Sensor network security protocols provide confidentiality for the messages. Object location and data
sink information are the sensitive elements in the sensor network. Two techniques are used to
provide location privacy to monitored objects. They are Source-location privacy and Sink-location
privacy. Periodic collection and Source simulation models are used in Source-location privacy
technique. Sink simulation and backbone flooding models are used in Sink-location privacy
technique. Communication cost and latency factors are consider in the privacy protection model.
Source and destination location details are protected in the privacy model.
The proposed system integrates the location privacy and data security process for the wireless sensor
network. Region based query model is used to improve location privacy. Confidentiality and
integrity techniques are used for the security process. Rivest Cipher (RC4) algorithm and Secure
Hashing Algorithms (SHA) are used for the data security.
Wireless sensor networks are nowadays widely popular and has become an integral part in the military
applications for human monitoring, thermal detection etc. Security of Wireless sensor network (WSN)
becomes a very important issue with the rapid development of WSN that is vulnerable to a wide range of
attacks such as sinkhole attacks due to deployment in the hostile environment and having limited resources.
Intrusion detection system is one of the major and efficient defensive methods against attacks in WSN. One
such detection technique is black listing technology. But using only Black listing technology is not suitable
for a mobile intruder since it was designed considering only a static intruding node in a WSN. So it is
necessary to build an energy efficient Intrusion detection system for sinkhole attack by a mobile intruder in
WSN. We are intended to design an energy efficient system for detection of sinkhole and elimination of a
mobile intruder from WSN nodes using a technology called greylisting. This technology uses pre alarm
packets to warn the neighboring nodes about the intruder and the energy consumed by the pre alarm
packets for making an alarm is much lesser than that of the packets used in black listing technology. Thus
this method will serve as the solution for the dilemma in providing the security for WSN in sinkhole attack.
An enhancing security for mobile sinks by providing location privacy in wsneSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Wireless sensor networks are nowadays widely popular and has become an integral part in the military
applications for human monitoring, thermal detection etc. Security of Wireless sensor network (WSN)
becomes a very important issue with the rapid development of WSN that is vulnerable to a wide range of
attacks such as sinkhole attacks due to deployment in the hostile environment and having limited resources.
Intrusion detection system is one of the major and efficient defensive methods against attacks in WSN. One
such detection technique is black listing technology. But using only Black listing technology is not suitable
for a mobile intruder since it was designed considering only a static intruding node in a WSN. So it is
necessary to build an energy efficient Intrusion detection system for sinkhole attack by a mobile intruder in
WSN. We are intended to design an energy efficient system for detection of sinkhole and elimination of a
mobile intruder from WSN nodes using a technology called greylisting. This technology uses pre alarm
packets to warn the neighboring nodes about the intruder and the energy consumed by the pre alarm
packets for making an alarm is much lesser than that of the packets used in black listing technology. Thus
this method will serve as the solution for the dilemma in providing the security for WSN in sinkhole attack.
An enhancing security for mobile sinks by providing location privacy in wsneSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Securing the Data Communication between the Neighboring Sensor Nodes using Bi...IJMTST Journal
Privacy of data is one of the most important concept in wireless sensor networks. Wireless sensor networks are used in many areas likewise in tracking and monitoring of some events. Each sensor node has one private key and an assigned id. We are providing data confidentiality between the sensor nodes in wireless sensor network using bilinear pairing (diffie-hellman algorithm). Sharing of data between those neighbouring nodes is also secured with the concept of shared secret key(symmetric key cryptography). Content privacy and context privacy can be obtained and the threats regarding to it can be overcomed. Data is encrypted between the nodes using those shared secret keys. We are providing security for the data between the neighbouring nodes in wireless sensor networks.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
A Survey on Threats and Security schemes in Wireless Sensor NetworksIJERA Editor
It is difficult to achieve and become particularly acute in wireless sensor networks due to the limitation in network capability, computational power and memory which do not allow for implementation of complex security mechanism because security being vital to the acceptance and use of wireless sensor networks for many applications. In this paper we have explored general security threats in wireless sensor networks and analyzed them. This paper is an attempt to survey and analyze the threats to the wireless sensor networks and focus on the type of attacks and achieve secure communication in wireless sensor networks.
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.
Securing WSN communication using Enhanced Adaptive Acknowledgement ProtocolIJMTST Journal
Wireless Sensor Networking is one of the most important technologies that have different applications. The
security of wireless sensor networks is a big concern. Hence for secure communication it is important to
detect and prevent the attacks in network. Major focus is given on security and on detection and prevention of
attacks. Adversary can create gray-hole attack and black-hole attack simultaneously. There are many
methods which do not provide proper method to defend against these kinds of attacks. The Ad-hoc On
Demand Distance Vector (AODV) scheme is used for detecting Gray-Hole attack and Enhanced Adaptive
Acknowledgment (EAACK) mechanism is used for detecting black-hole attack in network. But only by
detecting and preventing the attacks, it does not provide the better security to wireless network. Therefore, to
secure network a hybrid mechanism is deployed in wireless sensor network. Security algorithm for wireless
sensor networks such as CAWS and Modern Encryption Standard (MES-1) is used for secure communication.
The CAWS and Modern Encryption Standard (MES-1) is an advanced cryptography method which is used for
encryption and decryption process to provide special security.
