FUTURE OF CYBER DEFENSE: SELF-LEARNING NEURAL CYBER IMMUNITY HOW AI AND BIOLOGICAL IMMUNITY ARE TRANSFORMING ADVANCED THREAT LANDSCAPES

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Authors: Jouma Ali Al-Mohamad, Dr.Eng. Jamila Shaaban Ebrahim
Cited by: 0

Abstract

This article explores the transformative concept of Self-Learning Neural Cyber Immunity (SLNCI), a next-generation cybersecurity paradigm that merges artificial intelligence with biological immunity principles to create adaptive, autonomous defense systems. SLNCI moves beyond traditional signature-based detection, offering continuous learning and real-time adaptation against advanced persistent threats (APTs) and zero-day vulnerabilities. The article details the architectural components, learning mechanisms, and wide-ranging applications of SLNCI, while addressing implementation challenges and ethical considerations. By integrating neural networks with artificial immune systems (AIS), SLNCI represents a fundamental shift toward proactive, resilient cyber defense infrastructures capable of evolving alongside emerging threats.

Fields of Study & Subjects

Artificial Immune Systems Applications Network Security and Intrusion Detection Network Packet Processing and Optimization

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
7 February 2026