Providing an efficient security for wireless sensor network is a crucial challenge which is made more
difficult due to its broadcast nature and restrictions on resources such as energy, power memory usage,
computation and communication capabilities. The Reactive Jammer Attack is a major security threat to
wireless sensor networks because reactive jammer attack is a light weight attack which is easy to launch
but difficult to detect .This work suggest a new scheme to neutralize malicious reactive jammer nodes by
changing the characteristic of trigger nodes to act as only receiver. Here the current approach attempts to
identify the trigger nodes using the group testing technique, which enhances the identification speed and
reduces the message complexity of the status report sent periodically between the sensor nodes and the
base station.
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 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
This document summarizes research on defeating denial-of-service (DoS) attacks in wireless networks in the presence of jammers. It describes common types of jamming attacks like constant, deceptive, random, and reactive jammers. Detection techniques for jammers and methods to reduce the impact of DoS attacks are discussed. The objective is to detect jammers, lessen the effect of DoS attacks, and improve wireless communication security. Key jamming criteria like energy efficiency, detection probability, denial-of-service level, and strength against physical layer techniques are also outlined.
This document presents a project on preventing selective jamming attacks on wireless networks. It discusses existing jamming attacks, proposes a system to address selective jamming by an insider, and outlines the advantages of preventing real-time packet classification. The document contains sections on aim, existing system, proposed system, advantages, software and hardware specifications, conclusions, and references.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
We would send hard copy of Journal by speed post to the address of correspondence author after online publication of paper.
We will dispatched hard copy to the author within 7 days of date of publication
Detection and prevention of wormhole attack in mobile adhoc networksambitlick
This document discusses detection and prevention of wormhole attacks in mobile ad hoc networks. A wormhole attack is a powerful attack where two or more malicious nodes collude to tunnel packets between them, emulating a shorter route and attracting traffic. This can severely disrupt network communication. The paper proposes a novel trust-based scheme to identify wormhole-creating nodes without cryptography. Extensive simulations show the scheme effectively handles colluding malicious nodes without imposing extra network conditions.
WDA: Wormhole Attack Detection Algorithm based on measuring Round Trip Delay ...ijsrd.com
The recent advancements in the wireless arena and their wide-spread utilization have introduced new security vulnerabilities. The wireless media being shared is exposed to outside world, so it is susceptible to various attacks at different layers of OSI network stack. For example, jamming and device tampering at the physical layer; disruption of the medium access control (MAC) layer; routing attacks like Blackhole, rushing, wormhole; targeted attacks on the transport protocol like session hijacking, SYN flooding or even attacks intended to disrupt specific applications through viruses, worms and Trojan Horses. Wormhole attack is one of the serious routing attacks amongst all the network layer attacks launched on MANET. Wormhole attack is launched by creation of tunnels and it leads to total disruption of the routing paths on MANET. In this paper, Wormhole detection algorithm (WDA) is proposed based on modifying the forwarding packet process that detects and isolates wormhole nodes in ad hoc on demand distance vector (AODV) routing protocol.
This document presents optimal jamming attack strategies in wireless sensor networks. It discusses using monitoring nodes to detect jammer attacks and putting sensor nodes in sleep mode when attacks are detected to avoid energy loss. The document outlines different types of attacks in wireless sensor networks including passive and active attacks. It proposes using a detection algorithm at monitoring nodes to analyze observations and decide if an attack is occurring. The goal is to study controllable jamming attacks that are difficult to detect and defend against.
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 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
This document summarizes research on defeating denial-of-service (DoS) attacks in wireless networks in the presence of jammers. It describes common types of jamming attacks like constant, deceptive, random, and reactive jammers. Detection techniques for jammers and methods to reduce the impact of DoS attacks are discussed. The objective is to detect jammers, lessen the effect of DoS attacks, and improve wireless communication security. Key jamming criteria like energy efficiency, detection probability, denial-of-service level, and strength against physical layer techniques are also outlined.
This document presents a project on preventing selective jamming attacks on wireless networks. It discusses existing jamming attacks, proposes a system to address selective jamming by an insider, and outlines the advantages of preventing real-time packet classification. The document contains sections on aim, existing system, proposed system, advantages, software and hardware specifications, conclusions, and references.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
We would send hard copy of Journal by speed post to the address of correspondence author after online publication of paper.
We will dispatched hard copy to the author within 7 days of date of publication
Detection and prevention of wormhole attack in mobile adhoc networksambitlick
This document discusses detection and prevention of wormhole attacks in mobile ad hoc networks. A wormhole attack is a powerful attack where two or more malicious nodes collude to tunnel packets between them, emulating a shorter route and attracting traffic. This can severely disrupt network communication. The paper proposes a novel trust-based scheme to identify wormhole-creating nodes without cryptography. Extensive simulations show the scheme effectively handles colluding malicious nodes without imposing extra network conditions.
WDA: Wormhole Attack Detection Algorithm based on measuring Round Trip Delay ...ijsrd.com
The recent advancements in the wireless arena and their wide-spread utilization have introduced new security vulnerabilities. The wireless media being shared is exposed to outside world, so it is susceptible to various attacks at different layers of OSI network stack. For example, jamming and device tampering at the physical layer; disruption of the medium access control (MAC) layer; routing attacks like Blackhole, rushing, wormhole; targeted attacks on the transport protocol like session hijacking, SYN flooding or even attacks intended to disrupt specific applications through viruses, worms and Trojan Horses. Wormhole attack is one of the serious routing attacks amongst all the network layer attacks launched on MANET. Wormhole attack is launched by creation of tunnels and it leads to total disruption of the routing paths on MANET. In this paper, Wormhole detection algorithm (WDA) is proposed based on modifying the forwarding packet process that detects and isolates wormhole nodes in ad hoc on demand distance vector (AODV) routing protocol.
This document presents optimal jamming attack strategies in wireless sensor networks. It discusses using monitoring nodes to detect jammer attacks and putting sensor nodes in sleep mode when attacks are detected to avoid energy loss. The document outlines different types of attacks in wireless sensor networks including passive and active attacks. It proposes using a detection algorithm at monitoring nodes to analyze observations and decide if an attack is occurring. The goal is to study controllable jamming attacks that are difficult to detect and defend against.
Preventing jamming attack by combining cryptographyRumana Firdose
This document outlines a project to prevent selective jamming attacks in wireless networks. The project aims to combine three cryptographic schemes: 1) a strong hiding commitment scheme (SHCS) based on symmetric cryptography, 2) a cryptographic puzzle hiding scheme (CPHS) that forces recipients to perform computations before extracting secrets, and 3) an all-or-nothing transformation (AONT) scheme that sends pseudo-messages corresponding to original packets so the jammer cannot classify packets until all are received. The objectives are to prevent selective jamming, avoid packet dropouts, show a jammer's impact, and secure transmissions. A literature review analyzes previous work on jamming detection and prevention. The methodology describes each scheme and an
An Assessment of Security Mechanisms Against Reactive Jammer Attack In Wirele...ijfcstjournal
Wireless sensor networks have been widely applied to various domains such as environmental monitoring
and surveillance. Since wireless sensor networks utilize open transmission media, they are prone to radio
jamming attacks. These attacks are easy to launch but difficult to defend. These attacks may lead to low
network throughput because of jamming signals. Failure of data transmission in sensor networks is due to
corruption of packets by reactive jammers. A number of defence techniques have been proposed in recent
years to deal with these jammer attacks. However, each defence technique is suitable for only a limited
network range and specific jamming conditions. This paper proposes an adaptive approach to detect and
isolate the reactive jammers by using status messages and trigger identification service.