A Combined Approach for Worm-Hole and Black-Hole Attack Detection in MANETIJERA Editor
Mobile ad hoc network is a kind of wireless network, in this network all nodes are connected through the wireless links and perform cooperative communication.Due to limited radio range of these devices any time can leave or join the network. Therefore the routing techniques are responsible for the network organization and communication flow. Due to this the performance of MANET is low as compared with the traditional wired communication networks. In addition of that network is suffers from the probability of attacks. Thus in this paper MANET routing strategy and their attacks are investigated and learned. In addition of that in order to secure the communication recent approaches of security in MANET also investigated. Finally a new algorithm for prevention of malicious attack in MANET is suggested. Additionally the based on the concluded facts, future extension of the proposed work is also suggested.
Real-Time Location Systems Security using Distance BoundingIJRES Journal
Traditional Authentication protocols, that run between a prover and a verifier, enable the verifier to decide whether a prover is fraud or authenticate by using technique like password, smart card, but location based attacks cannot be prevent using these techniques. Networks like Real Time Location System (RTLS), Wireless, Mobile Adhoc Network (MANet) suffer location based attacks. Location based attacks categories in distance fraud, mafia fraud, and terrorist fraud. Distance bounding technique is use for secure neighbor detection in RTLS that cryptographically measure an upper bound for the physical distance between two network devices. In this paper propose architecture for physical proximity or location verification of devices, for all types of attacks and prevention technique to these location based attacks
Overview on security and privacy issues in wireless sensor networks-2014Tarek Gaber
Lecture Outlines
Why Security is Important for WSN
WSNs have many applications e.g.:
military, homeland security
assessing disaster zones
Others.
This means that such sensor networks have mission-critical tasks.
Security is crucial for such WSNs deployed in these hostile environments.
Why Security is Important for WSN
Moreover, wireless communication employed by WSN facilitates
eavesdropping and
packet injection by an adversary.
These mentioned factors require security for WSN during the design stage to ensure operation safety, secrecy of sensitive data, and privacy for people in sensor environments.
Algorithms to achieve security services
Symmetric Encryption
Asymmetric Encryption
Hash Function/Algorithm
Digital Signature
Why Security is Complex in WSN
Because of WSNs Characteristics:
Anti-jamming and physical temper proofing are impossible
greater design complexity and energy consumption
Denial-of-service (DoS) attack is difficult
Sensor node constraints
Sensor nodes are susceptible to physical capture
Deploying in hostile environment.
eavesdropping and injecting malicious message are easy
Using wireless communication
Why Security is Complex in WSN
Because of WSNs Characteristics:
maximization of security level is challenging
Resource consumption
asymmetric cryptography is often too expensive
Node constraints
centralized security solutions are big issue
no central control and constraints, e.g. small memory capacity.
Cost Issues
Overall cost of WSN should be as low as possible.
Typical Attacks to WSN
Physical Attacks
Environmental
Permanently destroy the node, e.g., crashing or stealing a node.
Attacks at the Physical Layer
Jamming: transmission of a radio signal to interfere with WSN radio frequencies.
Constant jamming: No message are able to be sent or received.
Intermittent jamming: Nodes are able to exchange messages periodically
Jamming Attack Countermeasure
Physical Attacks
Node Capture Attacks
routing functionalities
Countermeasure
tamper-proof features
Expensive solution
Self-Protection
disable device when attack detected
Attacks on Routing
Sinkhole attack
attacker tries to attract the traffic from a particular region through it
Solution:
Watchdog Nodes can start to trace the source of false routing information
Attacks on Routing
Sybil attack (Identity Spoofing)
attacker claims to have multiple identities or locations
provide wrong information for routing to launch false routing attacks
Solutions:
Misbehavior Detection.
Identity Protection
Privacy Attacks
Attempts to obtain sensitive information collected and communicated in WSNs
Eavesdropping
made easy by broadcast nature of wireless networks
Traffic analysis
used to identify sensor nodes of interest (data of interest),
WSN Privacy Issues Cont.
WSN Privacy Issues Attack
Trust and reputation in WSN
WSN Traditional Security Techniques
Cryptographic primitive
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.
In the computer security context, a hacker is someone who seeks and exploits weaknesses in a computer system or computer network. Hackers may be motivated by a multitude of reasons, such as profit, protest, challenge, enjoyment,[1] or to evaluate those weaknesses to assist in removing them. The subculture that has evolved around hackers is often referred to as the computer underground and is now a known community. While other uses of the word hacker exist that are related to computer security, such as referring to someone with an advanced understanding of computers and computer networks, they are rarely used in mainstream context. They are subject to the longstanding hacker definition controversy about the term's true meaning. In this controversy, the term hacker is reclaimed by computer programmers who argue that someone who breaks into computers, whether computer criminal (black hats) or computer security expert (white hats), is more appropriately called a cracker instead. Some white hat hackers, who claim that they also deserve the title hacker, and that only black hats should be called "crackers"
Securing the Data Communication between the Neighboring Sensor Nodes using Bi...IJMTST Journal
Privacy of data is one of the most important concept in wireless sensor networks. Wireless sensor networks are used in many areas likewise in tracking and monitoring of some events. Each sensor node has one private key and an assigned id. We are providing data confidentiality between the sensor nodes in wireless sensor network using bilinear pairing (diffie-hellman algorithm). Sharing of data between those neighbouring nodes is also secured with the concept of shared secret key(symmetric key cryptography). Content privacy and context privacy can be obtained and the threats regarding to it can be overcomed. Data is encrypted between the nodes using those shared secret keys. We are providing security for the data between the neighbouring nodes in wireless sensor networks.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
A Survey on Threats and Security schemes in Wireless Sensor NetworksIJERA Editor
It is difficult to achieve and become particularly acute in wireless sensor networks due to the limitation in network capability, computational power and memory which do not allow for implementation of complex security mechanism because security being vital to the acceptance and use of wireless sensor networks for many applications. In this paper we have explored general security threats in wireless sensor networks and analyzed them. This paper is an attempt to survey and analyze the threats to the wireless sensor networks and focus on the type of attacks and achieve secure communication in wireless sensor networks.
