Anomaly Detection

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Overview

Anomaly detection studies how to identify observations or events that depart from expected behavior, often when examples of real anomalies are scarce or unknown. Common approaches learn normality through density estimation, isolation methods, reconstruction or forecasting, while newer methods use graph structure, multimodal features, synthetic anomalies, and pretrained vision or language models. Work spans settings such as industrial images, sensor time series, network traffic, and transaction graphs, with benchmarks including MVTec AD, SWaT, and DCASE used to assess detection and localization. A central challenge is balancing sensitivity against false alarms as data shift, training sets become contaminated, and models move from curated benchmarks to constrained real-world deployments.

Latest papers

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657 papers61 papers in the last four weeks, level with the four weeks before. 0.4% of all new papers.

  1. Online Continual Learning for Anomaly Detection in IoT under Data Distribution Shifts

    Mar 8, 2026Matea Marinova, Shashi Raj Pandey, Junya Shiraishi +3Continual Anomaly DetectionOnline Anomaly Detection

    Faculty of Electrical Engineering and Information Technologies, Ss. Cyril and Methodius University in Skopje, 1000 Skopje, North Macedonia · Dept. of Electronic Systems, Aalborg University, Aalborg, Denmark

  2. Interpretable Maximum Margin Deep Anomaly Detection

    Mar 7, 2026Zhiji Yang, Mei Huang, Xinyu Li +3Semi-Supervised Anomaly DetectionAnomaly Detection

    the School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming 650221, China · the Academy for Multidisciplinary Studies, Capital Normal University, Beijing 100048, China

  3. DQE: A Semantic-Aware Evaluation Metric for Time Series Anomaly Detection

    Mar 6, 2026Yuewei Li, Dalin Zhang, Huan Li +3Time-Series Anomaly DetectionAnomaly Detection

    Hangzhou Dianzi University, Hangzhou, China · Zhejiang University, Hangzhou, China

  4. AegisUI: Behavioral Anomaly Detection for Structured User Interface Protocols in AI Agent Systems

    Mar 5, 2026Mohd Safwan Uddin, Saba HajiraAnomaly DetectionAI Agent Security

    Department of Computer Science, Muffakham Jah College of Engineering and Technology, Hyderabad, India · Department of Information Technology, Muffakham Jah College of Engineering and Technology, Hyderabad, India

  5. From Offline to Periodic Adaptation for Pose-Based Shoplifting Detection in Real-world Retail Security

    Mar 5, 2026Shanle Yao, Narges Rashvand, Armin Danesh Pazho +1Reference-Based Video Anomaly DetectionVideo Anomaly Detection

    The authors are with the Electrical and Computer Engineering Department, The University of North Carolina at Charlotte, Charlotte, NC, 28223 USA.

  6. Temporal Pooling Strategies for Training-Free Anomalous Sound Detection with Self-Supervised Audio Embeddings

    Mar 4, 2026Kevin Wilkinghoff, Sarthak Yadav, Zheng-Hua TanAnomaly Detection

    Department of Electronic Systems, Aalborg University, Aalborg, Denmark · Pioneer Centre for Artificial Intelligence, Denmark

  7. Multi-Scale Adaptive Neighborhood Awareness Transformer For Graph Fraud Detection

    Mar 3, 2026Jiaqi Lv, Qingfeng Du, Yu Zhang +2Graph TransformerAnomaly Detection

    School of Computer Science and Technology, Tongji University, Shanghai, China

  8. ERP-RiskBench: Leakage-Safe Ensemble Learning for Financial Risk

    Mar 3, 2026Sanjay MishraStacked Ensemble LearningFinancial Fraud Detection

    IEEE Member Raleigh, NC, USA

  9. TRAKNN: Efficient Trajectory Aware Spatiotemporal kNN for Rare Meteorological Trajectory Detection

    Mar 2, 2026Guillaume Coulaud, Davide Farandak-Nearest NeighborsAnomaly Detection

    UM, IROKO · University of Montpellier, Inria, CNRS, LIRMM, Montpellier, France · LMD, LSCE, ESTIMR +3