Source based Security Issues in WDM Systems IJECEIAES
The issue of security has become a bigger heddle for all telecommunication companies to climb in this era where information hungry customers are increasing daily. Unauthorized users are finding novel ways of accessing information of others and thereby attacking the requisite legitimate users’ information accounting to security threats. In this work, two forms of WDM system attacks will be considered. These attacks include a clone source based attack where the adversary tries to replicate the transmitted signal of the legitimate user by transmitting at the same wavelength and power and the different wavelength source based attack where the adversary transmit at a wavelength different from that of the legitimate user thereby creating interaction effects igniting security issues. Finally, a simulation of the outcome will be considered and the resulting output will be analyzed.
The document proposes a label-based secure localization scheme to defend against wormhole attacks in wireless sensor networks. It analyzes the impact of wormhole attacks on DV-Hop localization and describes a three-phase approach to label beacon and sensor nodes to identify and remove illegal connections introduced by wormholes. Simulation results show the scheme is effective at detecting wormholes and minimizing their impact on localization accuracy.
Packet hiding methods for preventing selective jamming attacksShaik Irfan
This project mainly describes how a data can be send securely via a network without getting being hacked by any intruder.here we use various different kind of cryptographic principal and secure mechanism where in which it complete protection to our data
Securing WSN communication using Enhanced Adaptive Acknowledgement ProtocolIJMTST Journal
This document summarizes an enhanced adaptive acknowledgement protocol for securing wireless sensor network communication. It begins by describing security challenges in WSNs like the wireless medium, hostile environments, and resource constraints. It then discusses common security attacks like black hole and grey hole attacks. Existing acknowledgement schemes like Watchdog, TWOACK, and AACK are explained along with their limitations in detecting such attacks. The document proposes an Enhanced Adaptive Acknowledgement (EAACK) scheme that uses ACK, Secure ACK, and Misbehavior Report Authentication to better detect attacks while reducing overhead. EAACK aims to securely detect black hole, grey hole, and false misbehavior reporting in wireless sensor networks.
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.
TRUST VALUE ALGORITHM: A SECURE APPROACH AGAINST PACKET DROP ATTACK IN WIRELE...IJNSA Journal
Wireless ad-hoc networks are widely used because these are very easy to deploy. However, there are
various security issues and problems. Two most important issues are interoperability and interaction
among various security technologies which are very important to consider for configuration and
management point of view. The packet drop ratio in the wireless network is very high as well as packets
may be easily delayed by the attacker. Ii is very difficult to detect intruders, so it results into high false
positive rate. Packets may be dropped or delayed by intruders as well as external nodes in wireless
networks. Hence, there is the need of effective intrusion detection system which can detect maximum
number of intruders and the corresponding packets be forwarded through some alternate paths in the
network. In this paper we propose an alternate solution to detect the intruders/adversary with help of trust
value. It would remove the need of inbuilt IDS in the wireless networks and result into improving the
performance of WLAN.
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
In our research work we are improving the performance of mobile ad hoc networks under jamming attack by using an integrated approach. The proposed work includes a network with high mobility, using IEEE Along g standard jamming attacks and countermeasures in wireless sensor networks
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 detection of node replication attack on wireless sensor networkIOSR Journals
This document summarizes two techniques for detecting node replication attacks in wireless sensor networks: centralized detection and distributed detection. Centralized detection involves nodes reporting information to a base station, which can detect replication by identifying conflicting location claims for the same node ID. Distributed detection techniques like witness-based strategies and deployment knowledge allow nodes to detect replication locally without a base station through methods like node broadcasting claims to witness nodes. The document analyzes the advantages and limitations of each approach.
Jamming Anticipation and Convolution through Immaculate Hiding Process of Pac...IOSR Journals
This document discusses selective jamming attacks on wireless networks. It defines the problem of real-time packet classification by jamming nodes and developing mechanisms to prevent this. It presents the network and adversary models considered. Optimization problems are formulated to represent the best strategies for the attacker and network when they have imperfect knowledge of each other. Detection of jamming attacks is also addressed through monitoring packet delivery ratios across nodes.
3 packet-hiding methods for preventing selective11W91D5809
This document proposes and evaluates methods for preventing selective jamming attacks in wireless networks. It discusses how an adversary with internal knowledge can launch selective jamming attacks by classifying packets in real-time. Three schemes are developed that combine cryptographic techniques with physical layer attributes to prevent real-time packet classification and mitigate these attacks. The security and performance overhead of the schemes are analyzed.
Packet-Hiding Methods: To Prevent Selective Jamming AttacksSwapnil Salunke
This document proposes a new packet-hiding scheme called PHSPL to prevent selective jamming attacks. It first discusses existing jamming attacks and anti-jamming techniques' limitations. Then it analyzes previous schemes like spread spectrum, spatial retreats, and AONT-based hiding that fail against internal threats. The proposed PHSPL scheme sends packets with headers and sequence IDs directly to hosts to overcome AONT's disadvantage of continuous packet loss and prevent real-time packet classification by jammers. The conclusion reasserts that PHSPL can mitigate selective jamming attacks.
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.
Improvement of quality of service parameters using reinvented fsmac protocol ...eSAT Journals
This document discusses improving quality of service parameters in wireless sensor networks using a reinvented FSMAC protocol. The FSMAC protocol first uses fuzzy logic to detect intrusions based on two new parameters: the number of times a node senses a free channel and the variation in channel sense periods. If an intrusion is detected, appropriate countermeasures are taken to reduce the effects of attacks. Simulations with 20 nodes show that the reinvented FSMAC protocol increases successful data transmission rates and network throughput.
This document discusses improving quality of service parameters in wireless sensor networks using a reinvented fuzzy logic secure media access control (FSMAC) protocol. It proposes using two new intrusion detection parameters - the number of times a node senses a free channel and the variation in the channel sense period. The protocol uses fuzzy logic to detect intrusions based on these parameters. If an intrusion is detected, the defense module is triggered to switch nodes to a different radio frequency band or stop transmissions to avoid attacks. Simulations with 20 nodes show this approach can increase successful data transmission rates and network throughput.
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.
A survey on jamming attacks, detection and defending strategies in wireless s...eSAT Journals
Abstract
Wireless Sensor Network (WSN)s are now a days most widely used and are undergoing many security threats. Of the different types of threats, Jamming attack has been considered a severe security threat. These jamming attacks cause the overutilization of scarce resources like the battery power. Further, high computations require lot of memory. Such problems cause the reduction in the lifetime of the sensor nodes in WSNs. There are four types of jamming attacks in which the most difficult type of attack is the reactive jammer as it is easy to launch by the adversary but very difficult to detect and defend. In this paper we present a brief survey of the types of jamming attacks, methods used to detect and defend the jammers.
Keywords: Wireless Sensor Networks, Jamming Attacks, Reactive jamming attack, and Trigger node identification
Jamming Attacks Prevention in Wireless Networks Using Packet Hiding MethodsIOSR Journals
This document discusses selective jamming attacks in wireless networks and methods to prevent them. It begins by introducing the open nature of wireless networks leaves them vulnerable to jamming attacks. It then discusses different types of jamming attacks and notes that selective jamming, which targets specific important packets, is more effective than continuous jamming. The document proposes using cryptographic techniques like commitment schemes and puzzles combined with physical layer parameters to prevent real-time packet classification and selective jamming. It reviews related work on jamming attacks and defenses. Finally, it outlines the problem statement, system model, and the contribution of using symmetric encryption and resisting brute force block encryption attacks to reduce jamming through packet hiding.
