A Lightweight Signature-Based IDS for IoT Environment

TL;DR

This paper presents a lightweight, pattern recognition-based intrusion detection system tailored for resource-constrained IoT environments, demonstrating effective attack detection using optimized algorithms and NSL KDD dataset results.

Contribution

It introduces a novel IDS architecture for IoT that employs an optimized pattern recognition algorithm to improve security while maintaining low resource consumption.

Findings

Effective attack detection demonstrated on NSL KDD dataset

Low resource usage suitable for IoT devices

Improved security against network intrusions

Abstract

With the advent of large-scale heterogeneous networks comes the problem of unified network control resulting in security lapses that could have otherwise avoided. A mechanism is needed to detect and deflect intruders to safeguard resource constraint edge devices and networks as well. In this paper we demonstrate the use of an optimized pattern recognition algorithm to detect such attacks. Furthermore, we propose an Intrusion Detection System (IDS) methodology and design architecture for Internet of Things that makes the use of this search algorithm to thwart various security breaches. Numerical results are presented from tests conducted with the aid of NSL KDD cup dataset showing the efficacy the IDS