Channel Surfing to protect Reactive Jammers in WSN by Identifying the InitiatorDone By:1.M.Divya(21309104019)2.K.Kavitha(21309104035)3.B.Monica(21309104047)

Abstract:• During the last decade, Reactive Jamming Attack has

emerged as a great security threat to wireless sensor networks, due to its mass destruction to legitimate sensor communications and difficulty to be disclosed and defended.

• Considering the specific characteristics of reactive jammer nodes, a new scheme to deactivate them by efficiently identifying all trigger nodes, whose transmissions invoke the jammer nodes, has been proposed and developed.

• Such a trigger-identification procedure can work as an application-layer service and benefit many existing reactive-jamming defending schemes.

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• In this paper, on the one hand, we leverage several optimization problems to provide a complete trigger-identification service framework for unreliable wireless sensor networks.

• On the other hand, we provide an improved algorithm with regard to two sophisticated jamming models, in order to enhance its robustness for various network scenarios.

• Theoretical analysis and simulation results are included to validate the performance of this framework.

Existing System:

•Since last decade, the security of wireless sensor networks (WSNs) has attracted numerous attentions, due to its wide applications in various monitoring systems and vulnerability toward sophisticated wireless attacks.

•Among these attacks, jamming attack where a jammer node disrupts the message delivery of its neighboring sensor nodes with interference signals, has become a critical threat to WSNs.

Disadvantages:

•Entire network can be destroyed.•Data transmission failure may affect the

process.•Communication Channel could be

blocked.•Reactive jammers can block the signal

and also disconnect the link between source and destination.

Proposed System:

•we present an application-layer real-time trigger-identification service for reactive-jamming in wireless sensor networks, which promptly provides the list of trigger-nodes using a lightweight decentralized algorithm, without introducing neither new hardware devices, nor significant message overhead at each sensor node.

• Our proposed system will exclude the set of trigger nodes from the routing paths, so that reactive jammers will have to stay idle since transmissions cannot be sensed.

• Even though the jammers move around and detect new sensor signals, the list of trigger nodes will be quickly updated, so are the routing tables. As another example, without prior knowledge of the number of jammers, the radius of jamming signals and specific jamming behavior types, it is quite hard to locate the Reactive jammers even the jammed areas are detected.

• However, with the trigger nodes localized, we can narrow down the possible locations of reactive jammers. Although the benefits of this trigger-identification service are exciting, its hardness is also obvious, which dues to the efficiency requirements of identifying the set of trigger nodes out of a much large set of victim nodes, that are affected jamming signals from reactive jammers with possibly various sophisticated behaviors.

• To address these problems, a novel randomized error-tolerant group testing scheme as well as minimum disk cover for polygons is proposed and leveraged.

Our proposed system will exclude the set of trigger nodes from the routing paths, so that reactive jammers will have to stay idle since transmissions cannot be sensed. Even though the jammers move around and detect new sensor signals, the list of trigger nodes will be quickly updated, so are the routing tables. As another example, without prior knowledge of the number of jammers, the radius of jamming signals and specific jamming behavior types, it is quite hard to locate the Reactive jammers even the jammed areas are detected. However, with the trigger nodes localized, we can narrow down the possible locations of reactive jammers. Although the benefits of this trigger-identification service are exciting, its hardness is also obvious, which dues to the efficiency requirements of identifying the set of trigger nodes out of a much large set of victim nodes, that are affected jamming signals from reactive jammers with possibly various sophisticated behaviors. To address these problems, a novel randomized error-tolerant group testing scheme as well as minimum disk cover for polygons is proposed and leveraged.

Advantages:

•Successful data transmission can be achieved.

•Communication channel can’t be blocked.•Reactive jammers can’t destroy the

communication channel as well as the network.

•Trigger nodes can be efficiently detected and controlled or blocked.

System Requirements:

•Software Requirements: 1.visual studio 2010 2.sql server 2005

Architecture diagram:

Modules:• Design of network• Aggressor Module

▫ Basic attacker ▫ Advanced attacker

• Sensing element module• Three kernel techniques

▫ Error-Tolerant Randomized Non-adaptive group testing▫ Minimum disk cover in a simple polygon▫ Clique-Independent Set

• Trigger-node recognition▫ Anomaly detection▫ Jammer property estimation▫ Trigger Detection

• Channel Surfing

DESIGN OF NETWORK:• We design a sensor network consisting of n

sensor nodes and one base station. • Larger sensor network can have multiple base

stations. Each sensor node will be equipped with globally synchronized time clock is one of the most important thing for data transmission.

• Among multiple nodes one node will be chosen as a sender and another one node will chosen as receiver. Sender will transmit data to receiver using intermediate nodes or senor nodes.

AGGRESSOR MODULE:

•Aggressor module describes types of attacker models which includes basic attacker and several advanced attackers.

• In our system attackers are nothing but jammers. Specifically, we provide a solution framework toward the basic attacker model, and validate its performance toward multiple advanced attacker models experimentally.

SENSING ELEMENT MODULE:

•all the sensor nodes can be categorized into four classes: trigger nodes TN, victim nodes VN, boundary nodes BN, and unaffected node UN.

•Trigger nodes refer to the sensor nodes whose signals awake the jammers, i.e., within a distance less than r from a jammer. Victim nodes are those within a distance R from an activated jammer and disturbed by the jamming signals.

THREE KERNEL TECHNIQUES:

• The key idea of group testing is to test items in multiple designated groups, instead of individually. In order to handle errors in the testing outcomes, the error-tolerant non-adaptive group testing has been developed in which groups are formed based on matrix.Nodes will be grouped by forming the matrix and nodes within that will be tested.

• Simple polygon will contain set of vertices inside, the problem of finding a minimum number of variable-radii disks that not only cover all the given vertices, but also are all within the polygon is minimum disk-cover.

• Clique-Independent Set method will find a set of pair-wise vertex-disjoint maximal set, which is referred to as a maximum clique-independent set.

 

TRIGGER-NODE RECOGNITION:

• Our proposed algorithm lightweight decentralized trigger-identification is the major process in which no extra hardware device will be used except for the simple sample report messages sent by each sensor, and the geographic locations of all sensor maintained at base stations. And also in our system all calculations will be done by base station.

• Anomaly detection• Jammer property estimation• Trigger Identification

CHANNEL SURFING:• In this module we are enhancing our system to avoid the jamming

attacks by including channel surfing technique. To protect the healthy nodes from attacked nodes, healthy nodes are required to change their communication channel more frequently.

• By this those nodes can’t be attacked by trigger nodes. Every node will change its communication once the transmission is successfully completed.

• Normal channel surfing concept is to migrate to another communication channel when specific communication channel is being attacked by anomalies.

• In this case there is a possibility for channel to be controlled by the hacker. To overcome this problem our methodology changes the communication channel as soon as the transmission is completed. So that node will be protected from getting attacked.

Running nodes while base station is unavailable:

Base Station initial level:

Node act as sender:

References:•W. Xu, K. Ma, W. Trappe, and Y. Zhang,

“Jamming Sensor Networks: Attack and Defense Strategies,” IEEE Network, May/June, pp. 41-47, 2006.

•  •L. Karlsson, “System and Method to

Autonomously and Selectively Jam Frequency Hopping Signals in Near Real-Time,” U. S. Patent 7,126,979, 24 Oct., 2006.

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