Preventing jamming attack by combining cryptographyRumana Firdose
This document outlines a project to prevent selective jamming attacks in wireless networks. The project aims to combine three cryptographic schemes: 1) a strong hiding commitment scheme (SHCS) based on symmetric cryptography, 2) a cryptographic puzzle hiding scheme (CPHS) that forces recipients to perform computations before extracting secrets, and 3) an all-or-nothing transformation (AONT) scheme that sends pseudo-messages corresponding to original packets so the jammer cannot classify packets until all are received. The objectives are to prevent selective jamming, avoid packet dropouts, show a jammer's impact, and secure transmissions. A literature review analyzes previous work on jamming detection and prevention. The methodology describes each scheme and an
An Assessment of Security Mechanisms Against Reactive Jammer Attack In Wirele...ijfcstjournal
Wireless sensor networks have been widely applied to various domains such as environmental monitoring
and surveillance. Since wireless sensor networks utilize open transmission media, they are prone to radio
jamming attacks. These attacks are easy to launch but difficult to defend. These attacks may lead to low
network throughput because of jamming signals. Failure of data transmission in sensor networks is due to
corruption of packets by reactive jammers. A number of defence techniques have been proposed in recent
years to deal with these jammer attacks. However, each defence technique is suitable for only a limited
network range and specific jamming conditions. This paper proposes an adaptive approach to detect and
isolate the reactive jammers by using status messages and trigger identification service.
Source based Security Issues in WDM Systems IJECEIAES
The issue of security has become a bigger heddle for all telecommunication companies to climb in this era where information hungry customers are increasing daily. Unauthorized users are finding novel ways of accessing information of others and thereby attacking the requisite legitimate users’ information accounting to security threats. In this work, two forms of WDM system attacks will be considered. These attacks include a clone source based attack where the adversary tries to replicate the transmitted signal of the legitimate user by transmitting at the same wavelength and power and the different wavelength source based attack where the adversary transmit at a wavelength different from that of the legitimate user thereby creating interaction effects igniting security issues. Finally, a simulation of the outcome will be considered and the resulting output will be analyzed.
The document proposes a label-based secure localization scheme to defend against wormhole attacks in wireless sensor networks. It analyzes the impact of wormhole attacks on DV-Hop localization and describes a three-phase approach to label beacon and sensor nodes to identify and remove illegal connections introduced by wormholes. Simulation results show the scheme is effective at detecting wormholes and minimizing their impact on localization accuracy.
Packet hiding methods for preventing selective jamming attacksShaik Irfan
This project mainly describes how a data can be send securely via a network without getting being hacked by any intruder.here we use various different kind of cryptographic principal and secure mechanism where in which it complete protection to our data
Securing WSN communication using Enhanced Adaptive Acknowledgement ProtocolIJMTST Journal
This document summarizes an enhanced adaptive acknowledgement protocol for securing wireless sensor network communication. It begins by describing security challenges in WSNs like the wireless medium, hostile environments, and resource constraints. It then discusses common security attacks like black hole and grey hole attacks. Existing acknowledgement schemes like Watchdog, TWOACK, and AACK are explained along with their limitations in detecting such attacks. The document proposes an Enhanced Adaptive Acknowledgement (EAACK) scheme that uses ACK, Secure ACK, and Misbehavior Report Authentication to better detect attacks while reducing overhead. EAACK aims to securely detect black hole, grey hole, and false misbehavior reporting in wireless sensor networks.
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.
TRUST VALUE ALGORITHM: A SECURE APPROACH AGAINST PACKET DROP ATTACK IN WIRELE...IJNSA Journal
Wireless ad-hoc networks are widely used because these are very easy to deploy. However, there are
various security issues and problems. Two most important issues are interoperability and interaction
among various security technologies which are very important to consider for configuration and
management point of view. The packet drop ratio in the wireless network is very high as well as packets
may be easily delayed by the attacker. Ii is very difficult to detect intruders, so it results into high false
positive rate. Packets may be dropped or delayed by intruders as well as external nodes in wireless
networks. Hence, there is the need of effective intrusion detection system which can detect maximum
number of intruders and the corresponding packets be forwarded through some alternate paths in the
network. In this paper we propose an alternate solution to detect the intruders/adversary with help of trust
value. It would remove the need of inbuilt IDS in the wireless networks and result into improving the
performance of WLAN.
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
In our research work we are improving the performance of mobile ad hoc networks under jamming attack by using an integrated approach. The proposed work includes a network with high mobility, using IEEE Along g standard jamming attacks and countermeasures in wireless sensor networks
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 detection of node replication attack on wireless sensor networkIOSR Journals
This document summarizes two techniques for detecting node replication attacks in wireless sensor networks: centralized detection and distributed detection. Centralized detection involves nodes reporting information to a base station, which can detect replication by identifying conflicting location claims for the same node ID. Distributed detection techniques like witness-based strategies and deployment knowledge allow nodes to detect replication locally without a base station through methods like node broadcasting claims to witness nodes. The document analyzes the advantages and limitations of each approach.
Jamming Anticipation and Convolution through Immaculate Hiding Process of Pac...IOSR Journals
This document discusses selective jamming attacks on wireless networks. It defines the problem of real-time packet classification by jamming nodes and developing mechanisms to prevent this. It presents the network and adversary models considered. Optimization problems are formulated to represent the best strategies for the attacker and network when they have imperfect knowledge of each other. Detection of jamming attacks is also addressed through monitoring packet delivery ratios across nodes.
3 packet-hiding methods for preventing selective11W91D5809
This document proposes and evaluates methods for preventing selective jamming attacks in wireless networks. It discusses how an adversary with internal knowledge can launch selective jamming attacks by classifying packets in real-time. Three schemes are developed that combine cryptographic techniques with physical layer attributes to prevent real-time packet classification and mitigate these attacks. The security and performance overhead of the schemes are analyzed.
Packet-Hiding Methods: To Prevent Selective Jamming AttacksSwapnil Salunke
This document proposes a new packet-hiding scheme called PHSPL to prevent selective jamming attacks. It first discusses existing jamming attacks and anti-jamming techniques' limitations. Then it analyzes previous schemes like spread spectrum, spatial retreats, and AONT-based hiding that fail against internal threats. The proposed PHSPL scheme sends packets with headers and sequence IDs directly to hosts to overcome AONT's disadvantage of continuous packet loss and prevent real-time packet classification by jammers. The conclusion reasserts that PHSPL can mitigate selective jamming attacks.
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.
Improvement of quality of service parameters using reinvented fsmac protocol ...eSAT Journals
This document discusses improving quality of service parameters in wireless sensor networks using a reinvented FSMAC protocol. The FSMAC protocol first uses fuzzy logic to detect intrusions based on two new parameters: the number of times a node senses a free channel and the variation in channel sense periods. If an intrusion is detected, appropriate countermeasures are taken to reduce the effects of attacks. Simulations with 20 nodes show that the reinvented FSMAC protocol increases successful data transmission rates and network throughput.
This document discusses improving quality of service parameters in wireless sensor networks using a reinvented fuzzy logic secure media access control (FSMAC) protocol. It proposes using two new intrusion detection parameters - the number of times a node senses a free channel and the variation in the channel sense period. The protocol uses fuzzy logic to detect intrusions based on these parameters. If an intrusion is detected, the defense module is triggered to switch nodes to a different radio frequency band or stop transmissions to avoid attacks. Simulations with 20 nodes show this approach can increase successful data transmission rates and network throughput.
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.
A survey on jamming attacks, detection and defending strategies in wireless s...eSAT Journals
Abstract
Wireless Sensor Network (WSN)s are now a days most widely used and are undergoing many security threats. Of the different types of threats, Jamming attack has been considered a severe security threat. These jamming attacks cause the overutilization of scarce resources like the battery power. Further, high computations require lot of memory. Such problems cause the reduction in the lifetime of the sensor nodes in WSNs. There are four types of jamming attacks in which the most difficult type of attack is the reactive jammer as it is easy to launch by the adversary but very difficult to detect and defend. In this paper we present a brief survey of the types of jamming attacks, methods used to detect and defend the jammers.
