ItemConference Paper

Explainable Intrusion Detection System for Internet of Things-explainability with reliability

Title
Explainable Intrusion Detection System for Internet of Things-explainability with reliability
Creator
Paul, Aditi; Kumari, Sweety; Navadia, Nipun R; Sinha, Somnath
Description
Explainable Artificial Intelligence (XAI) based Intrusion Detection System (IDS) (X-IDS) has transformed the traditional IDS into interpretable and transparent system with the goal of providing interpretable justification for IDS models. XAI is now being used to extract more appropriate features for specific cyber-attacks. The black-box model of ML based IDS is not capable of giving reason for false positive to the cyber defense personnel. XAI tools reduces this abstraction by locally interpreting the model's behaviour at some datapoints along with global interpretability. This article proposes an explainable IDS by using XAI tools. We used SHAP (SHapley Additive exPlanations) to identify the variations in feature importance of selected ML based IDSs and explain the variations of their detection accuracies. Also, we have shown that with same dataset, feature importance varies differently with different ML models. This leads us to the conclusion that specific set of features are required for specific ML models while other can be discarded. The explainability proposed in this study also help to select less set of features to overcome time of execution and cost. 2025 IEEE.
Source
Proceedings of 5th International Conference on Soft Computing for Security Applications, ICSCSA 2025;pp.226-232
Date
01-01-2025
Publisher
Institute of Electrical and Electronics Engineers Inc.
Subject
DoS attack; feature importance; Intrusion Detection System; XAI based IDS; XAI for machine learning
Coverage
Paul A., Banasthali Vidhapith, Department of Computer Science, Jaipur, India; Kumari S., Banasthali Vidhapith, Department of Computer Science, Jaipur, India; Navadia N.R., Pace University, New York City, NY, United States; Sinha S., Christ University, Department of Computer Science, Bengaluru, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 979-833159491-6;
Format
online
Language
English
Type
Conference paper

Citation

Paul, Aditi; Kumari, Sweety; Navadia, Nipun R; Sinha, Somnath, “Explainable Intrusion Detection System for Internet of Things-explainability with reliability,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/26110.

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