Download PDFOpen PDF in browser

Memory Requirements for the Detection of Impostor Nodes in Wireless Sensor Networks

12 pagesPublished: July 18, 2022

Abstract

This paper shows how it is at least in principle possible to detect impostor nodes in wireless sensor networks with a quite simplistic detection algorithm by purely statistical means and merely from external observation without any knowledge of the impostor’s inter- nal composition. This method, however, requires considerable volumes of internal memory for any WSN node on which such detection algorithms are supposed to be implemented.
Keywords: Wireless Sensor Networks · WSN Reliability · WSN Integrity · WSN Safety and Security · WSN Trustworthiness · Node Replication Attacks · Intrusion Detection · Probabilistic Finite Automata · Randomised Detection Algorithm · Detection Accuracy · Memory Requirements

Keyphrases: - Randomised Detection Algorithm, - WSN Integrity, - WSN Safety and Security, - WSN Trustworthiness, detection accuracy, Intrusion Detection, memory requirements, Node Replication Attacks, probabilistic finite automata, Wireless Sensor Networks, WSN reliability

In: Aurona Gerber (editor). Proceedings of 43rd Conference of the South African Institute of Computer Scientists and Information Technologists, vol 85, pages 36--47

Links:
BibTeX entry
@inproceedings{SAICSIT2022:Memory_Requirements_for_Detection,
  author    = {Stefan Gruner and Dylan Krajnc and Johan Pieter van Rooyen},
  title     = {Memory Requirements for the Detection of Impostor Nodes in Wireless Sensor Networks},
  booktitle = {Proceedings of 43rd Conference of the South African Institute of Computer Scientists and Information Technologists},
  editor    = {Aurona Gerber},
  series    = {EPiC Series in Computing},
  volume    = {85},
  pages     = {36--47},
  year      = {2022},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {https://easychair.org/publications/paper/CTn5},
  doi       = {10.29007/8ds7}}
Download PDFOpen PDF in browser