TY - GEN
T1 - Artificial intelligence-based technique for intrusion detection in wireless sensor networks
AU - Kalnoor, Gauri
AU - Agarkhed, Jayashree
N1 - Publisher Copyright:
© Springer Nature Singapore Pte Ltd. 2017.
PY - 2017
Y1 - 2017
N2 - Network with large number of sensor nodes distributed spatially is termed as Wireless Sensor Network (WSN). The tiny devices called as sensor nodes are cheap, consume less power, and the capabilities of computation is limited. The most challenging issue for WSN is protecting the network from misbehavior of intruders or adversaries. One of the major techniques used to prevent from any type of attack in the sensor network is artificial intelligence system (AIS). Intrusion Detection System (IDS) is considered to be the second line of defense, as sensor nodes are first defense line. WSNs are highly vulnerable to intrusions and different types of attacks. In most critical applications of WSN, the human intervention or some physical devices are not sufficient for protecting the network from strong adversaries and attacks. Thus, artificial intelligence techniques are used for intrusion detection and prevention of sensor networks.
AB - Network with large number of sensor nodes distributed spatially is termed as Wireless Sensor Network (WSN). The tiny devices called as sensor nodes are cheap, consume less power, and the capabilities of computation is limited. The most challenging issue for WSN is protecting the network from misbehavior of intruders or adversaries. One of the major techniques used to prevent from any type of attack in the sensor network is artificial intelligence system (AIS). Intrusion Detection System (IDS) is considered to be the second line of defense, as sensor nodes are first defense line. WSNs are highly vulnerable to intrusions and different types of attacks. In most critical applications of WSN, the human intervention or some physical devices are not sufficient for protecting the network from strong adversaries and attacks. Thus, artificial intelligence techniques are used for intrusion detection and prevention of sensor networks.
UR - https://www.scopus.com/pages/publications/85027140623
UR - https://www.scopus.com/inward/citedby.url?scp=85027140623&partnerID=8YFLogxK
U2 - 10.1007/978-981-10-3174-8_69
DO - 10.1007/978-981-10-3174-8_69
M3 - Conference contribution
AN - SCOPUS:85027140623
SN - 9789811031731
T3 - Advances in Intelligent Systems and Computing
SP - 835
EP - 845
BT - Artificial Intelligence and Evolutionary Computations in Engineering Systems - Proceedings of ICAIECES 2016
A2 - Das, Swagatam
A2 - Panigrahi, Bijaya Ketan
A2 - Dash, Subhransu Sekhar
A2 - Vijayakumar, K.
PB - Springer Verlag
T2 - International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems, ICAIECES 2016
Y2 - 19 May 2016 through 21 May 2016
ER -