Keywords: Wireless Sensor Networks, Jamming Attacks, Reactive jamming attack, and Trigger node identification
Jamming Attacks Prevention in Wireless Networks Using Packet Hiding MethodsIOSR Journals
This document discusses selective jamming attacks in wireless networks and methods to prevent them. It begins by introducing the open nature of wireless networks leaves them vulnerable to jamming attacks. It then discusses different types of jamming attacks and notes that selective jamming, which targets specific important packets, is more effective than continuous jamming. The document proposes using cryptographic techniques like commitment schemes and puzzles combined with physical layer parameters to prevent real-time packet classification and selective jamming. It reviews related work on jamming attacks and defenses. Finally, it outlines the problem statement, system model, and the contribution of using symmetric encryption and resisting brute force block encryption attacks to reduce jamming through packet hiding.
International Journal of Computational Engineering Research(IJCER)ijceronline
1. The document discusses selective jamming attacks in wireless networks. Selective jamming attacks target important messages to degrade network performance.
2. The authors develop three schemes that combine cryptographic techniques with physical layer attributes to prevent real-time packet classification and mitigate selective jamming attacks.
3. The schemes are analyzed for their security and computational and communication overhead. The schemes aim to prevent adversaries from identifying important messages to selectively jam on the physical layer.
Ij a survey on preventing jamming attacks in wireless communicationshobanavsm
The document summarizes techniques for preventing jamming attacks in wireless communication. It discusses (1) how to thwart jamming in control channels by organizing networks into clusters with clusterheads, (2) using uncoordinated spread spectrum techniques like frequency hopping to enable anti-jamming broadcast communication, and (3) mitigating jamming impact on timing channels by using packet reception events to build low-rate overlays and allow communication despite interference. The key techniques analyzed are cluster-based architectures, uncoordinated frequency hopping, and using timing channels to transfer data even when the network is disrupted.
ADVANCED TECHNIQUES FOR PREVENTING SELECTIVE JAMMING ATTACKS USING PACKET-HID...ijiert bestjournal
The wireless networks are more vulnerable to jammin g. This jamming can be used as a launch pad for mounting Denial-Of-Service attack on wireless networks. Typically,jamming has been address under an external threat model. Ho wever,adversaries with internal knowledge of protocol specification and network sec rets can launch low-effort jamming attacks that are difficult to detect and counter. I n this work we address the problem of jamming attacks as internal threat model,where the attacker is aware of all network secrets and details of implementation. These types of attac kers are difficult to identify. In this work we address the problem of selective jamming attacks . In these attacks the attacker is active for only short period of time,selectively targetin g the messages. The selective jamming attacks can be launched by performing real-time pac ket classification at the physical layer. To mitigate these attacks,we illustrate different sch emes that prevent real-time packet classification by combining cryptographic primitive s with physical-layer attributes.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
This document summarizes a research paper that proposes a distributed localization scheme to detect jamming attacks in mobile ad hoc networks (MANETs). The scheme involves all nodes operating in promiscuous mode to monitor neighboring nodes for abnormal behavior, using metrics like packet delivery ratio and signal strength. If abnormal behavior is detected, an alert is broadcasted without relying on a centralized authority. This distributed approach is evaluated through simulations and found to more efficiently detect jamming attacks compared to a clustered network architecture with designated cluster heads.
The document summarizes a research paper on avoiding jamming attacks over wireless networks through packet hiding. It discusses how selective jamming works, impacting network performance. It proposes three schemes combining cryptographic mechanisms like puzzle schemes, commitment schemes, and all-or-nothing transformations with physical layer parameters to mitigate selective jamming. The main goal is to transform a selective jammer into a random one and enable safe transmission even with a jammer present.
PREVENTION OF WORMHOLE ATTACK IN WIRELESS SENSOR NETWORKIJNSA Journal
Ubiquitous and pervasive applications, where the Wireless Sensor Networks are typically deployed, lead to the susceptibility to many kinds of security attacks. Sensors used for real time response capability also make it difficult to devise the resource intensive security protocols because of their limited battery, power, memory and processing capabilities. One of potent form of Denial of Service attacks is Wormhole attack that affects on the network layer. In this paper, the techniques dealing with wormhole attack are investigated and an approach for wormhole prevention is proposed. Our approach is based on the analysis of the two-hop neighbors forwarding Route Reply packet. To check the validity of the sender, a unique key between the individual sensor node and the base station is required to be generated by suitable scheme.
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.
IMPACT ANALYSIS OF BLACK HOLE ATTACKS ON MOBILE AD HOC NETWORKS PERFORMANCEijgca
A Mobile Ad hoc Network (MANET) is a collection of mobile stations with wireless interfaces which form a temporary network without using any central administration. MANETs are more vulnerable to attacks because
they have some specific characteristics as complexity of wireless communication and lack of infrastructure. Hence security is an important requirement in mobile ad hoc networks. One of the attacks against network integrity
in MANETs is the Black Hole Attack. In this type of attack all data packets are absorbed by malicious node, hence data loss occurs. In this paper we investigated the impacts of Black Hole attacks on the network
performance. We have simulated black hole attacks using Network Simulator 2 (NS-2) and have measured the packet loss in the network without and with a black hole attacks. Also, we measured the packet loss when the
number of black hole attacks increases.
IMPACT ANALYSIS OF BLACK HOLE ATTACKS ON MOBILE AD HOC NETWORKS PERFORMANCEijgca
A Mobile Ad hoc Network (MANET) is a collection of mobile stations with wireless interfaces which form a temporary network without using any central administration. MANETs are more vulnerable to attacks because they have some specific characteristics as complexity of wireless communication and lack of infrastructure. Hence security is an important requirement in mobile ad hoc networks. One of the attacks against network integrity in MANETs is the Black Hole Attack. In this type of attack all data packets are absorbed by malicious node, hence data loss occurs. In this paper we investigated the impacts of Black Hole attacks on the network performance. We have simulated black hole attacks using Network Simulator 2 (NS-2) and have measured the packet loss in the network without and with a black hole attacks. Also, we measured the packet loss when the number of black hole attacks increases.
This document summarizes a study on the impact of black hole attacks on the performance of mobile ad hoc networks (MANETs). The study used the Network Simulator 2 (NS-2) to simulate black hole attacks on MANETs using the Ad Hoc On-Demand Distance Vector (AODV) routing protocol. It found that the packet delivery ratio decreased significantly when black hole nodes were introduced that dropped packets instead of forwarding them as they should. Increasing the number of black hole nodes caused an even more dramatic decrease in the packet delivery ratio.
This document summarizes a study on the impact of black hole attacks on the performance of mobile ad hoc networks (MANETs). The study used the Network Simulator 2 (NS-2) to simulate black hole attacks in MANETs using the Ad hoc On-Demand Distance Vector (AODV) routing protocol. It was found that the packet delivery ratio decreased significantly when black hole attacks were introduced. Additionally, the packet delivery ratio decreased dramatically as the number of black hole nodes increased.
A secure routing process to simultaneously defend against false report and wo...ieijjournal
This document proposes a new secure routing scheme to simultaneously detect and defend against wormhole attacks and false report attacks in wireless sensor networks. Existing security schemes focus on defending against single attacks but their performance degrades when multiple attacks occur simultaneously. The proposed scheme uses a key partition-based routing protocol to mitigate the detection probability reduction caused by wormholes. It also defines a new event report format containing verification counts and wormhole detection mechanisms. The scheme aims to detect attacks with few hops and low overhead even if the sender or receiver is compromised.