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.
Securing WSN communication using Enhanced Adaptive Acknowledgement ProtocolIJMTST Journal
Wireless Sensor Networking is one of the most important technologies that have different applications. The
security of wireless sensor networks is a big concern. Hence for secure communication it is important to
detect and prevent the attacks in network. Major focus is given on security and on detection and prevention of
attacks. Adversary can create gray-hole attack and black-hole attack simultaneously. There are many
methods which do not provide proper method to defend against these kinds of attacks. The Ad-hoc On
Demand Distance Vector (AODV) scheme is used for detecting Gray-Hole attack and Enhanced Adaptive
Acknowledgment (EAACK) mechanism is used for detecting black-hole attack in network. But only by
detecting and preventing the attacks, it does not provide the better security to wireless network. Therefore, to
secure network a hybrid mechanism is deployed in wireless sensor network. Security algorithm for wireless
sensor networks such as CAWS and Modern Encryption Standard (MES-1) is used for secure communication.
The CAWS and Modern Encryption Standard (MES-1) is an advanced cryptography method which is used for
encryption and decryption process to provide special security.
A Combined Approach for Worm-Hole and Black-Hole Attack Detection in MANETIJERA Editor
Mobile ad hoc network is a kind of wireless network, in this network all nodes are connected through the wireless links and perform cooperative communication.Due to limited radio range of these devices any time can leave or join the network. Therefore the routing techniques are responsible for the network organization and communication flow. Due to this the performance of MANET is low as compared with the traditional wired communication networks. In addition of that network is suffers from the probability of attacks. Thus in this paper MANET routing strategy and their attacks are investigated and learned. In addition of that in order to secure the communication recent approaches of security in MANET also investigated. Finally a new algorithm for prevention of malicious attack in MANET is suggested. Additionally the based on the concluded facts, future extension of the proposed work is also suggested.
Real-Time Location Systems Security using Distance BoundingIJRES Journal
Traditional Authentication protocols, that run between a prover and a verifier, enable the verifier to decide whether a prover is fraud or authenticate by using technique like password, smart card, but location based attacks cannot be prevent using these techniques. Networks like Real Time Location System (RTLS), Wireless, Mobile Adhoc Network (MANet) suffer location based attacks. Location based attacks categories in distance fraud, mafia fraud, and terrorist fraud. Distance bounding technique is use for secure neighbor detection in RTLS that cryptographically measure an upper bound for the physical distance between two network devices. In this paper propose architecture for physical proximity or location verification of devices, for all types of attacks and prevention technique to these location based attacks
Overview on security and privacy issues in wireless sensor networks-2014Tarek Gaber
Lecture Outlines
Why Security is Important for WSN
WSNs have many applications e.g.:
military, homeland security
assessing disaster zones
Others.
This means that such sensor networks have mission-critical tasks.
Security is crucial for such WSNs deployed in these hostile environments.
Why Security is Important for WSN
Moreover, wireless communication employed by WSN facilitates
eavesdropping and
packet injection by an adversary.
These mentioned factors require security for WSN during the design stage to ensure operation safety, secrecy of sensitive data, and privacy for people in sensor environments.
Algorithms to achieve security services
Symmetric Encryption
Asymmetric Encryption
Hash Function/Algorithm
Digital Signature
Why Security is Complex in WSN
Because of WSNs Characteristics:
Anti-jamming and physical temper proofing are impossible
greater design complexity and energy consumption
Denial-of-service (DoS) attack is difficult
Sensor node constraints
Sensor nodes are susceptible to physical capture
Deploying in hostile environment.
eavesdropping and injecting malicious message are easy
Using wireless communication
Why Security is Complex in WSN
Because of WSNs Characteristics:
maximization of security level is challenging
Resource consumption
asymmetric cryptography is often too expensive
Node constraints
centralized security solutions are big issue
no central control and constraints, e.g. small memory capacity.
Cost Issues
Overall cost of WSN should be as low as possible.
Typical Attacks to WSN
Physical Attacks
Environmental
Permanently destroy the node, e.g., crashing or stealing a node.
Attacks at the Physical Layer
Jamming: transmission of a radio signal to interfere with WSN radio frequencies.
Constant jamming: No message are able to be sent or received.
Intermittent jamming: Nodes are able to exchange messages periodically
Jamming Attack Countermeasure
Physical Attacks
Node Capture Attacks
routing functionalities
Countermeasure
tamper-proof features
Expensive solution
Self-Protection
disable device when attack detected
Attacks on Routing
Sinkhole attack
attacker tries to attract the traffic from a particular region through it
Solution:
Watchdog Nodes can start to trace the source of false routing information
Attacks on Routing
Sybil attack (Identity Spoofing)
attacker claims to have multiple identities or locations
provide wrong information for routing to launch false routing attacks
Solutions:
Misbehavior Detection.
Identity Protection
Privacy Attacks
Attempts to obtain sensitive information collected and communicated in WSNs
Eavesdropping
made easy by broadcast nature of wireless networks
Traffic analysis
used to identify sensor nodes of interest (data of interest),
WSN Privacy Issues Cont.
WSN Privacy Issues Attack
Trust and reputation in WSN
WSN Traditional Security Techniques
Cryptographic primitive
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.
