LGTBIDS: Layer-wise Graph Theory Based Intrusion Detection System in Beyond 5G

TL;DR

This paper introduces LGTBIDS, a graph theory-based intrusion detection system for beyond 5G networks that detects attacked nodes by analyzing energy efficiency and secrecy rate across network layers.

Contribution

It proposes a novel layer-wise graph theory framework for intrusion detection, focusing on energy efficiency and secrecy rate thresholds to identify vulnerable nodes.

Findings

Better performance than conventional methods

Low computational time and complexity

Effective detection of attacked nodes

Abstract

The advancement in wireless communication technologies is becoming more demanding and pervasive. One of the fundamental parameters that limit the efficiency of the network are the security challenges. The communication network is vulnerable to security attacks such as spoofing attacks and signal strength attacks. Intrusion detection signifies a central approach to ensuring the security of the communication network. In this paper, an Intrusion Detection System based on the framework of graph theory is proposed. A Layerwise Graph Theory-Based Intrusion Detection System (LGTBIDS) algorithm is designed to detect the attacked node. The algorithm performs the layer-wise analysis to extract the vulnerable nodes and ultimately the attacked node(s). For each layer, every node is scanned for the possibility of susceptible node(s). The strategy of the IDS is based on the analysis of energy efficiency and secrecy rate. The nodes with the energy efficiency and secrecy rate beyond the range of upper and lower thresholds are detected as the nodes under attack. Further, detected node(s) are transmitted with a random sequence of bits followed by the process of re-authentication. The obtained results validate the better performance, low time computations, and low complexity. Finally, the proposed approach is compared with the conventional solution of intrusion detection.