This document discusses preventing and isolating black hole attacks in mobile ad hoc networks (MANETs) using alarm packets. It begins with background on MANETs and security attacks they face such as black hole attacks. Then, it reviews existing literature on detecting and preventing black hole attacks. Next, it describes how black hole attacks work in MANETs by having malicious nodes advertise short paths to destinations and drop packets. The proposed solution will use alarm packets to isolate and prevent black hole attacks in MANETs.
NOVEL HYBRID INTRUSION DETECTION SYSTEM FOR CLUSTERED WIRELESS SENSOR NETWORKIJNSA Journal
Wireless sensor network (WSN) is regularly deployed in unattended and hostile environments. The WSN is vulnerable to security threats and susceptible to physical capture. Thus, it is necessary to use effective mechanisms to protect the network. It is widely known, that the intrusion detection is one of the most efficient security mechanisms to protect the network against malicious attacks or unauthorized access. In this paper, we propose a hybrid intrusion detection system for clustered WSN. Our intrusion framework uses a combination between the Anomaly Detection based on support vector machine (SVM) and the Misuse Detection. Experiments results show that most of routing attacks can be detected with low false alarm.
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.
Prevention of Selective Jamming Attacks by Using Packet Hiding MethodsIOSR Journals
Abstract: The open nature of the wireless medium leaves it too weak to intentional interference attacks,
typically defined as jamming. This intentional interference with wireless transmissions can be used as a launch
pad for mounting Denial-of-Service attacks on wireless networks. Typically, jamming has been introduced
under an external threat model. However, intruders with internal knowledge of protocol specifications and
network secrets can launch low-effort jamming attacks that are difficult to detect and counter. In this work, we
address the problem of selective jamming attacks in wireless networks. In these attacks, the hacker is active only
for a short period of time, selectively targeting messages of high importance. We demonstrate the advantages of
selective jamming in terms of network performance degradation and hacker effort by presenting two case
studies; a selective attack on TCP and one on routing. We show that selective jamming attacks can be
forwarded by performing real-time packet classification at the physical layer. To reduce these attacks, we
develop three schemes that prevent real-time packet classification by combining cryptographic primitives with
physical-layer attributes. We analyze the security of the proposed methods and evaluate their computational and
communication overhead.
Malicious attack detection and prevention in ad hoc network based on real tim...eSAT 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.
Malicious attack detection and prevention in ad hoc network based on real tim...eSAT Journals
Abstract This paper deals with Real Time Operating System (RTOS) based secure wormhole detection and prevention in ad hoc networks. The wormhole attack can form a serious threat to wireless networks, especially against many ad hoc network routing protocols and location based wireless security systems. A wormhole is created in the ad hoc network by introducing two malicious nodes. These two nodes form a worm hole link and message is transmitted through this link. The next part of the work is to detect the wormhole link by defining worm hole detection and prevention algorithm. After detecting suspicious links, one node performs a verification procedure for each suspicious link. The detection procedure and verifying procedure of suspicious worm link are used for further prevention of wormhole attack in the ad hoc network.
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A Security Mechanism Against Reactive Jammer Attack In Wireless Sensor Networks Using Trigger Identification Service
1. International Journal of Security, Privacy and Trust Management (IJSPTM) vol 2, No 2, April 2013
DOI : 10.5121/ijsptm.2013.2204 43
A Security Mechanism Against Reactive Jammer
Attack In Wireless Sensor Networks Using Trigger
Identification Service
Ramya Shivanagu1
and Deepti C2
1
PG Student, The Oxford College of Engineering, India
ramya.shivanagu@gmail.com
2
Asst Professor, The Oxford College of Engineering, India
deeptic82@gmail.com
ABSTRACT
Providing an efficient security for wireless sensor network is a crucial challenge which is made more
difficult due to its broadcast nature and restrictions on resources such as energy, power memory usage,
computation and communication capabilities. The Reactive Jammer Attack is a major security threat to
wireless sensor networks because reactive jammer attack is a light weight attack which is easy to launch
but difficult to detect .This work suggest a new scheme to neutralize malicious reactive jammer nodes by
changing the characteristic of trigger nodes to act as only receiver. Here the current approach attempts to
identify the trigger nodes using the group testing technique, which enhances the identification speed and
reduces the message complexity of the status report sent periodically between the sensor nodes and the
base station.
KEYWORDS
Wireless sensor network, Jamming Techniques, Reactive jamming, Trigger identification.
1. INTRODUCTION
Wireless sensor networks has limited resource constraints in terms of energy and range which
leads to many challenging and intriguing security-sensitive problems that cannot be handled using
conventional security solutions. The broadcast nature of the transmission medium makes it prone
to attacks using jammers which use the method of injecting interference signals, which is why
they can be considered as the most critical and fatally adversarial threat that can disrupt the
networks. Jamming attacks do not have to modify communication packets or compromise any
sensors in order to launch the attack.This makes them difficult to detect and defend against. As a
consequence, wireless sensor networks are further exposed to passive and active attacks. A
malicious node initiates a passive attack [1] through inert observation of the ongoing
communication, whereas an active attacker is involved in transmission as well.
1.1. Jamming Techniques
The spot jamming technique [2] involves a malicious node that directs all its transmitting power
to a single frequency. It makes use of identical modulation schemes and less power to override
the original signal. The assault on WSNs due to this attack is easily avoided by surfing to another
2. International Journal of Security, Privacy and Trust Management ( IJSPTM) vol 2, No 2, April 2013
frequency. In case of Sweep jamming technique [3], the malicious node can jam multipl
communication frequencies, but this
simultaneously. The attack also leads to
increase consumption of energy in the network.
Fig 1: Different types of jamming techniques
Figure 1 is an illustration of the types of jamming techniques used in general to launch jammer
attacks. In Barrage jamming technique
simultaneously which decreases the signal
technique increases the range of jammed frequencies and reduces the output power of the jammed
node. Deceptive jamming[5] has the capability to flood the network with useless data which can
mislead the sensor nodes present in the network .The available bandwidth used by the sensor
nodes is reduced. The malicious nodes
existence.
1.2. Jamming Types
ational Journal of Security, Privacy and Trust Management ( IJSPTM) vol 2, No 2, April 2013
f Sweep jamming technique [3], the malicious node can jam multipl
communication frequencies, but this jamming does not affect all the involved nodes
. The attack also leads to packet loss and retransmission of packet data that will
e consumption of energy in the network.
Fig 1: Different types of jamming techniques
Figure 1 is an illustration of the types of jamming techniques used in general to launch jammer
. In Barrage jamming technique[4], the malicious node jams a group of frequencies
simultaneously which decreases the signal-to-noise ratio of the destination node. This jamming
technique increases the range of jammed frequencies and reduces the output power of the jammed
e jamming[5] has the capability to flood the network with useless data which can
mislead the sensor nodes present in the network .The available bandwidth used by the sensor
he malicious nodes that make use of this technique do not
Fig 2: Types of jammers
ational Journal of Security, Privacy and Trust Management ( IJSPTM) vol 2, No 2, April 2013
44
f Sweep jamming technique [3], the malicious node can jam multiple
does not affect all the involved nodes
of packet data that will
Figure 1 is an illustration of the types of jamming techniques used in general to launch jammer
[4], the malicious node jams a group of frequencies
noise ratio of the destination node. This jamming
technique increases the range of jammed frequencies and reduces the output power of the jammed
e jamming[5] has the capability to flood the network with useless data which can
mislead the sensor nodes present in the network .The available bandwidth used by the sensor
do not reveal their
3. International Journal of Security, Privacy and Trust Management ( IJSPTM) vol 2, No 2, April 2013
Figure 2 depicts several types of jammers that may be used in attacks against wireless sensor
networks namely constant jammer, deceptive jammer
constant jammer [6] emits uninterrupted radio signals in the wireless medium. They do not follow
any underlying MAC protocol and include just random bits. This jammer keeps the channel busy
and disturbs the communication between the nodes. The deceptive j
jamming techniques to attack the wireless sensor nodes. The random jammer [8] sleeps for an
indiscriminate time and wakes up to jam the network for an arbitrary time. The last jamming
approach indicated above is the reactive jamme
channel. On detection of legitimate activity, the jammer node immediately sends out a random
signal to disrupt the valid communication
1.3. System Architecture
The inference after comparing the above mentioned jamming attacks is that reactive jamming is a
far more destructive attack that
paper considers the reactive jammer attack since it
networks as the reactive jammer nodes can disrupt the message delivery of its neighbouring
sensor nodes with strong interference signals. The consequences of the attack are the loss of link
reliability, increased energy consumption, extended packet delays, and disruption of end
routes.
