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. VARS-FL: Validation-Aligned Client Selection for Non-IID Federated Learning in IoT Systems

    May 7, 2026Mohamed Lakas, Mohamed Amine FerragIoT Intrusion DetectionClient Selection in Federated Learning

    College of Information Technology, United Arab Emirates University, UAE

  2. A-THENA: Early Intrusion Detection for IoT with Time-Aware Hybrid Encoding and Network-Specific Augmentation

    Apr 23, 2026Ioannis Panopoulos, Maria Lamprini A. Bartsioka, Sokratis Nikolaidis +3IoT Intrusion DetectionNetwork Intrusion Detection

    National Technical University of Athens, Greece · Samsung AI Center, UK

  3. Robustness Analysis of Machine Learning Models for IoT Intrusion Detection Under Data Poisoning Attacks

    Apr 15, 2026Fortunatus Aabangbio Wulnye, Justice Owusu Agyemang, Kwame Opuni-Boachie Obour Agyekum +3IoT Intrusion DetectionAdversarial Robustness

    Department of Telecommunication, Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana

  4. BRIDGE and TCH-Net: Heterogeneous Benchmark and Multi-Branch Baseline for Cross-Domain IoT Botnet Detection

    Apr 13, 2026Ammar Bhilwarawala, Likhamba Rongmei, Harsh Sharma +4IoT Intrusion DetectionDomain Generalization

    School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha 751024, India

  5. Hybrid ResNet-1D-BiGRU with Multi-Head Attention for Cyberattack Detection in Industrial IoT Environments

    Apr 7, 2026Afrah Gueriani, Hamza Kheddar, Ahmed Cherif MazariIoT Intrusion DetectionConvolutional RNNs

    LSEA Lab., Faculty of Technology, University of MEDEA, Medea 26000, Algeria · LSEA Lab, Faculty of Science, University of MEDEA, Medea 26000, Algeria

  6. MA-IDS: Multi-Agent RAG Framework for IoT Network Intrusion Detection with an Experience Library

    Apr 7, 2026Md Shamimul Islam, Luis G. Jaimes, Ayesha S. DinaExplainable Intrusion DetectionIoT Intrusion Detection

    Department of Computer Science, Florida Polytechnic University, Lakeland, Florida

  7. SE-Enhanced ViT and BiLSTM-Based Intrusion Detection for Secure IIoT and IoMT Environments

    Apr 6, 2026Afrah Gueriani, Hamza Kheddar, Ahmed Cherif Mazari +2Hybrid Transformer ArchitecturesIoT Intrusion Detection

    LSEA Lab., Faculty of Technology, University of MEDEA, Medea 26000, Algeria · LSEA Lab, Faculty of Science, University of MEDEA, Medea 26000, Algeria · Department of Computer Engineering, Gazi University, Ankara, Turkey +1

  8. A Tsetlin Machine-driven Intrusion Detection System for Next-Generation IoMT Security

    Apr 3, 2026Rahul Jaiswal, Per-Arne Andersen, Linga Reddy Cenkeramaddi +2Explainable Intrusion DetectionIoT Intrusion Detection

    The Centre for Artificial Intelligence Research (CAIR), Department of ICT, University of Agder, Norway

  9. Toward a Multi-Layer ML-Based Security Framework for Industrial IoT

    Mar 25, 2026Aymen Bouferroum, Valeria Loscri, Abderrahim BenslimaneInternet of ThingsIoT Intrusion Detection

    LIA · Inria Lille-Nord Europe, Lille, France · LIA/CERI University of Avignon, Avignon, France

  10. Targeted Adversarial Traffic Generation : Black-box Approach to Evade Intrusion Detection Systems in IoT Networks

    Mar 24, 2026Islam Debicha, Tayeb Kenaza, Ishak Charfi +3Adversarial AttacksIoT Intrusion Detection

  11. Explainable Threat Attribution for IoT Networks Using Conditional SHAP and Flow Behavior Modelling

    Mar 24, 2026Samuel Ozechi, Jennifer OkonkwoabutuExplainable Intrusion DetectionIoT Intrusion Detection

