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This paper offers a comprehensive survey of Machine Learning (ML) utilization in Intrusion Detection Systems (IDS) for Wireless Sensor Networks (WSNs). Given the widespread applications of WSNs and the need to safeguard sensitive data, this survey delves into the foundational aspects of WSNs, IDS, and ML, highlighting their interconnectedness. It provides insights into the latest advancements in IDS for WSNs, focusing on ML-based methodologies. Various ML algorithms are discussed in detail, elucidating their strengths, weaknesses, and relevance in IDS for WSNs. Furthermore, the survey conducts a comparative analysis of different ML-based IDS approaches, using diverse evaluation metrics. Ultimately, it concludes by pinpointing research challenges and future directions aimed at enhancing the efficacy of IDS for WSNs. The survey's overarching goal is to furnish an exhaustive assessment of approaches designed to bolster security in wireless remote networks (WSNs), exploring the factors influencing their implementation and adoption.

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An Analysis of ML-Based Intelligent IDS for Wireless Sensor Networks

  • 会议论文

  • 发表日期：

    2025年

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  • Sumedh Gangadhar Dhengre,
  • Shabnam Farook Sayyad

摘要

This paper offers a comprehensive survey of Machine Learning (ML) utilization in Intrusion Detection Systems (IDS) for Wireless Sensor Networks (WSNs). Given the widespread applications of WSNs and the need to safeguard sensitive data, this survey delves into the foundational aspects of WSNs, IDS, and ML, highlighting their interconnectedness. It provides insights into the latest advancements in IDS for WSNs, focusing on ML-based methodologies. Various ML algorithms are discussed in detail, elucidating their strengths, weaknesses, and relevance in IDS for WSNs. Furthermore, the survey conducts a comparative analysis of different ML-based IDS approaches, using diverse evaluation metrics. Ultimately, it concludes by pinpointing research challenges and future directions aimed at enhancing the efficacy of IDS for WSNs. The survey's overarching goal is to furnish an exhaustive assessment of approaches designed to bolster security in wireless remote networks (WSNs), exploring the factors influencing their implementation and adoption.