This work presents system architecture
description of the overall trigger
the set of sufferer nodes .These nodes are
testing is carried out at the base station
procedure to identify each individual node
can be stored locally for use by routing schemes or can be sent
ational Journal of Security, Privacy and Trust Management ( IJSPTM) vol 2, No 2, April 2013
Figure 2 depicts several types of jammers that may be used in attacks against wireless sensor
networks namely constant jammer, deceptive jammer ,random jammer and reactive jammer. The
constant jammer [6] emits uninterrupted radio signals in the wireless medium. They do not follow
any underlying MAC protocol and include just random bits. This jammer keeps the channel busy
and disturbs the communication between the nodes. The deceptive jammer [7] uses misleading
jamming techniques to attack the wireless sensor nodes. The random jammer [8] sleeps for an
indiscriminate time and wakes up to jam the network for an arbitrary time. The last jamming
approach indicated above is the reactive jammer [9] which listens for on-going activity on the
channel. On detection of legitimate activity, the jammer node immediately sends out a random
valid communication signals prevalent on the channel leading to collision.
The inference after comparing the above mentioned jamming attacks is that reactive jamming is a
that opposes secure communication in wireless sensor network. This
s the reactive jammer attack since it poses a critical threat to wireless sensor
reactive jammer nodes can disrupt the message delivery of its neighbouring
sensor nodes with strong interference signals. The consequences of the attack are the loss of link
d energy consumption, extended packet delays, and disruption of end
Fig 3: System Architecture
system architecture for defense against reactive jamming attack. The initial
description of the overall trigger identification service framework begins with the identification of
nodes are then grouped into several testing teams. Once the group
at the base station, the nodes themselves locally execute
each individual node as a trigger or non trigger. The identification outcomes
ally for use by routing schemes or can be sent to the base station for jamming
ational Journal of Security, Privacy and Trust Management ( IJSPTM) vol 2, No 2, April 2013
45
Figure 2 depicts several types of jammers that may be used in attacks against wireless sensor
reactive jammer. The
constant jammer [6] emits uninterrupted radio signals in the wireless medium. They do not follow
any underlying MAC protocol and include just random bits. This jammer keeps the channel busy
ammer [7] uses misleading
jamming techniques to attack the wireless sensor nodes. The random jammer [8] sleeps for an
indiscriminate time and wakes up to jam the network for an arbitrary time. The last jamming
going activity on the
channel. On detection of legitimate activity, the jammer node immediately sends out a random
prevalent on the channel leading to collision.
The inference after comparing the above mentioned jamming attacks is that reactive jamming is a
secure communication in wireless sensor network. This
ireless sensor
reactive jammer nodes can disrupt the message delivery of its neighbouring
sensor nodes with strong interference signals. The consequences of the attack are the loss of link
d energy consumption, extended packet delays, and disruption of end-to-end
for defense against reactive jamming attack. The initial
identification of
. Once the group
locally execute the testing
as a trigger or non trigger. The identification outcomes
base station for jamming
4. International Journal of Security, Privacy and Trust Management ( IJSPTM) vol 2, No 2, April 2013
localization process. The rest of the work is organized
model, and the attacker model along with jamming characteristics.
implementation approach for
Section 4 describes the performance evaluation
along with evaluation of the time taken to execute the testing rounds and also the message
complexity.
2. SYSTEM MODELS AND NOTATION
2.1. Network Model
The model considers a wireless sensor network
station. Each sensor node has omni
total of k channels throughout the network, where k>m.
is considered to be uniform, so the transmission
constant r and the network is modelled as a unit disk graph (UDG). w
said to be connected if the Euclidean
2.2. Attacker model
The jammer nodes can sense an ongoing transmission to decide whether
jamming signal depending on the power of the sensed
reactive jammers have omnidirectional antennas with uniform power strength on each direction
which is similar to the property of the sensors. The jammed area
lies on the centre of the network area, with a radius R, where jammer range
greater than the range of all the sensors in the network
jammer model. All the sensors within this range will be jammed during the jammer wake
period. The value of R can be calculated based on
victim nodes in the networks. Another assumption is that any two jammer nodes are not in close
range with each other so as to maximize the jammed area.
2.3. Sensor model
Fig 3: Categorization of Sensor Nodes
ational Journal of Security, Privacy and Trust Management ( IJSPTM) vol 2, No 2, April 2013
The rest of the work is organized as follows. Section 2 explains the network
model, and the attacker model along with jamming characteristics. Section 3
trigger identification service by making use of group testing
performance evaluation by analysis of the time complexity involved
along with evaluation of the time taken to execute the testing rounds and also the message
SYSTEM MODELS AND NOTATION
wireless sensor network that consists of n sensor nodes and one base
Each sensor node has omni-directional antennas, along with m radios that adds up to a
total of k channels throughout the network, where k>m. Here the power strength in each
to be uniform, so the transmission range of each sensor can be considered as
is modelled as a unit disk graph (UDG). where any node pair (
uclidean distance between (i, j) < r.
The jammer nodes can sense an ongoing transmission to decide whether or not
nding on the power of the sensed signal. The assumption made
have omnidirectional antennas with uniform power strength on each direction
property of the sensors. The jammed area created by the reactive jammers
on the centre of the network area, with a radius R, where jammer range R is r
greater than the range of all the sensors in the network in order to achieve a powerful and efficient
jammer model. All the sensors within this range will be jammed during the jammer wake
period. The value of R can be calculated based on the positions of the boundary sensors and
Another assumption is that any two jammer nodes are not in close
to maximize the jammed area.
Fig 3: Categorization of Sensor Nodes
ational Journal of Security, Privacy and Trust Management ( IJSPTM) vol 2, No 2, April 2013
46
explains the network
3 describes the
by making use of group testing.
by analysis of the time complexity involved
along with evaluation of the time taken to execute the testing rounds and also the message
consists of n sensor nodes and one base
directional antennas, along with m radios that adds up to a
power strength in each direction
range of each sensor can be considered as a
here any node pair ( i , j ) is
or not to launch a
assumption made here is that
have omnidirectional antennas with uniform power strength on each direction
y the reactive jammers
R is required to be
to achieve a powerful and efficient
jammer model. All the sensors within this range will be jammed during the jammer wake-up
the positions of the boundary sensors and
Another assumption is that any two jammer nodes are not in close
5. International Journal of Security, Privacy and Trust Management ( IJSPTM) vol 2, No 2, April 2013
The jamming status is utilised to categorise the sensor nodes into four types as shown in Figure
3.Trigger Node TN is a sensor node which awakes the jammers, victim nodes VN are those
within a distance R from an activated jammer, boundary nodes BN and un
from the effect of jammers.