In the computer security context, a hacker is someone who seeks and exploits weaknesses in a computer system or computer network. Hackers may be motivated by a multitude of reasons, such as profit, protest, challenge, enjoyment,[1] or to evaluate those weaknesses to assist in removing them. The subculture that has evolved around hackers is often referred to as the computer underground and is now a known community. While other uses of the word hacker exist that are related to computer security, such as referring to someone with an advanced understanding of computers and computer networks, they are rarely used in mainstream context. They are subject to the longstanding hacker definition controversy about the term's true meaning. In this controversy, the term hacker is reclaimed by computer programmers who argue that someone who breaks into computers, whether computer criminal (black hats) or computer security expert (white hats), is more appropriately called a cracker instead. Some white hat hackers, who claim that they also deserve the title hacker, and that only black hats should be called "crackers"
Learn the latest on protecting your system from spyware, spam, and unauthorized access. Discover what you need to do to ensure the integrity of your company’s valuable data.
Robust encryption algorithm based sht in wireless sensor networksijdpsjournal
In bound applications, the locations
of events reportable by a device network have to be compelled to stay
anonymous. That is, unauthorized observers should be unable to notice the origin of such events by
analyzing the network traffic. I analyze 2 forms of downsides: Communication overhead a
nd machine load
problem. During this paper, I gift a brand new framework for modeling, analyzing, and evaluating
obscurity in device networks. The novelty of the proposed framework is twofold: initial, it introduc
es the
notion of “interval indistinguishabi
lity” and provides a quantitative live to model obscurity in wireless
device networks; second, it maps supply obscurity to the applied mathematics downside I showed that
the
present approaches for coming up with statistically anonymous systems introduce co
rrelation in real
intervals whereas faux area unit unrelated. I show however mapping supply obscurity to consecutive
hypothesis testing with nuisance Parameters ends up in changing the matter of exposing non
-
public supply
data into checking out associate d
egree applicable knowledge transformation that removes or minimize the
impact of the nuisance data victimization sturdy cryptography algorithmic rule. By doing therefore,
I
remodel the matter of analyzing real valued sample points to binary codes, that ope
ns the door for
committal to writing theory to be incorporated into the study of anonymous networks. In existing wor
k,
unable to notice unauthorized observer in network traffic. However our work in the main supported
enhances their supply obscurity against
correlation check. the most goal of supply location privacy is to
cover the existence of real events.
A Novel Approach to Detect & Prevent Wormhole Attack over MANET & Sensor n/w ...IOSR Journals
Abstract: In Mobile Ad hoc Network (MANET) mobile node is responsible for route establishment using
wireless link where each node may behave like both as a host and router. MANET encounters number of
security threats because of its open entrusted environment, with little security arrangement, security over
MANET can be enhance up to some satisfactory level because of its inherent characteristics. Among some of
the prominent security threats wormhole attack is considered to be a very serious security threat over MANET.
In wormhole two selfish node which is geographically very far away to each other makes tunnel between each
other to hide their actual location and give the illusion that they are true neighbours and attract other nodes to
make conversation through the wormhole tunnel. Many researchers focused on detecting wormhole attack and
its prevention mechanism. It seems that in the previous technique there is a need to improve their results in the
brink of false negative rate, routing overhead etc. The present paper has proposed the hybrid model in order to
detect and prevent the wormhole attack. This approach has been work with neighbour node and hop count
method.
Keywords: Mobile Ad hoc Network, Selfish node, Malicious node, AODV
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
A simple and effective scheme to find malicious node in wireless sensor networkeSAT Journals
Abstract Wireless Sensor Network consists of hundreds or thousands of sensor nodes. Impractical to maintain topology and protect each sensor nodes from attack. Wireless Sensor Network is often deployed in an unattended and hostile environment to perform the monitoring and data collection tasks. When sensor nodes are deployed in such an environment, sensor network lacks in physical protection and is subject to insertion of malicious node. After that an adversary may launch various attacks to disrupt the in-network communication through malicious node. In such attacks malicious node behave like normal nodes by selectively drop packets for make it harder to detect their malicious nature. Many schemes have been proposed to detect malicious nodes, but very few can identify attacks. But those proposals are send redundant packets, consume more energy and storage to identify malicious nodes. A simple and effective scheme proposed as Stop Transmit and Listen (STL) to find the malicious node. Each node is having the built-in time limit to stop their transmission. For every few seconds every node stops their transmission and listens for malicious behavior. Malicious nodes are not aware of non-transmitting time. If malicious node sends or forwards the data in non-transmitting time, malicious node is caught by their neighbor nodes in the network. Key Words: IDS, Secure Routing Protocol, Stop Transmit and Listen
A simple and effective scheme to find malicious node in wireless sensor networkeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Secure and Reliable Data Routing in Wireless Sensor Networkdbpublications
Wireless Sensor Networks (WSNs) are materializing as one of the dominant technologies of the future because of their large range of applications in military and civilian fields. Because of their operating behavior, they are often neglected and thus vulnerable to various types of attacks. For instance, an attacker could catch sensor nodes, getting all the information saved therein-sensor nodes are generally considered to not be temper-proof. Hence, an attacker may clone cached sensor nodes and use them in the network to conduct a variety of mischievous activities. As the decisions taken by a sensor network rely on the information gathered by the sensor nodes, if an adversary inhibits the necessary or confidential data from being forwarded to the BS/ target, this will cause the whole breakdown of the network or outcomes in the wrong judgment being made, possibly causing deliberate loss. There are many types of attacks such as compromised node, denial of service attack, black hole attack, etc. Hence there is a necessity to find all such attacks in WSN, and to safely route our sensitive information to the target. This paper represents the survey of some types of attacks and there detection techniques. Also the survey includes different techniques for secure and reliable data collection in Wireless Sensor Networks.
