Natural Killer Cells in Intrusion Detection: A CIS-Based Approach for Improving Detection Accuracy

Intrusion detection system (IDS) is utilized to screen network to distinguish inconsistencies and assaults with the goal to safeguard confidentiality, integrity, and availability(CIA) of data. Natural Killer (NK) cells are used to create a Cyber Immune System (CIS)-based IDS framework in this paper. CIS is the idea of utilizing Artificial Immune System (AIS) in IDS. Inconsistent NK cells are made and Negative Determination Calculation is used to discard self-perceiving cells. High wellbeing NK cells are multiplied on to the organization utilizing Clonal Determination Calculation. In this method, a number of Light NK cells (LNK) and a single Heavy NK cell (HNK) are used. Anomalies can be detected with the help of LNK, which is made by the NSA, and normality can be checked with HNK. There are two kinds of LNK used: memory NK (MNK), which stays in the system, and cloned NK (CNK), which grows or goes away based on its health benefits. The methodology is evaluated utilizing NSL KDD 99 dataset and results show that the methodology has superior exactness, high location rate, low phony problem rate and speedy reaction time.

• Publication year

  2025

• Venue

  2025 3rd International Conference on Communication, Security, and Artificial Intelligence (ICCSAI)

• Publication date

  2025-04-04

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1109/ICCSAI64074.2025.11064549
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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