Abstract：
:Due to lack of a central bureaucrat in mobile ad hoc networks, the security of the network becomes serious issue. During malicious attacks, according to the motivation of intruder the severity of the threat varies. It may lead to loss of data, energy or throughput. This paper proposes a lightweight Intruder Node Detection and Isolation Action mechanism (INDIA) using feature extraction, feature optimization and classification techniques. The indirect and direct trust features are extracted from each node and the total trust feature is computed by combining them. The trust features are extracted from each node of MANET and these features are optimized using Particle Swarm Optimization (PSO) algorithm as feature optimization technique. These optimized feature sets are then classified using Neural Networks (NN) classifier which identifies the intruder node. The performance of the proposed methodology is studied in terms of various parameters such as success rate in packet delivery, delay in communication and the amount of energy consumption for identifying and isolating the intruder.
journal_name
J Med Systjournal_title
Journal of medical systemsauthors
Kavitha T,Geetha K,Muthaiah Rdoi
10.1007/s10916-019-1309-2subject
Has Abstractpub_date
2019-05-10 00:00:00pages
179issue
6eissn
0148-5598issn
1573-689Xpii
10.1007/s10916-019-1309-2journal_volume
43pub_type
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