    University of East London, United Kingdom · ECE Ecole D’Ingenieur, France

  12. In-network Attack Detection with Federated Deep Learning in IoT Networks: Real Implementation and Analysis

    Mar 23, 2026Devashish Chaudhary, Sutharshan Rajasegarar, Shiva Raj Pokhrel +2IoT Intrusion DetectionNetwork Intrusion Detection

    School of IT, Deakin University, Geelong, Australia · School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India

  13. Deep learning based intelligent IDS for Large-scale IoT networks

    Mar 17, 2026Isha Andrade, Shalaka S Mahadik, Mithun Mukherjee +2IoT Intrusion DetectionNetwork Intrusion Detection

    Department of Computer Science, Birla Institute of Technology and Science, Pilani, Dubai Campus, Dubai International Academic City, Dubai, United Arab Emirates

  14. How the Graph Construction Technique Shapes Performance in IoT Botnet Detection

    Feb 28, 2026Hassan Wasswa, Hussein Abbass, Timothy LynarGraph ConstructionIoT Intrusion Detection

    School of Systems and Computing, University of New South Wales, Canberra, 2600 ACT Australia

  15. Neurosymbolic Learning for Advanced Persistent Threat Detection under Extreme Class Imbalance

    Feb 28, 2026Quhura Fathima, Neda Moghim, Mostafa Taghizade Firouzjaee +3IoT Intrusion DetectionNeurosymbolic Learning

    Center for Secure & Intelligent Critical Systems and School of Cybersecurity, Old Dominion University, VA, USA · Department of Computer Engineering, University of Isfahan, Iran · Faculty of Engineering Modern Technologies, Amol University of Special Modern Technologies, Iran +2

  16. Quantifying Catastrophic Forgetting in IoT Intrusion Detection Systems

    Feb 27, 2026Sourasekhar Banerjee, David Bergqvist, Salman Toor +2IoT Intrusion DetectionCatastrophic Forgetting

    Uppsala University, Department of Information Technology, Sweden · Scaleout Systems AB, Sweden · Ericsson Research, Research Area AI, Sweden

  17. Exploring Robust Intrusion Detection: A Benchmark Study of Feature Transferability in IoT Botnet Attack Detection

    Feb 27, 2026Alejandro Guerra-Manzanares, Jialin HuangIoT Intrusion DetectionCross-Domain Generalization

    School of Computer Science, University of Nottingham, Ningbo, China · School of Computer Science, University of Nottingham, Nottingham, United Kingdom

  18. MI2^2DAS: A Multi-Layer Intrusion Detection Framework with Incremental Learning for Securing Industrial IoT Networks

    Feb 27, 2026Wei Lian, Alejandro Guerra-ManzanaresIoT Intrusion DetectionNetwork Intrusion Detection

    School of Computer Science, University of Nottingham, Ningbo, China

  19. ThreatFormer-IDS: Robust Transformer Intrusion Detection with Zero-Day Generalization and Explainable Attribution

    Feb 26, 2026Srikumar NayakExplainable Intrusion DetectionIoT Intrusion Detection

    Incedo Inc, USA

  20. Explainability-Aware Evaluation of Transfer Learning Models for IoT DDoS Detection Under Resource Constraints

    Feb 25, 2026Nelly ElsayedIoT Intrusion DetectionCybersecurity

    School of Information Technology, University of Cincinnati, Ohio, United States

  21. PenTiDef: Decentralized Federated Intrusion Detection System with Differential Privacy and Latent-Space Defense via Blockchain Coordination in IIoT

    Feb 20, 2026Phan The Duy, Nghi Hoang Khoa, Nguyen Tran Anh Quan +3Blockchain-Based Federated LearningIoT Intrusion Detection

    Information Security Lab, University of Information Technology, Ho Chi Minh City, Vietnam. · Vietnam National University, Ho Chi Minh City, Vietnam. · VNU-HCM Information Security Center, Ho Chi Minh City, Vietnam.