3. IMPLEMENTATION APPROACH USING
IDENTIFICATION
Fig 4: Trigger identification procedure
Trigger identification service is mainly divided into three main steps
first step executes anomaly detection where the base station detects impending reactive jamming
attacks. Each boundary node identifies itself to the base station. In the second step jammer
property estimation is performed where the base station calculates
jamming range based on the location of boundary node. The third step is trigger detection where
the base station broadcasts a short testing schedule message M to all the boundary nodes
.Thereafter the boundary nodes keep broad
jammed area for a period P.Subsequently the victim nodes locally execute the testing procedure
based on M and identify themselves as trigger or nontrigger.
The non-adaptive Group Testing (GT)
sophisticatedly grouping and testing the items in pools
testing them. This way of groupin
represent the testing group and each column refers to an item. M[i , j ] = 1 implies that the j
participates in the ith testing group, and the number
each group is represented as an outcome
trigger in this testing group) and 1 is a positive result (possible triggers in the
achieve the minimum testing length for non
the union of any d columns does not contain any other column.
Step 1: Anomaly Detection
ational Journal of Security, Privacy and Trust Management ( IJSPTM) vol 2, No 2, April 2013
is utilised to categorise the sensor nodes into four types as shown in Figure
3.Trigger Node TN is a sensor node which awakes the jammers, victim nodes VN are those
within a distance R from an activated jammer, boundary nodes BN and unaffected nodes are free
IMPLEMENTATION APPROACH USING TRIGGER
Fig 4: Trigger identification procedure
Trigger identification service is mainly divided into three main steps as shown in Figure 4
first step executes anomaly detection where the base station detects impending reactive jamming
attacks. Each boundary node identifies itself to the base station. In the second step jammer
property estimation is performed where the base station calculates the estimated jammed area and
jamming range based on the location of boundary node. The third step is trigger detection where
the base station broadcasts a short testing schedule message M to all the boundary nodes
.Thereafter the boundary nodes keep broadcasting M to all the victim nodes within the estimated
jammed area for a period P.Subsequently the victim nodes locally execute the testing procedure
based on M and identify themselves as trigger or nontrigger.
adaptive Group Testing (GT) method can be used to minimize the testing
sophisticatedly grouping and testing the items in pools simultaneously, instead of individually
way of grouping is based on a 0-1 matrix Mt×n where the matrix rows
each column refers to an item. M[i , j ] = 1 implies that the j
testing group, and the number of testing is the number of rows. The result of
an outcome vector with size t where 0 is a negative testing result (no
nd 1 is a positive result (possible triggers in the testing
testing length for non-adaptive GT, M is required to be d-disj
s not contain any other column.
Fig 5: Status report message
ational Journal of Security, Privacy and Trust Management ( IJSPTM) vol 2, No 2, April 2013
47
is utilised to categorise the sensor nodes into four types as shown in Figure
3.Trigger Node TN is a sensor node which awakes the jammers, victim nodes VN are those
affected nodes are free
as shown in Figure 4. The
first step executes anomaly detection where the base station detects impending reactive jamming
attacks. Each boundary node identifies itself to the base station. In the second step jammer
the estimated jammed area and
jamming range based on the location of boundary node. The third step is trigger detection where
the base station broadcasts a short testing schedule message M to all the boundary nodes
casting M to all the victim nodes within the estimated
jammed area for a period P.Subsequently the victim nodes locally execute the testing procedure
an be used to minimize the testing period by
f individually
where the matrix rows
each column refers to an item. M[i , j ] = 1 implies that the jth
item
of testing is the number of rows. The result of
vector with size t where 0 is a negative testing result (no
testing group). To
disjunct, where
6. International Journal of Security, Privacy and Trust Management ( IJSPTM) vol 2, No 2, April 2013
Figure 5 shows the status report message having four tuples: Source_ID gives the ID of the sensor
nodes, Time stamp indicates the sequence number, Label gi
field indicates packet transmission time
In anomaly detection every sensor periodically sends a status report message to the base station.
There is a possibility that jammers
allow report messages from the compromised sensors to be received by the base station. The base
station can decide whether jamming attack has occurred in the network or not by comparing the
ratio of received report to a predefined threshold.
Step 2: Jammer Property Estimation
The jammed area and jamming range D will be calculated by the base station by considering the
location of boundary and victim nodes. In this work sparse
distribution of jammers is relatively sparse and there is no overlap between the jammer nodes. By
denoting the set of boundary nodes for the it
estimated as
(Xj,Yj)= {
Where (Xk ,Yk) is the coordinate of a node k is the jammed area BN
D= min{max( √(Xk-Xj)
Step 3:. Trigger Detection
The jammers immediately broadcast jamming signals once it senses the ongoing transmission by
the sensors. The jammers are identified by trigger identification service. He
schedule is adhered by all the victim nodes.
the set of boundary nodes and the global topology. Information with regard to topology is stored
as a message and broadcast to all bound
each boundary node broadcasts the message by using simple flooding method to its adjoining
jammed area. All victim nodes implement the testing schedule and specify themselves as trigger
or non-trigger node.
ational Journal of Security, Privacy and Trust Management ( IJSPTM) vol 2, No 2, April 2013
shows the status report message having four tuples: Source_ID gives the ID of the sensor
ates the sequence number, Label gives present jamming status,
field indicates packet transmission time and energy.
In anomaly detection every sensor periodically sends a status report message to the base station.
There is a possibility that jammers may be activated during this period .This occurrence will not
allow report messages from the compromised sensors to be received by the base station. The base
station can decide whether jamming attack has occurred in the network or not by comparing the
o of received report to a predefined threshold.
Step 2: Jammer Property Estimation
The jammed area and jamming range D will be calculated by the base station by considering the
location of boundary and victim nodes. In this work sparse-jamming is considered where the
distribution of jammers is relatively sparse and there is no overlap between the jammer nodes. By
denoting the set of boundary nodes for the ith jammed area as BNi, the jammer coordinate can be
}
) is the coordinate of a node k is the jammed area BNi and jamming range D is
Xj)2
+(Yk-Yj)2
)}
The jammers immediately broadcast jamming signals once it senses the ongoing transmission by
the sensors. The jammers are identified by trigger identification service. Here encrypted testing
schedule is adhered by all the victim nodes. Scheduling will be done at the base station based on
the set of boundary nodes and the global topology. Information with regard to topology is stored
as a message and broadcast to all boundary nodes. After receiving the test scheduling message,
each boundary node broadcasts the message by using simple flooding method to its adjoining
jammed area. All victim nodes implement the testing schedule and specify themselves as trigger
ational Journal of Security, Privacy and Trust Management ( IJSPTM) vol 2, No 2, April 2013
48
shows the status report message having four tuples: Source_ID gives the ID of the sensor
ves present jamming status, TTL
In anomaly detection every sensor periodically sends a status report message to the base station.
may be activated during this period .This occurrence will not
allow report messages from the compromised sensors to be received by the base station. The base
station can decide whether jamming attack has occurred in the network or not by comparing the
The jammed area and jamming range D will be calculated by the base station by considering the
considered where the
distribution of jammers is relatively sparse and there is no overlap between the jammer nodes. By
the jammer coordinate can be
(1)[20]
and jamming range D is
(2)[20]
The jammers immediately broadcast jamming signals once it senses the ongoing transmission by
re encrypted testing
Scheduling will be done at the base station based on
the set of boundary nodes and the global topology. Information with regard to topology is stored
test scheduling message,
each boundary node broadcasts the message by using simple flooding method to its adjoining
jammed area. All victim nodes implement the testing schedule and specify themselves as trigger
7. International Journal of Security, Privacy and Trust Management ( IJSPTM) vol 2, No 2, April 2013
49
As shown in algorithm above, the groups can decide to conduct group testing on themselves in m
pipelines. If any jamming signals occur in pipeline ,then the current test will be stopped and the
next test has to be scheduled. The groups receiving no jamming signals are required to resend
triggering messages and wait until the predefined round time has passed.
