IoT Intrusion Detection

IoT: Internet of Things

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Overview

IoT intrusion detection studies how to recognize attacks such as botnets, denial-of-service, and probing in networks of connected devices and industrial systems. Approaches range from Random Forest and gradient-boosted flow classifiers to CNNs, recurrent networks, Transformers, graph models, and anomaly detection; federated and compressed models aim to work across private, resource-limited edge devices. Evaluation commonly uses datasets such as CICIoT2023, Edge-IIoTset, and ToN-IoT, but leakage and dataset-specific shortcuts can make impressive test scores overstate real-world performance. A central challenge is achieving reliable cross-device and cross-network generalization while resisting evasion or poisoning and meeting constraints on privacy, latency, and computation.

Latest papers

CardsList

51 papers7 papers in the last four weeks, level with the four weeks before. 0.0% of all new papers.

  1. AIRO: A Streaming-Based Machine Learning Framework for Threat Detection and Security in Industrial Internet of Things

    Oct 22, 2026Raima Deb, Pranav M Pawar, Mithun Mukherjee +2IoT Intrusion DetectionAutonomous Cyber Defense

    ∗Department of Computer Science, Birla Institute of Technology and Science, Pilani, Dubai Campus, Dubai International Academic City, Dubai, United Arab Emirates · † Guangdong Polytechnic Normal University, Guangzhou, China

  2. PVBRF-ID: Private, Verifiable and Byzantine-Robust Federated Intrusion Detection for Oilfield Enterprise Networks

    Oct 8, 2026Mustafa S. Aljumaily, Ali Ataeemh Allami, Mustafa N. Mnati +2Privacy-Preserving Federated LearningFederated Learning

    Daw Alfada Company, Amarah, Maysan, Iraq · University of Misan, Amarah, Maysan, Iraq · University of Southern Queensland, Toowoomba, QLD, Australia

  3. Adversarial RL for Port-Scan Evasion: Attacker Feature Visibility in Edge-Deployed IDS

    Oct 5, 2026Logan Andrew North, Priya Sanjay Kaluskar, Shasi Kumar Ramachandran Prabhu +2Adversarial AttacksIoT Intrusion Detection

    Pennsylvania State University University Park, PA, USA · Elizabethtown College Elizabethtown, PA, USA

  4. GCTAuto-encoder: A Cross modal Framework for Security Flaw Detection in IoT Networks

    Oct 5, 2026Najmieh Sadat SafarabadiCross-Modal LearningIoT Intrusion Detection

    Department of Computational Linguistics, University of Stuttgart, Stuttgart, Germany.

  5. Out of Sync, Out of Sight: Phantom State Attacks against IIoT Intrusion Detection

    Oct 1, 2026Sabrine Ennaji, Elhadj Benkhelifa, Nadia KabachiAdversarial AttacksIoT Intrusion Detection

    Universit´e Lyon 1, Universit´e Lumi`ere Lyon 2, ERIC, 69100 Villeurbanne, France · School of Computer Science and Mathematics, Liverpool John Moores University, Liverpool, U.K.

  6. From Network Intrusion Detection to Blockchain-Backed Endpoint Detection and Response: Mapping the Landscape of Decentralized Detection-and-Response Architectures

    Oct 1, 2026Yahya Shahsavari, Sara Rouhani, Kaiwen ZhangAutonomous Cyber DefenseIoT Intrusion Detection

    Dept. of Software and IT Engineering ´Ecole de technologie sup´erieure ( ´ETS) Montr´eal, Qu´ebec, Canada · Dept. of Computer Science University of Calgary Calgary, Alberta, Canada

  7. Cybersecurity in Edge Computing: A Trust-Aware Federated Hybrid Intrusion Detection Framework

    Sep 30, 2026Zawad Yalmie Sazid, Robert AbbasFederated Learning AggregationByzantine-Robust Federated Learning

    Victoria University, Sydney, Australia

  8. Evasion Attacks on Cost-Utility-Based Adversarial Training for Online AutoML in IoT Networks

    Sep 25, 2026Chukwunonso Henry Nwokoye, Wajiha Zaheer, Khalil El-Khatib +1Adversarial RobustnessAdversarial Training

    Faculty of Business and Information Technology, Ontario Tech University, Oshawa, Ontario, Canada · Department of Computer Science, Alex Ekwueme Federal University, Nigeria

