The distributed web architectures of today are threatened by highly advanced vulnerabilities due to fast-paced polymorphic Layer7 (L7) DDoS attacks, carried out by nation-states as well as decentralized botnets. Traditional cyber defense techniques relying on static WAF rules, IP-based rate limiting, and manual security operations can be circumvented easily by attackers using distributed residential proxy networks and HTTP header manipulation. In this paper, we introduce Adaptive Intelligence Offense Neutralization (AION), an autonomous and self-healing cybersecurity architecture in the form of a high throughput digital immune system. AION utilizes line-speed kernel-level eBPF/XDP traffic analysis, unsupervised behavioral baselining, and Deep Reinforcement Learning (DRL) to construct filtering policies in sub-millisecond granularity in an automated manner. We evaluate AION in experiments based on a real-world 85 million requests polymorphic L7 attack launched against critical sovereign infrastructure such as airports, municipal utilities, and ID backends. Our experiments show that AION can achieve 99.98% of malicious request neutralization, inline inspection latency less than 0.42 ms, no collateral false positives, and automated rule lifecycle recovery.

Iftekhar Ahmed Shakib,"A Review on Pore Geometry and Connectivity as Controls on Seismic Response in Hydrocarbon Reservoirs" International Journal of Advanced Multidisciplinary Research and Educational Development, V2(5): Page(95-110) September - October 2026. ISSN: 3107-6513. www.ijamred.com. Published by Scientific and Academic Research Publishing.