Soft Computing - A step towards building Secure Cognitive WLAN

TL;DR

This paper proposes a soft computing-based framework for enhancing security in cognitive WLANs by using neural networks and access control mechanisms to detect unauthorized access and protect network integrity.

Contribution

It introduces a novel Cognitive Framework Architecture with a Cognitive Security Manager that employs neural networks and PADL for improved WLAN security.

Findings

Neural networks effectively identify unauthorized access patterns.

The CFA enhances WLAN security against dense network threats.

The framework integrates soft computing for dynamic security management.

Abstract

Wireless Networks rendering varied services has not only become the order of the day but the demand of a large pool of customers as well. Thus, security of wireless networks has become a very essential design criterion. This paper describes our research work focused towards creating secure cognitive wireless local area networks using soft computing approaches. The present dense Wireless Local Area Networks (WLAN) pose a huge threat to network integrity and are vulnerable to attacks. In this paper we propose a secure Cognitive Framework Architecture (CFA). The Cognitive Security Manager (CSM) is the heart of CFA. The CSM incorporates access control using Physical Architecture Description Layer (PADL) and analyzes the operational matrices of the terminals using multi layer neural networks, acting accordingly to identify authorized access and unauthorized usage patterns.