  9. Input-Layer Starvation: Why Per-Layer Pruning Breaks IoT Intrusion Detectors

    Sep 25, 2026Md Anas BiswasNeural Network PruningIoT Intrusion Detection

    School of Computing, University of Portsmouth, Portsmouth, United Kingdom

  10. Unmasking Shortcut Learning in IoT Intrusion Detection: A Forensic, Multi-Paradigm Evaluation of Feature Dependence and Data Leakage

    Sep 23, 2026Uday Shankar Roy, Mahbuba Jahan MinuData LeakageIoT Intrusion Detection

    Computer Science and Engineering Khulna University of Engineering & Technology Khulna, Bangladesh

  11. Reliable Federated TinyML Deployment for IoT Security

    Sep 23, 2026Younsoo Park, Seokhyoen Bae, Shasi Kumar Ramachandran Prabhu +2IoT Intrusion DetectionTiny ML

    The Pennsylvania State University, University Park, Pennsylvania, USA · Elizabethtown College, Elizabethtown, Pennsylvania, USA

  12. An LLM-Assisted AutoML Framework for Intrusion Detection in IoT Networks

    Sep 19, 2026Li YangAutomated Machine LearningIoT Intrusion Detection

    Faculty of Business and Information Technology, Ontario Tech University, Oshawa, ON L1G 0C5, Canada · Department of Electrical and Computer Engineering, Western University, London, ON N6A 3K7, Canada

  13. An Adversarial Zero-Shot Learning Approach for Anomaly Detection in Multivariate IoT Traffic Data

    Sep 3, 2026Mahshid Rezakhani, Tolunay Seyfi, Fatemeh AfghahDomain-Adversarial LearningUnsupervised Domain Adaptation

    Holcombe Department of Electrical and Computer Engineering, Clemson University, Clemson, 29634 SC, USA

  14. SPADE: SPaT Attack Detection from the Connected Vehicle's Perspective

    Sep 2, 2026James Di Novo, Hany Ragab, Sylvain P. LeblancCybersecurityV2X Communication

    Department of Electrical and Computer Engineering, Faculty of Engineering, Royal Military College of Canada (RMC), Kingston, Ontario, K7K 7B4, Canada.

  15. Clustering-Based Collective Anomaly Detection in IoT Systems: A Graph Neural Network Approach

    Aug 26, 2026Dalila Khettaf, Djamel Djenouri, Zeinab Rezaeifar +1Anomaly DetectionUnsupervised Anomaly Detection

    University of the West of England(UWE) Bristol BS16 1QY, England · University of South-Eastern Norway, Kongsberg, 3616 Norway

  16. Diff-DDoS: Realistic Cyber-Physical Attack Synthesis and Robust Detection for 5G-Enabled CPS Using Tabular Diffusion Models

    Aug 18, 2026Bilal Hussain, Xiao Tang, Qinghe Du +3CybersecurityNetwork Intrusion Detection

    Division of Science, Engineering, and Health Studies, School of Professional Education and Executive Development, The Hong Kong Polytechnic University · School of Information and Communications Engineering, Xi’an Jiaotong University · Department of Computer Science, The Hang Seng University of Hong Kong +2

  17. Provenance, Not Behaviour: A Serialisation Artifact in Edge-IIoTset and a Leakage-Free Benchmark for Precision-Agriculture Intrusion Detection

    Aug 16, 2026Mostafa M. GalalIoT Intrusion DetectionData Leakage

    Department of Computer and Systems Engineering, Alexandria University, Alexandria, Egypt

  18. Benchmarking Cyberattack Detection in Electric Vehicle Charging Infrastructure with Benign User Updates

    Aug 11, 2026Hannan Chen, Roshni Anna Jacob, Jie ZhangIoT Intrusion DetectionElectric Vehicle Charging

    Department of Mechanical Engineering, The University of Texas at Dallas, Richardson, TX 75080, USA

  19. Beyond Detection Accuracy: Measuring Explanation Cost, Stability, and Utility for Resource-Aware IoT Intrusion Detection

    Aug 11, 2026Abdurrahman TolaySHAP Feature AttributionIoT Intrusion Detection

    Independent Researcher, Istanbul, Türkiye

  20. FedTransKD-IDS: Robust Federated Transfer Learning with Knowledge Distillation for Intrusion Detection in IoT

    Aug 6, 2026Mohammad Hosssein Gholamrezazadeh, Ahmadreza MontazerolghaemAhmadreza MontazerolghaemIoT Intrusion DetectionCybersecurity