4. PERFORMANCE EVALUATION AND RESULT ANALYSIS
The results of these experiments show that this solution is time efficient for identifying trigger
nodes and defending reactive jamming attacks. The trigger identification procedure for reactive
jamming in network simulator NS2[21] on 900×900 square sensor field with n=10 sensor nodes
has been simulated. The sensor nodes are uniformly distributed, with one base station and J
Algorithm :Trigger Nodes Identification Algorithm
/*All nodes in a group N synchronously performs the following to recognize trigger nodes in
N.*/
INPUT: n victim nodes in a testing group
OUTPUT: all trigger nodes within these victim nodes
//In order to estimate d i.e. upper bound of error
Set γ=(10t- 8t2
- t-d
-1)/2;
//Likelihood for each test
Set T=t ln n(d+1)2
/(t- √(d+1))2
;
Construct a (d,z)- disjunct matrix using ETG algorithm with T rows, and divide all the n victim
nodes into T group accordingly {g1,g2,.....,gt};
// Group testing will be done for each round on m groups using m different channels. Here
testing can be done in asynchronous manner ,the m group tested in parallel need not wait for
each other to finish the testing, instead any finished test j will trigger the test j+m, i.e, the tests
are conducted in m pipelines.
for i= 1 to [t/m] do
Conduct group testing in group gim+1,gim+2,gim+m in parallel;
If any node in group gj with jЄ [im+1,im+m] detects jamming noises, finish the testing in this
group and start testing on gj+m;
If no nodes in group gj sense jamming noises, while at least one other test in parallel detects
jamming noises,
All the nodes in group gj resend more messages to set off possible hidden jammers;
If no jamming signals are detected till the end of the predefined round length (L)
Return a negative outcome for this group and start testing on gj+m;
End
8. International Journal of Security, Privacy and Trust Management ( IJSPTM) vol 2, No 2, April 2013
50
distributed jammer nodes. In this work ,the sensor transmission radius r and jamming
transmission R as 2r has been considered to achieve better efficiency of the jamming model.
Fig 6: Simulation of reactive jamming
Figure6 shows a network simulated with 10 sensor node with 1 malicious node and 1 base station.
The transmission range(r) of ordinary sensor node is set as 50m while jammer transmission
range(R) set to 100m(2r).
Fig 7: The number of testing rounds t(sec)
Figure7 explains the protocol performance based on the variation in the numbers of jammers J in
the network. In this test,N = 10 nodes with m = 3 radios, on a 900×900 network field have been
considered where J ∈ [1, 5] jammers are uniformly deployed. Group testing employs a
sophisticated technique to perform as many parallel tests as possible so that the estimated
number of testing rounds T(sec) can be stable even though the number of jammers J increase.
9. International Journal of Security, Privacy and Trust Management ( IJSPTM) vol 2, No 2, April 2013
51
Fig 8: Time Complexity.
In order to show that the trigger identification service for reactive jamming attack is more
efficient, group testing has been performed on different groups simultaneously for detecting the
trigger node. With this reduction in time complexity can be demonstrated.Figure8 shows that
time complexity can be reduced as the number of victim nodes that execute testing procedure in
the group increase.
Fig 9: Message Complexity.
This work considers simple status message transfers between the sensor node and base station
that can provide reduction in message complexity as compared to AODV(Ad hoc On-Demand
Distance Vector) which makes use of unnecessary bandwidth consumption due to periodic
beaconing that leads to message overhead. Figure9 shows that message complexity is reduced in
the case of implementation of the trigger identification service.
5. RELATED WORK
One of the reactive countermeasures uses Adapted Breadth-First Search Tree algorithm for
identification of jammer node[13]. Here the base station broadcasts a message to all n nodes
along a BFS tree. Once a node receives this message, it will set its corresponding entry to one. If
the node senses that any one of the channels is jammed, another normal channel is used to
transmit the broadcast message. The base station will receive a collection of messages from all
0
5
10
15
20
25
30
AODV STATUS REPORT
10. International Journal of Security, Privacy and Trust Management ( IJSPTM) vol 2, No 2, April 2013
52
leaf nodes. In this case, the number of ACKs from the leaf nodes leads to overhead in base
station.
Another approach for the detection and mapping of jammed area [14] has been proposed by
Wood and Stankovic to increase network efficiency. However, this method has several
drawbacks: first, it cannot practically defend in the situation that the attacker jams the entire
network; second, in case the attacker targets some specific nodes i.e. those that guard a security
entrance to obstruct their data transmission, then this technique fails to protect the nodes under
attack.
Xu [15] proposed two strategies against jammers i.e, channel surfing and spatial retreat. Channel
surfing is adaptive form of FHSS. Instead of switching continuously from one channel to another,
a node switches to a channel only when it discovers that the current channel is free from jammer.
The spatial retreat method makes two nodes to move in diverse ways with separation atleast equal
to Manhattan distances [16] to get away from a jammed region. The disadvantages of the above
mentioned methods are that they are valuable only for constant jammers and they have no effect
on reactive jamming.
The concept of Wormhole [17] can be used to bypass the jammed areas which disturb the regular
communication of the sensor nodes. These solutions can only effectively reduce the intensity of
the jamming attacks, but their performance depends on the accuracy of detection of the jammed
areas, i.e. transmission overhead would be needlessly involved if the jammed area is much larger
than its actual size. Victim nodes cannot efficiently avoid jamming signals because they do not
possess knowledge over possible positions of hidden reactive jammer nodes, especially in dense
sensor networks
This paper proposes a fresh implementation move towards defence of the network against
reactive jamming attack i.e. trigger identification service [18-19]. This can be considered as a
lightweight mechanism because all the calculations are done at the base station. This approach
attempts to reduce the transmission overhead as well as the time complexity. The advantage that
this approach seeks to achieve is the elimination of additional hardware requirement. The
requirement of the mechanism is to send simple status report messages from each sensor and the
information regarding the geographic locations of all sensors maintained at the base station.
6. CONCLUSION
In this paper, a novel trigger identification service for reactive jamming attack in wireless sensor
network is introduced to achieve minimum time and message overhead. The status report
message are transferred between the base station and all sensor nodes . For isolating reactive
jammer in the network a trigger identification service is introduced, which requires all testing
groups to schedule the trigger node detection algorithm using group testing after anomaly
detection. By identifying the trigger nodes in the network, reactive jammers can be eliminated by
making trigger nodes as only receivers. This detection scheme is thus well-suited for the
protection of the sensor network against the reactive jammer. Furthermore, investigation into
more stealthy and energy efficient jamming models with simulations indicates robustness of the
present proposed scheme. The result can be stored in the network for further operations i.e. to
11. International Journal of Security, Privacy and Trust Management ( IJSPTM) vol 2, No 2, April 2013
53
perform best routing operation without jamming. This work achieves the elimination of attackers
to maintain the soundness of wireless sensor networks.
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Authors
Miss Ramya Shivanagu received her Bachelor of Engineering in Information Science
and engineering in 2010. Currently She is a M.Tech student in Computer Networking
Engineering from Visvesvaraya Technological University at The Oxford College of
Engineering, Bangalore. Her research interests are wireless sensor networks, Network
Security.
Mrs Deepti C received her Bachelor of Engineering in Electronics and Communication
in 2004. She received her M.Tech in Computer Network Engineering with distinction
from Visvesvaraya Technological University in 2009. Currently she also holds a faculty
position as Assistant Professor, Department of ISE, The Oxford College of Engineering.
Her main research interests are signal processing, wireless sensor networks, wireless
network security .