AN IMPROVED WATCHDOG TECHNIQUE BASED ON POWER-AWARE HIERARCHICAL DESIGN FOR I...IJNSA Journal
Preserving security and confidentiality in wireless sensor networks (WSN) are crucial. Wireless sensor networks in comparison with wired networks are more substantially vulnerable to attacks and intrusions. In WSN, a third person can eavesdrop to the information or link to the network. So, preventing these intrusions by detecting them has become one of the most demanding challenges. This paper, proposes an
improved watchdog technique as an effective technique for detecting malicious nodes based on a power aware hierarchical model. This technique overcomes the common problems in the original Watchdog mechanism. The main purpose to present this model is reducing the power consumption as a key factor
for increasing the network's lifetime. For this reason, we simulated our model with Tiny-OS simulator and then, compared our results with non hierarchical model to ensure the improvement. The results indicate that, our proposed model is better in performance than the original models and it has increased the lifetime of the wireless sensor nodes by around 2611.492 seconds for a network with 100 sensors.
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.
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.
The wormhole attack in Wireless sensor networks (WSNs) decreases the network performance by dropping the No. of Packets. Many techniques have been proposed to so far reduce the impact of the wormhole attack by detecting and preventing it. But, related work indicates that no technique is perfect for every kind of circumstances of WSNs. Among the existing techniques, Watchdog technique has better performance in preventing the wormhole attack. It utilizes the local knowledge of the next hop node and eavesdrops it. If it gets that spending time of the Packet is more than the given threshold, then it characterizes that node as wormhole attacker. However, this method has several shortcomings that it does not track the link transmission errors, which may be because of congestion in WSNs and also it not offers high mobility for maximum No. of nodes, which eventually decreases the WSNs performance. In order to handle this issue, a new multipoint relay based Watchdog monitoring and prevention technique is proposed in this paper. The proposed technique utilizes the dynamic threshold value to detect the wormhole attacker node, and then clustering and the Watchdog based optimistic path is selected for communicating the Packets. Thus, it reduces the overall Packet dropping, which improves the performance of the WSNs.
Secure and Efficient Hierarchical Data Aggregation 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.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Maximizing network interruption in wirelessIJCNCJournal
With the colossal growth of wireless sensor networks (WSNs) in different applications starting from home
automation to military affairs, the pressure on ensuring security in such a network is paramount.
Considering the security challenges, it is really a hard-hitting effort to develop a secured WSN system.
Moreover, as the information technology is getting popular, the intruders are also planning new ideas to
break the system security, to harm the network and to make the system quality down with the target of
taking the control of the network to corrupt it or to get benefits from it anyway. The intruders corrupt the
system only when the security breaking cost (SBC) is lower compared with the benefits they attained or the
harm it can make to others. In this paper, the authors define the term “maximizing network interruption
problem” and propose a technique, called the grid point approximation algorithm, to estimate the SBC of a
multi-hop WSN so that it can be made tougher for an intruder to break the system security. It is assumed
that the intruder has the complete picture of the entire network. The technique is designed from the
intruder’s point of view for completely jamming all the sensor nodes in the network through placing
jammers or malicious nodes strategically and at the same time keeping the number of jammer nodes to
minimum or near minimum. To the best of the authors’ knowledge, there is no work proposed so far of the
same kind. Experimental results with the changes of the different network parameters show that the
proposed algorithm is able to provide excellent performances to achieve the targets.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
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Integrated Security and Attack Detection Scheme for Wireless Sensor Networks
1. Scientific Journal Impact Factor (SJIF): 1.711
International Journal of Modern Trends in Engineering
and Research
www.ijmter.com
@IJMTER-2014, All rights Reserved 372
e-ISSN: 2349-9745
p-ISSN: 2393-8161
Integrated Security and Attack Detection Scheme for
Wireless Sensor Networks
N. S. KAVITHA1
, P. SUGANTHI2
, Mr. R. Subramanian3
Assistant Professors, CSE,,
1,2
Erode Sengunthar Engineering College, Thudupathi, Palakarai, Tamil Nadu, India
Abstract- The wireless sensor node is a tiny device that is used to capture environment information.
Sensor devices are used to capture temperature and pressure details from the environment. The
sensor devices are used in hospitals, home and production plants. The main components of a sensor
node are microcontroller, transceiver, external memory and power source. A wireless sensor network
(WSN) is a wireless network consisting of spatially distributed autonomous devices. Sensors are
used to cooperatively monitor physical or environmental conditions. Sensor network is equipped
with a radio transceiver or other wireless communications device. The sensor networks are deployed
with consideration of sensing and transmission coverage factors.
Sensor network security protocols provide confidentiality for the messages. Object location and data
sink information are the sensitive elements in the sensor network. Two techniques are used to
provide location privacy to monitored objects. They are Source-location privacy and Sink-location
privacy. Periodic collection and Source simulation models are used in Source-location privacy
technique. Sink simulation and backbone flooding models are used in Sink-location privacy
technique. Communication cost and latency factors are consider in the privacy protection model.
Source and destination location details are protected in the privacy model.
The proposed system integrates the location privacy and data security process for the wireless sensor
network. Region based query model is used to improve location privacy. Confidentiality and
integrity techniques are used for the security process. Rivest Cipher (RC4) algorithm and Secure
Hashing Algorithms (SHA) are used for the data security.
I. INTRODUCTION
A Wireless Sensor Network (WSN) is a collection of spatially deployed wireless sensors by which to
monitor various changes of environmental conditions in a collaborative manner without relying on
any underlying infrastructure support. Recently, a number of research efforts have been made to
develop sensor hardware and network architectures in order to effectively deploy WSNs for a variety
of applications. Due to a wide diversity of WSN application requirements, however, a general-
purpose WSN design cannot fulfill the needs of all applications. Many network parameters such as
sensing range, transmission range, and node density have to be carefully considered at the network
design stage, according to specific applications. To achieve this, it is critical to capture the impacts of
network parameters on network performance with respect to application specifications.
