Abstract

This article explores the transformative concept of SelfLearning Neural Cyber Immunity (SLNCI), a nextgeneration 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.