Unsupervised Anomaly Detection

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Overview

Unsupervised anomaly detection learns what typical data look like, then flags samples or events that depart from those patterns when anomaly labels are unavailable. Methods include density and distance scoring, such as Isolation Forest and k-nearest neighbors; one-class models; reconstruction and forecasting; and self-supervised or generative models that learn useful representations of normal data. For time series, graphs, images, audio, and multiple sensor modalities, methods can also model temporal, relational, spatial, or cross-modal structure, supporting applications from industrial inspection and medical imaging to network security and scientific monitoring. A central challenge is reliable deployment: contamination of training data, shifts in normal behavior, and threshold choices can undermine performance, while strong results on curated benchmarks may not transfer across domains.

Latest papers

CardsList

229 papers29 papers in the last four weeks, up 26% on the four weeks before. 0.2% of all new papers.

  1. Anomaly Detection on Resource-Constrained Devices with Reservoir Computing

    Nov 3, 2026Marco Angioli, Mathias Persson, Hiroto Tamura +5Time-Series Anomaly DetectionAnomaly Detection

    the AI, Robotics and Cybersecurity Center (ARC) and the Department of Computer Science, Örebro University, 70281 Örebro, Sweden. · the Graduate School of Informatics, Osaka Metropolitan University, 558-8585 Osaka Japan · the International Research Center for Neurointelligence (IRCN), the University of Tokyo, 113-0033 Tokyo, Japan +3

  2. Bounded AUKS: A Novel Evaluation Metric for Anomaly Detection via Bounded Area Under the Kolmogorov--Smirnov Curve

    Nov 3, 2026Yanshuo Zhang, Juan DuAnomaly DetectionUnsupervised Anomaly Detection

    Smart Manufacturing Thrust, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, 100190, China · Data Science and Analytics Thrust, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, 100190, China · Department of Mechanical and Aerospace Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, 999077, China

  3. Benchmarking Unsupervised Jamming Detection in 5G Open RAN

    Nov 3, 2026Sneihil Gopal, Fernando J. Cintron, Richard A. RouilUnsupervised Anomaly DetectionAnomaly Detection

    PREP Associate, National Institute of Standards and Technology (NIST), USA · Department of Physics, Georgetown University, USA · National Institute of Standards and Technology (NIST), USA.

  4. Robust Remote ECG Monitoring under Energy Constraints: Anomaly Filtering versus Predictive Uncertainty

    Nov 1, 2026Mustafa Fuad Rifet Ibrahim, Maurice Meijer, Alexander Schlaefer +1Remote Patient MonitoringElectrocardiogram Classification

    CTO System Innovation, NXP Semiconductors Germany GmbH, Beiersdorfstraße 12, Hamburg, 22529, Germany · Institute of Medical Technology and Intelligent Systems, Hamburg University of Technology, Am Schwarzenberg-Campus 1, Hamburg, 21073, Germany · Faculty of Computer Science and Digital Society, Hamburg University of Applied Sciences, Berliner Tor 5, Hamburg, 20099, Germany +1

  5. A Hybrid Anomaly Detection Method for Electric Vehicle Identification from Smart Meter Recordings

    Nov 1, 2026Ali Babalhavaeji, Hui Song, Mohammadreza Radmanesh +1Anomaly DetectionUnsupervised Anomaly Detection

    RMIT University, Melbourne, Australia

  6. VariaFlow: Uncertainty-Aware Flow Matching for Unsupervised Anomaly Detection

    Oct 30, 2026Arnela Hadzic, Martin Urschler, Cosmin I. BerceaMedical Image Anomaly DetectionUnsupervised Anomaly Detection

    Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria · Institute of Visual Computing, Graz University of Technology, Graz, Austria · Technical University of Munich, School of Medicine and Health, TUM University Hospital, Klinikum rechts der Isar, Department of Diagnostic and Interventional Radiology, Munich, Germany

  7. Anomalies as Residuals: Cauchy Displacement Networks

    Oct 30, 2026Yang Cao, Zihao GuoAnomaly DetectionTabular Anomaly Detection

    School of Computing and Information Technology, Great Bay University · Tsinghua Shenzhen International Graduate School, Tsinghua University, China · Institute for Advanced Research, Great Bay University, China

  8. Pneuma: A Large-Scale Real-World Time Series Benchmark for Commercial Aircraft Predictive Maintenance

    Oct 27, 2026Jiafeng Lin, Yutian Zhang, Huan Zhang +5Predictive MaintenanceMultivariate Time Series Forecasting

    China Southern Airlines, Guangzhou, China · School of Transportation Science and Engineering, Beihang University, Beijing, China

