Enhanced AIS Based Intrusion Detection System Using Natural Killer Cells
subject: AIS; anomaly detection; IDS; Intrusion; natural killer cells
description: Intrusion detection system is used to monitor the system and network activities to identify anomalies and attacks so that integrity, availability, and confidentiality can be preserved. Here an intrusion detection system based on Artificial Immune System is proposed based on Natural Killer (NK) cells with immunological memory. NK cells are created and each NK cells detection radius is determined using the negative selection algorithm and is trained to detect various attacks. Effective cells with high fairness values are proliferated and distributed to the network using clonal selection algorithm. In this paper, two types of NK cell are used-a Heavyweight NK cell (HWNK) and a number of Lightweight NK cells (LWNK). The incoming data is vectorized and Major Histocompatibility Complex Class I (MHC1) is created. Then based on this MHC1, any of the receptors i.e. Activating Receptor or Inhibiting Receptor is activated. If it is the signature of an attack, Activating Receptor is activated. Activating receptor activation results in either cytokine release or apoptosis. Here cytokine release means an alarm is generated informing the administrator and apoptosis stands for dropping of the packet. If Inhibiting Receptor is activated, it's a normal packet there is no action taken. The technique proposed yields high accuracy, better detection rate and quick response time. 2020 River Publishers. All Rights Reserved.
creator: Bejoy B.J.; Janakiraman S.
source: Journal of Cyber Security and Mobility, Vol-9, No. 4, pp. 515-534.
publisher: River Publishers
date: 2020-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 22451439
format: Online
language: English
type: Article
coverage: Bejoy B.J., Department of CSE, Christ (Deemed to be University), India; Janakiraman S., Department of Banking Technology, Pondicherry University, India