Intrusion detection a WSN can be regarded as a monitoring system for detecting the intruder that is
invading the network domain. The intrusion detection application concerns how fast the intruder can
be detected by the WSN. If sensors are deployed with a high density so that the union of all sensing
ranges covers the entire network area, the intruder can be immediately detected once it approaches
the network area. However, such a high-density deployment policy increases the network investment
and may be even unaffordable for a large area. In fact, it is not necessary to deploy so many sensors
2. International Journal of Modern Trends in Engineering and Research (IJMTER)
Volume 02, Issue 01, [January - 2015] e-ISSN: 2349-9745, p-ISSN: 2393-8161
@IJMTER-2014, All rights Reserved 373
to cover the entire WSN area in many applications, since a network with small and scattered void
areas will also be able to detect a moving intruder within a certain intrusion distance. In this case, the
application can specify a required intrusion distance within which the intruder should be detected.
The intrusion distance is referred as D and defined as the distance between the point the intruder
enters the WSN, and the point the intruder is detected by the WSN system. This distance is of central
interest to a WSN used for intrusion detection.
In this system derived the expected intrusion distance and evaluate the detection probability in
different application scenarios. Given a maximal allowable intrusion distance Dmax = ε, we
theoretically capture the impact on the detection probability in terms of different network parameters,
including node density, sensing range, and transmission range. For example, given an expected
detection distance E(D), we can derive the node density with respect to sensors’ sensing range,
thereby knowing the total number of sensors required for WSN deployment.
In a WSN, there are two ways to detect an object: single-sensing detection and multiple-sensing
detection. In the single-sensing detection, the intruder can be successfully detected by a single
sensor. On the contrary, in the multiple-sensing detection, the intruder can only be detected by
multiple collaborating sensors. In some applications, the sensed information provided by a single
sensor might be inadequate for recognizing the intruder. It is because individual sensors can only
sense a portion of the intruder. For example, the location of an intruder can only be determined from
at least three sensors’ sensing data. In view of this, we analyze the intrusion detection problem under
two application scenarios: single-sensing detection and multiple-sensing detection.
II. RELATED WORKS
Location privacy has been an active area of research in recent years. In location-based services, a
user may want to retrieve location-based data without revealing her location. Techniques such as k-
anonymity [2] and private information retrieval [10] have been developed for this purpose. In
pervasive computing, users’ location privacy can be compromised by observing the wireless signals
from user devices [7]. Random delay and dummy traffic have been suggested to mitigate these
problems. Location privacy in sensor networks also falls under the general framework of location
privacy. The adversary monitors the wireless transmissions to infer locations of critical
infrastructure. There are some challenges unique to sensor networks. First, sensor nodes are usually
battery powered, which limits their functional lifetime. Second, a sensor network is often
significantly larger than the network in smart home or assisted living applications.
Source-location privacy: Prior work in protecting the location of monitored objects sought to
increase the safety period, i.e., the number of messages sent by the source before the object is located
by the attacker. The flooding technique has the source node send each packet through numerous
paths to a sink, making it difficult for an adversary to trace the source. Fake packet generation
creates fake sources whenever a sender notifies the sink that it has real data to send. The fake senders
are away from the real source and approximately at the same distance from the sink as the real
sender. Phantom single-path routing [4] achieves location privacy by making every packet walk
along a random path before being delivered to the sink. Cyclic entrapment creates looping paths at
various places in the network to fool the adversary into following these loops repeatedly and thereby
increase the safety period. However, all these techniques assume a local eavesdropper who is only
capable of eavesdropping on a small region. A global eavesdropper can easily defeat these schemes
by locating the first node initiating the communication with the base station.
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Recently, several techniques have been proposed to deal with global eavesdroppers. Yang et al.
propose to use proxies to shape the network traffic such that global eavesdroppers cannot infer the
locations of monitored objects [9]. Shao et al. propose to reduce the latency of real events without
reducing the location privacy under a global eavesdropper. This technique ensures that the adversary
cannot determine the real traffic from statistical analysis.
Sink-location privacy: Deng et al. described a technique to protect the locations of sinks from a
local eavesdropper by hashing the ID field in the packet header. In [8], it was shown that an
adversary can track sinks by carrying out time correlation and rate monitoring attacks. To mitigate
these two kinds of attacks, Deng et al. introduced a multiple-parent routing scheme, a controlled
random walk scheme, a random fake path scheme, and a hot spots scheme. Redundant hops and fake
packets are added to provide privacy when data are sent to the sink. These techniques all assume that
the adversary is a local eavesdropper. A global eavesdropper can easily defeat these schemes. For
example, the global eavesdropper only needs to identify the region exhibiting a high number of
transmissions to locate the sink. We, thus, focus on privacy-preserving techniques designed to defend
against a global eavesdropper.
III. DATA COMMUNICATION IN WSN
A wireless sensor network (WSN) typically consists of a large number of small, multifunctional, and
resource-constrained sensors that are self-organized as an ad hoc network to monitor the physical
world [1]. Sensor networks are often used in applications where it is difficult or infeasible to set up
wired networks. Examples include wildlife habitat monitoring, security and military surveillance,
and target tracking. Location privacy is, thus, very important, especially in hostile environments.
