mlsanityData to 14 Oct 2026

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

arXiv 2210.03518 ↗First posted 6 Oct 2022cs.CR cs.LGcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 31 references that are in the map. First posted on arXiv 6 Oct 2022.

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6 of 31 references.

References · 6

  1. 2018Active Learning for Wireless IoT Intrusion Detectioncited by 19
  2. 2018AI-based Two-Stage Intrusion Detection for Software Defined IoT Networkscited by 5
  3. 2022Prediction and Detection of FDIA and DDoS Attacks in 5G Enabled IoTcited by 2
  4. 2021A Survey on Security Issues of 5G NR: Perspective of Artificial Dust and Artificial Raincited by 1
  5. 2021AR Based Half-Duplex Attack in Beyond 5G networkscited by 1
  6. 2022Behavioral Model For Live Detection of Apps Based Attackcited by 1

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