A Study on the Adaptability of Immune models for Wireless Sensor Network Security | Zendy

Vishwa Alaparthy | Zendy; Amar Amouri | Zendy; S.D. Morgera | Zendy

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A Study on the Adaptability of Immune models for Wireless Sensor Network Security

Author(s) -

Vishwa Alaparthy,

Amar Amouri,

S.D. Morgera

Publication year - 2018

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2018.11.003

Subject(s) - computer science , adaptability , intrusion detection system , artificial immune system , wireless sensor network , selection (genetic algorithm) , field (mathematics) , artificial neural network , computer security , wireless , artificial intelligence , machine learning , computer network , telecommunications , ecology , biology , mathematics , pure mathematics

Researchers in the field of artificial cognitive systems have persistently tried to adopt mechanisms and paradigms deployed in biological systems. Artificial neural network is one of the early examples adopting brain cell architecture and its computational practices. Similarly, Human Immune System (HIS) can be adopted for intrusion detection systems (IDS). The HIS recognizes and tries to eliminate external entities such as bacteria and viruses and works towards defending it from such threats. Detection and prevention mechanisms from HIS has been studied and adopted for Wireless Sensor Networks (WSN). Three well known techniques in the field of HIS-based IDS are studied and their adaptability to WSN’s is reported. These techniques include prominent immune models such as Negative Selection, Positive Selection, Danger Theory and Clonal Selection.

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