Failure to protect such information can completely subvert the intended purposes of sensor network
applications. Location privacy measures, thus, need to be developed to prevent the adversary from
determining the physical locations of source sensors and sinks. Due to the limited energy lifetime of
battery-powered sensor nodes, these methods have to be energy efficient. Since communication in
sensor networks is much more expensive than computation, we use communication cost to measure
the energy consumption of our protocols.
Providing location privacy in a sensor network is challenging. First, an adversary can easily intercept
network traffic due to the use of a broadcast medium for routing packets. He can use information like
packet transmission time and frequency to perform traffic analysis and infer the locations of
monitored objects and data sinks. Second, sensors usually have limited processing speed and energy
supplies. It is very expensive to apply traditional anonymous communication techniques for hiding
the communication between sensor nodes and sinks. We need to find alternative means to provide
location privacy that accounts for the resource limitations of sensor nodes. In this paper, we focus on
privacy-preserving communication methods in the presence of a global eavesdropper who has a
complete view of the network traffic. The contributions in this paper are twofold.
We point out that the assumption of a global eavesdropper who can monitor the entire
network traffic is often realistic for highly motivated adversaries. We then formalize the
location privacy issues under such an assumption and apply an analysis based on Steiner trees
to estimate the minimum communication cost required to achieve a given level of privacy.
We provide the first formal study of how to quantitatively measure location privacy in sensor
networks. We then apply the results of this study to evaluate our proposed techniques for
location privacy in sensor networks. These include two techniques that hide the locations of
monitored objects—periodic collection and source simulation—and two techniques that
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provide location privacy to data sinks—sink simulation and backbone flooding. Our analysis
and simulation studies show that these approaches are effective and efficient.
IV. PROBLEM STATEMENT
Sensor network security protocols provide confidentiality for the messages. Object location and data
sink information are the sensitive elements in the sensor network. Two techniques are used to
provide location privacy to monitored objects [15]. They are Source-location privacy and Sink-
location privacy. Periodic collection and Source simulation models are used in Source-location
privacy technique. Sink simulation and backbone flooding models are used in Sink-location privacy
technique. Communication cost and latency factors are consider in the privacy protection model.
Source and destination location details are protected in the privacy model. The following problems
are identified from the current security methods in WSN. Location dependent attacks are not
efficiently handled. Dynamic data update process is not managed. Communication overhead is high.
Data security is not provided.
V. PRIVACY EVALUATION MODEL
We describe a model for evaluating the location privacy of critical components in sensor networks.
In this model, the adversary deploys a snooping network to monitor the wireless transmission
activity in the target network. We consider a scenario in which an adversary can monitor all
transmissions of the sensors in the network. In practice, the adversary does not need to know exactly
where a packet is sent or the exact location of the sensor node that sends the packet. A rough
estimate of the location will be good enough for the attacker to conduct traffic analysis. However, we
assume the worst case scenario: for every observed packet, the adversary knows where it is sent or
which sensor node sends the packet. This indicates that each sensor i is an observation point, and a
tuple (i, t, e) is available to the adversary by observing each packet e send by node i at time t. We
assume that all transmissions are encrypted, and hence, the actual useful information available to the
adversary is (i, t). We assume that the network begins operations at time t = 0.
The attacker’s objective is to locate the source or the sink by snooping on the wireless transmissions.
The main observation used by the global adversary is: there must be a sequence of spatial-temporal
correlated packets involved in each communication from the source to the sink. As long as the
adversary knows the routing protocol, he can easily identify all these sequences from the traffic and
determine the set of possible sources and sinks. Intuitively, the defender has to create dummy
sequences in the network to confuse the attacker; such dummy sequences usually require the addition
of dummy traffic into the network, leading to more communication overhead. Clearly, there is a
trade-off between the location privacy and the communication overhead. We develop a theoretical
study of this trade-off.
We now describe our privacy model in detail. We will first describe a privacy model for source-
location privacy and then extend it to include sink-location privacy. Some notations frequently used
in this paper, their specific meanings will be further explained in our discussion below. A sensor
network deployed for an application can be viewed as a graph G = {V, E} where the set of vertices V
is the union of the set I of sensor nodes and the set of sinks. A small subset of the sensors will be the
source nodes. The set E of edges includes all direct communication links between sensor nodes
physically close to each other. At any point in time, from the global eavesdropper’s point of view,
the network can be considered to include a set SP, a set SA and a set of sensors that transfer data
between sources and sinks. The adversary eavesdrops on the entire network with the intention of
physically locating objects. We model each observation of the adversary as the tuple (i, t),
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representing the fact that a packet has been emitted by a node i and observed by the adversary at time
t.
VI. PRIVACY-PRESERVING ROUTING
We present the proposed privacy-preserving techniques for protecting the location information of
monitored objects and data sinks. We assume that all communications between sensor nodes in the
network are encrypted so that the contents of packets appear random to the global eavesdropper.
Many key predistribution protocols can be used for this purpose [5]. We present two techniques to
provide location privacy to monitored objects in sensor networks, periodic collection and source
simulation. The periodic collection method achieves the optimal privacy but can only be applied to
applications that collect data at a low rate and do not have strict requirements on the data delivery
latency. The source simulation method provides practical trade-offs between privacy, communication
overhead, and latency.
6.1. Sink-Location Privacy Techniques
Two privacy-preserving routing techniques for sink-location privacy in sensor networks: sink
simulation and backbone flooding. The sink simulation method achieves location privacy by
simulating sinks at specified locations, and the backbone flooding method provides location privacy
by flooding the event reports in a backbone network that covers the data sinks. Both techniques
provide trade-offs between privacy, communication cost, and latency. In this work, we focus on
protection of passive sinks that only receive data from sensors. We will consider location privacy for
sinks that broadcast packets in future work.