  10. Trivial Graph Features and Classical Learning are Enough to Detect Random Anomalies

    Mar 2, 2026Matthieu Latapy, Stephany RajehAnomaly DetectionGraph-Based Anomaly Detection

    CNRS, LIP6 Sorbonne Universit´e Paris, France · Efrei Research Lab Efrei Paris Panth´eon-Assas Universit´e Villejuif, France

  11. GCTAM: Global and Contextual Truncated Affinity Combined Maximization Model For Unsupervised Graph Anomaly Detection

    Mar 2, 2026Xiong Zhang, Hong Peng, Zhenli He +3Social Network AnalysisUnsupervised Anomaly Detection

    School of Software, Yunnan University, Kunming, China

  12. Dual Distillation for Few-Shot Anomaly Detection

    Mar 2, 2026Le Dong, Qinzhong Tan, Chunlei Li +5Few-Shot Anomaly DetectionAnomaly Detection

    Xidian University, China · MedAI Technology (Wuxi) Co. Ltd., China · Technical University of Munich, Germany

  13. DualSentinel: A Lightweight Framework for Detecting Targeted Attacks in Black-box LLM via Dual Entropy Lull Pattern

    Mar 2, 2026Xiaoyi Pang, Xuanyi Hao, Pengyu Liu +3LLM SecurityBackdoor Defense in LLMs

    The Hong Kong University of Science and Technology, Hong Kong · The State Key Laboratory of Blockchain and Data Security, Zhejiang University, P. R. China · School of Cyber Science and Technology, Zhejiang University, P. R. China

  14. TAS-GNN: A Status-Aware Signed Graph Neural Network for Anomaly Detection in Bitcoin Trust Systems

    Feb 28, 2026Chang Xue, Fang Liu, Jiaye Wang +2Anomaly DetectionGraph Neural Networks

    Yeshiva University · Yale University · University of California, San Diego +2

  15. An Efficient Unsupervised Federated Learning Approach for Anomaly Detection in Heterogeneous IoT Networks

    Feb 27, 2026Mohsen Tajgardan, Atena Shiranzaei, Mahdi Rabbani +2Unsupervised Anomaly DetectionAnomaly Detection

    Faculty of Electrical and Computer Engineering, Qom University of Technology, Qom, Iran · Department of Computer Engineering, Faculty of Industry and Mining (Khash), Sistan and Baluchestan University, Zahedan, Iran · Canadian Institute for Cybersecurity, University of New Brunswick, NB, Canada +1

  16. Incremental dimension reduction for efficient and accurate visual anomaly detection

    Feb 27, 2026Teng-Yok LeeDimensionality ReductionAnomaly Detection

    Information R&D Technology Center, Mitsubishi Electric Coporation

  17. Modelling and Simulation of Neuromorphic Datasets for Anomaly Detection in Computer Vision

    Feb 26, 2026Mike Middleton, Teymoor Ali, Hakan Kayan +6Synthetic Anomaly GenerationEvent-Based Vision

    Bio-Inspired Systems and Technologies Lab, University of York, York, UK · Faculty of Natural Sciences, University of Stirling, Stirling, UK · School of Computer Science and Informatics, Cardiff University, Cardiff, UK +2

  18. SubspaceAD: Training-Free Few-Shot Anomaly Detection via Subspace Modeling

    Feb 26, 2026Camile Lendering, Erkut Akdag, Egor BondarevFew-Shot Anomaly DetectionAnomaly Detection

    AIMS Group, Department of Electrical Engineering, Eindhoven University of Technology

  19. SmartBench: Evaluating LLMs in Smart Homes with Anomalous Device States and Behavioral Contexts

    Feb 24, 2026Qingsong Zou, Zhi Yan, Zhiyao Xu +3Anomaly DetectionLLM Evaluation

    Tsinghua Shenzhen International Graduate School Shenzhen, China · Jilin University Jilin, China · The Chinese University of Hong Kong Hong Kong, China +1

