This document proposes a trigger identification service to identify sensor nodes that trigger reactive jamming attacks in wireless sensor networks. The service uses a decentralized algorithm to efficiently provide a list of trigger nodes without adding new hardware or significant message overhead. It considers various jammer and network models. Theoretical analysis and simulations validate that the framework can identify trigger nodes and help defend against reactive jamming attacks in unreliable wireless sensor networks.

1. A Trigger Identification Service for Defending Reactive
Jammers in Wireless Sensor Network
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. 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:
Reactive Jamming Attack has emerged as a great security threat to wireless sensor
networks, due to its mass destruction to legitimate sensor communications and

2. difficulty to be disclosed and defended. Among the various 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.
PROPOSED SYSTEM:
We present a simulation based 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.
MODULES:
 Network Model
 Attacker Model
 Jamming range
 Triggering range
 Jammer distance
MODULES DESCRIPTION:
Network Model

3. We consider a wireless sensor network consisting of n sensor nodes and one base
station (larger networks with multiple base stations can be split into small ones to
satisfy the model). Each sensor node is equipped with a globally synchronized time
clock, omnidirectional antennas, m radios for in total k channels throughout the
network, where k > m. For simplicity, the power strength in each direction is
assumed to be uniform, so the transmission range of each sensor can be abstracted
as a constant rs and the whole network as a unit disk graph (UDG) G ¼ ðV ;EÞ,
where any node pair i; j is connected iff the Euclidean distance between i; j: _ði; jÞ
_ rs. We leave asymmetric powers and polygonal transmission area for further
study.
Attacker Model
We consider both a basic attacker model and several advanced attacker models in
this paper. Specifically, we provide a solution framework toward the basic attacker
model, and validate its performance toward multiple advanced attacker models
theoretically and experimentally
Jamming range
R. Similar to the sensors, the jammers are equipped with omnidirectional antennas
with uniform power strength on each direction. The jammed area can be regarded
as a circle centered at the jammer node, with a radius R, where R is assumed
greater than rs, for simulating a powerful and efficient jammer node. All the

4. sensors within this range will be jammed during the jammer wake-up period. The
value of R can be approximated based on the positions of the boundary sensors
(whose neighbors are jammed but themselves not), and then further refined.
Triggering range
On sensing an ongoing transmission, the decision whether or not to launch a
jamming signal depends on the power of the sensor signal Ps, the arrived signal
power at the jammer Pa with distance r from the sensor, and the power of the
background noise Pn.
Jammer distance
Any two jammer nodes are assumed not to be too close to each other, i.e., the
distance between jammer J1 and J2 is _ðJ1; J2Þ > R. The motivations behind this
assumptions are three-fold: 1) the deployment of jammers should maximize the
jammed areas with a limited number of jammers, therefore large overlapping
between jammed areas of different jammers lowers down the attack efficiency; 2)
_ðJ1; J2Þ should be greater than R, since the transmission signals from one
jammer should not interfere the signal reception at the other jammer. Otherwise,
the latter jammer will not able to correctly detect any sensor transmission signals,
since they are accompanied with high RF noises, unless the jammer spends a lot of

5. efforts in denoising or embeds jammer-label in the jamming noise for the other
jammers to recognize. Both ways are infeasible for an efficient attack; 3) the
communications between jammers are impractical, which will expose the jammers
to anomaly detections at the network authority.
SYSTEM REQUIREMENTS:
HARDWARE REQUIREMENTS:
• System : Pentium IV 2.4 GHz.
• Hard Disk : 40 GB.
• Floppy Drive : 1.44 Mb.
• Monitor : 15 VGA Colour.
• Mouse : Logitech.
• Ram : 512 Mb.
SOFTWARE REQUIREMENTS:
• Operating system : - Windows XP.
• Coding Language : JAVA

6. REFERENCE:
Ying Xuan, Yilin Shen, Nam P. Nguyen, and My T. Thai, “A Trigger
Identification Service for Defending Reactive Jammers in WSN”, IEEE
TRANSACTIONS ON MOBILE COMPUTING, VOL. 11, NO. 5, MAY 2012