A Self-Adaptive Network Protection System

TL;DR

This paper proposes a self-adaptive network security system that uses fuzzy logic and biologically inspired algorithms to automatically detect and prevent security threats, enhancing network defense capabilities.

Contribution

It introduces a novel hybrid approach combining soft computing techniques for automated threat discovery and prevention in network security.

Findings

Demonstrates effectiveness of fuzzy logic in threat detection

Shows biological algorithms improve prevention accuracy

Achieves adaptive security responses in network environments

Abstract

In this treatise we aim to build a hybrid network automated (self-adaptive) security threats discovery and prevention system; by using unconventional techniques and methods, including fuzzy logic and biological inspired algorithms under the context of soft computing.