    Faculty of Computer Engineering University of Isfahan Isfahan, Iran

  21. Post-Hoc Trajectory-Risk Certification for Modular LLM-Based Security Agents

    Aug 4, 2026Zhenpeng LiIoT Intrusion DetectionCybersecurity

    Guangzhou Health Science College, No. 248 Guangyuan Middle Road, Guangzhou, Guangdong 510405, China

  22. Explainable Hybrid Feature Selection for Intrusion Detection in Internet of Medical Things Environments

    Aug 1, 2026Amira Berrezzek, Hayet Djellali, Giulio Mallardi +1IoT Intrusion DetectionNetwork Intrusion Detection

    Computer Science Dept. Badji Mokhtar University Annaba, Algeria · Computer Science Dept. University of Bari Bari, Italy

  23. Closing the Loop: An Access-Control Architecture for Automated, Anomaly-Driven Network Revocation in IoT Deployments

    Jul 13, 2026Muhammet Emir Korkmaz, Kemal Bicakci, Yusuf UzunayAutonomous Cyber DefenseIoT Intrusion Detection

    Securify Information Technology and Security Training Consulting Inc., 06378, Ankara, TÜRK˙IYE · Informatics Institute, Istanbul Technical University, Ayazaga Campus, 34467, Maslak, Istanbul, TÜRK˙IYE

  24. Enhanced Feature Extraction for IoT Network Intrusion Detection Using GNNs and KAN

    Jul 3, 2026Long Zhao, Shixun Ji, Bin Cheng +1Graph Neural NetworksIoT Intrusion Detection

    Department of Control Science & Engineering, Tongji University, Shanghai 201804, China · National Key Laboratory of Autonomous Intelligent Unmanned Systems, Shanghai 201203, China

  25. Cross-Domain Generalization Failure in Lightweight Intrusion Detection Models for IIoT Networks

    Jul 1, 2026MD Azizul Hakim, Md Shihab Uddin, Talha Ibne AnisIoT Intrusion DetectionNetwork Intrusion Detection

    Department of Computer Science and Technology, Bangladesh Sweden Polytechnic Institute Kaptai, Rangamati, Chittagong 4530, Bangladesh · Department of Electrical Engineering, Bangladesh Sweden Polytechnic Institute Kaptai, Rangamati, Chittagong 4530, Bangladesh

  26. Comparative Analysis of Machine Learning based Intrusion Detection in Realistic IoT Networks

    Jun 30, 2026Rana Alharbi, Chuadhry Mujeeb AhmedIoT Intrusion DetectionNetwork Intrusion Detection

    Newcastle University, UK

  27. Categorical Robustness Assessment for Machine Learning based Network Intrusion Detection Systems

    Jun 10, 2026Mayank Raj, Nathaniel D. Bastian, Lance Fiondella +1IoT Intrusion DetectionAdversarial Attacks

    University of Massachusetts Dartmouth, Dartmouth, MA 02747 USA · United States Military Academy, West Point, NY 10996 USA

  28. Improving IoT Intrusion Detection Through SMOTE-Based Oversampling and Extended Multi-Model Evaluation on Side-Channel Power Data

    May 29, 2026Muhammad Khuram Shahzad, Haseeb Khan, Muhammad Masood Khan +1Class-Imbalanced LearningIoT Intrusion Detection

    aSchool of Electrical Engineering and Computer Science (SEECS), NUST, H-12 Campus, Islamabad, Pakistan44000

  29. ASTRO: Adaptive Spatio-Temporal Reinforcement Optimization for GNN Powered Anomly Detection in Cyber Physical Systems

    May 24, 2026Rai Ali Yar, Umaisa Lail, Anwar ShahIndustrial Anomaly DetectionOnline Anomaly Detection

    Department of Computer Science, FAST NUCES, Development Sector, Faisalabad, Pakistan · Department of Information Technology, Riphah International University, Faisalabad, Pakistan

  30. CLAD: A Clustered Label-Agnostic Federated Learning Framework for Joint Anomaly Detection and Attack Classification

    May 7, 2026Iason Ofeidis, Nikos Papadis, Randeep Bhatia +2IoT Intrusion DetectionNetwork Intrusion Detection

    Yale University, New Haven, CT, USA · Nokia Bell Labs, Murray Hill, NJ, USA