In backbone flooding, we send packets to a connected portion of the network, the backbone, instead
of sending them directly to a few sinks. The packets are only flooded among the backbone members,
the sensors that belong to this backbone. As long as the real sinks are located in the communication
range of at least one backbone member, they can receive packets from any source in the field.
Clearly, for a global eavesdropper, the sink could be anywhere near the backbone. We assume that
the backbone is created soon after the network is deployed and that the adversary does not eavesdrop
until the backbone is created.
The main component of backbone flooding is the construction of the backbone. Existing studies have
focused on finding the minimal number of sensors that are needed to flood a packet so that the entire
network can receive it [11]. In our case, we need to flood the packets to cover an area large enough
to achieve the desired level of location privacy. In backbone flooding, we create a backbone
consisting of |L| members, such that each sink is within the range of at least one backbone member.
Given |L|, the backbone formed should cover as large an area as possible for maximum location
privacy. However, finding optimal solutions has been shown to be NP-hard [12].
Every new sensor v added to the set L will send an election message to find the number of uncovered
sensors each neighbor can cover. If maxv(m) outputs a valid sensor ID and the coverage of this node,
the ID of this node will be added to L. The newly added sensor will then execute the same algorithm.
If maxv(m) = , v will collaborate with existing nearby backbone members to find a usable sensor
using Algorithm 1. The backbone is a tree structure with backbone members as the tree nodes.
During the collaboration, the sensor will need to get information from its parent to find a node that
can cover at least m nodes. This collaboration could continue to next level of ancestors if such a node
is not known to the immediate parent. This backtracking process continues until a sensor meeting the
required constraints is found. If a sensor that can cover at least m uncovered sensors is unavailable, a
sensor that covers the maximum number of uncovered sensors is used.
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Algorithm 1. Backtrack Procedure
1: procedure BACKTRACK(Coverage, Id,m)
2: ResultId Id
3: Max Coverage
4: LocalMaxId -1
5: CollectCoverageInfo(GetMyId(),NULL)
6: (LocalMaxId,Max) MaxId(m)
7: if Max m then
return LocalMaxId, Max
8: else if Max < Coverage then
9: ResultId = LocalMaxId
10: Max = Coverage
11: end if
12: for EachUnvisitedNeighborBKMember do
13: (Id,Coverage) = Backtrack(Max, ResultId,m)
14: if Coverage m then
15: ResultId = Id
16: Max = Coverage
17: break
18: else if Coverage > Max then
19: Max = Coverage
20: ResultId = Id
21: end if
22: end for return ResultId,Max
23: end procedure
The beginning and termination of the backtracking process depends on the value of m. A value of m
≤ 1 would mean that backtracking would start only if v cannot find any neighbor that can cover at
least one uncovered sensor. If m has a value greater than the number of neighbors any sensor could
have, then the backtracking process would ensure that the sensor that covers the maximum number
of uncovered sensors is selected. Intuitively, this would mean that an increase of m would help in
covering more sensors with the help of fewer backbone members. More energy will be consumed to
form a backbone for a large m due to more backtracking steps.
VII. INTEGRATED SECURITY AND ATTACK DETECTION SCHEME
The proposed system integrates the location privacy and data security process for the wireless sensor
network. Region based query model is used to improve location privacy. Confidentiality and
integrity techniques are used for the security process. Rivest Cipher (RC4) algorithm and Secure
Hashing Algorithms (SHA) are used for the data security. The system is designed to provide location
privacy and data security for sensor networks. Adhoc query processing is performed in the system.
Location privacy is provided in node and sinks level. The system is divided into six major modules.
They are network deployment, data capture, query submission, sink level privacy, node level privacy
and security management. The network deployment module is designed to construct wireless sensor
networks. The data capture process module is designed to perform data sensing operations. Query
submission module is designed to handle query submission tasks. Sink level privacy is provided
under Sink privacy module. The node level privacy is provided under the node privacy module. The
security management module is designed to handle key and data distribution process.
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7.1. Network Deployment
The network deployment module is designed to setup wireless sensor nodes. Sensor node and its
properties are collected from the user. Sensor nodes are placed with its coverage information. The
network is divided into a set of clusters.
7.2. Data Capture
The data capture process is performed in the sensor nodes. The data values are captured and updated
into the memory. The data values are updated with time information. The sensor nodes are managed
by the sink nodes.
7.3. Query Submission
The query submission process is initiated from the base station or external systems. The query values
are issued with node and time information. Node and sink level query values are used in the system.
Query values are prepared with node identification protection process.
7.4. Sink Level Privacy
The sink level privacy model protects the query processing under the sink nodes. The sink node
collects the query value from the base station. The sink node redirects the query value to the
downlink nodes. The query response is collected from the node by the sink node.
7.5. Node Level Privacy
Node level privacy model is used to protect sensor node based query values. The query values are
issued for the selected node. Query details are encrypted with node level key values. Node
identification values are protected by the system.
7.6. Security Management
The system provides security for query response from the sensor nodes. Rivest Cipher (RC4)
algorithm is used for the data confidentiality process. Data integrity is verified using the Secure
Hashing Algorithm (SHA). Key values are distributed from the base station.
VIII. CONCLUSION
Sensor networks are constructed to capture environment information. Data centers collect
information from sensor devices. Location privacy is provided for the sensor node and sinks node
levels. Data security is integrated with the location privacy scheme. The system manages the data
collection and analysis operations in sensor networks. The system reduces the bandwidth and battery
power consumption. Sensitive location and data values are protected by the system. Traffic level is
reduced by the system.
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