  20. Inspectorch: Efficient rare event exploration in solar observations

    Feb 23, 2026C. J. Díaz Baso, I. J. Soler Poquet, C. Kuckein +2Solar PhysicsAnomaly Detection

    Institute of Theoretical Astrophysics, University of Oslo, P.O. Box 1029 Blindern, N-0315 Oslo, Norway · Rosseland Centre for Solar Physics, University of Oslo, P.O. Box 1029 Blindern, N-0315 Oslo, Norway · Instituto de Astrofísica de Canarias, C/Vía Láctea s/n, E-38205 La Laguna, Tenerife, Spain +3

  21. Learning Discriminative and Generalizable Anomaly Detector for Dynamic Graph with Limited Supervision

    Feb 23, 2026Yuxing Tian, Yiyan Qi, Fengran Mo +3Semi-Supervised Anomaly DetectionGraph-Based Anomaly Detection

    Universit´e de Montréal · International Digital Economy Academy (IDEA) · McGill University +1

  22. SHIELD: Semantic Heterogeneity Integrated Embedding for Latent Discovery in Clinical Trial Safety Signals

    Feb 23, 2026Francois Vandenhende, Anna Georgiou, Theodoros Psaras +1Semantic ClusteringAnomaly Detection

    ClinBAY Limited, Limassol, Cyprus

  23. RAID: Retrieval-Augmented Anomaly Detection

    Feb 23, 2026Mingxiu Cai, Zhe Zhang, Gaochang Wu +2Unsupervised Anomaly DetectionAnomaly Detection

    State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University · University of Surrey

  24. INTACT: Intent-Aware Representation Learning for Cryptographic Traffic Violation Detection

    Feb 22, 2026Rahul D RayEncrypted Network Traffic AnalysisAnomaly Detection

    Department of Electronics & Electrical Engineering, BITS Pilani, Hyderabad Campus

  25. From Few-Shot to Zero-Shot: Towards Generalist Graph Anomaly Detection

    Feb 21, 2026Yixin Liu, Shiyuan Li, Yu Zheng +4Anomaly DetectionZero-Shot Anomaly Detection

    School of Information and Communication Technology, Griffith University, Australia. · School of Computer, Electronics and Information, Guangxi University, Nanning, China. · Department of Data Science and Artificial Intelligence, The Hong Kong Polytechnic University, Hong Kong. +1

  26. Mind the Gap: Detecting Cluster Exits for Robust Local Density-Based Score Normalization in Anomalous Sound Detection

    Feb 21, 2026Kevin Wilkinghoff, Gordon Wichern, Jonathan Le Roux +1Anomaly DetectionUnsupervised Anomaly Detection

    Department of Electronic Systems, Aalborg University, Aalborg, Denmark · Pioneer Centre for Artificial Intelligence, Copenhagen, Denmark · Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA

  27. Multi-Axis Trust Modeling for Interpretable Account Hijacking Detection

    Feb 20, 2026Mohammad AL-SmadiAnomaly DetectionInterpretable Anomaly Detection

    Qatar University, Doha, Qatar

  28. EAGLE: Expert-Augmented Attention Guidance for Tuning-Free Industrial Anomaly Detection in Multimodal Large Language Models

    Feb 19, 2026Xiaomeng Peng, Xilang Huang, Seon Han ChoiAnomaly DetectionIndustrial Anomaly Detection

    Ewha Womans University

  29. StructCore: Structure-Aware Image-Level Scoring for Training-Free Unsupervised Anomaly Detection

    Feb 19, 2026Joongwon Chae, Lihui Luo, Yang Liu +8Unsupervised Anomaly DetectionAnomaly Detection

    Tsinghua University Shenzhen International Graduate School, Shenzhen, China · Ratel Soft · Affiliated Fifth Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China +1

  30. How Much Does Machine Identity Matter in Anomalous Sound Detection at Test Time?

    Feb 18, 2026Kevin Wilkinghoff, Keisuke Imoto, Zheng-Hua TanAnomaly DetectionIndustrial Anomaly Detection

    Aalborg University, Denmark · Pioneer Centre for Artificial Intelligence, Denmark · Kyoto University, Japan