  9. ExCal: Optimization-Free Multivariate Time Series Anomaly Detection via Excess Calibration

    Oct 26, 2026Kadir-Kaan Özer, René Ebeling, Markus EnzweilerMemory-Bank-Based Anomaly DetectionTime-Series Anomaly Detection

    Mercedes-Benz AG, Germany · Institute for Intelligent Systems, Esslingen University of Applied Sciences, Germany

  10. LEAP: a Latent Embedding Anomaly Patch-Transformer for time-series anomaly detection

    Oct 26, 2026Cristhian Moya-Mota, Ignacio Aguilera-Martos, Diego García-Gil +1Time-Series Anomaly DetectionUnsupervised Anomaly Detection

    Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain. · Andalusian Institute of Data Science and Computational Intelligence (DaSCI), University of Granada, Granada, Spain. · Department of Software Engineering, University of Granada, Granada, Spain

  11. Learning Pathology-Sensitive Representations for Unsupervised Retinal OCT Anomaly Detection

    Oct 23, 2026Tania Haghighi, Sina Gholami, Behafarin Emam +5Medical Image Anomaly DetectionUnsupervised Anomaly Detection

    University of North Carolina at Charlotte, Charlotte, North Carolina, USA · University of Illinois Chicago, Chicago, IL, USA · Byers Eye Institute at Stanford, Stanford University School of Medicine, Stanford, CA, USA +1

  12. TENET: Time-point Encoding Network for Multivariate Time Series Anomaly Detection

    Oct 23, 2026Dongchan Cho, Juwon Hwang, Keumyeong Kang +2Unsupervised Anomaly DetectionTime-Series Anomaly Detection

    Industrial AI Lab, SimPlatform Co. Ltd. Affiliate Research Institute

  13. EVOLVE: Uncertainty-Aware Multivariate Time Series Anomaly Prediction with Adaptive Prototype Memories

    Oct 23, 2026Jianxin Jin, Kai Zhao, Shiyan Hu +8Time-Series Anomaly DetectionUnsupervised Anomaly Detection

    East China Normal University · Aalborg University · APPLab, Huawei +2

  14. WADE: An LSTM-Based Anomaly Detection Engine for WebAssembly Applications

    Oct 22, 2026Ilaria Campestrini, Stefano Zanero, Engin KirdaSoftware SecurityAnomaly Detection

    Politecnico di Milano, Milan, Italy · Northeastern University, Boston, MA, USA

  15. HARMONY: Hierarchical Anchor Retrieval on Manifold for Oblivious-source Machinery Acoustic Anomaly Detection

    Oct 22, 2026Yuhang Zhang, Yang Li, Qiang Wu +1Anomaly DetectionIndustrial Anomaly Detection

    School of Software and Microelectronics, Peking University, Beijing, China · Independent Researcher · Collaborative Innovation Center for Western Ecological Safety, Lanzhou University, Lanzhou, China +2

  16. Distilling Multi-Teacher Scoring Principles for Unsupervised Time Series Anomaly Detection

    Oct 21, 2026Dongchan Cho, Jiho Han, Juwon Hwang +3Unsupervised Anomaly DetectionTime-Series Anomaly Detection

    Industrial AI Lab, SimPlatform Co. Ltd. Affiliate Research Institute

  17. HCFM: Helmholtz Component Flow Matching for Time Series Anomaly Detection

    Oct 18, 2026Shyam Sundar Saravanan, Tie Luo, Sanjay MadriaTime-Series Anomaly DetectionUnsupervised Anomaly Detection

    Department of Computer Science, Missouri University of Science and Technology, Rolla, MO, USA · Department of ECE, University of Kentucky, Lexington, KY, USA

  18. Few-Shot Adaptation for Anomalous Sound Detection at Low False-Positive Rate

    Oct 14, 2026Simone Lugani, Christof Pichler, Hannes Wegleiter +3Anomaly DetectionIndustrial Anomaly Detection

    DITEN, University of Genoa, Genoa, Italy · Christian Doppler Laboratory for Measurement Systems for Harsh Operating Conditions, EMS, TU Graz, Graz, Austria · voestalpine Stahl GmbH, Linz, Austria

  19. Physical Layer Anomaly Detection via Adaptive Gaussian Mixture Model

    Oct 13, 2026Mamady Delamou, Luan Chen, Arsenia ChortiUnsupervised Anomaly DetectionGaussian Mixture Models

    ETIS UMR 8051, CY Cergy Paris Université, ENSEA, CNRS, Cergy, France · Barkhausen Institut, Dresden, Germany

  20. Unsupervised Data Drift Monitoring for Deployed Deepfake Speech Detectors

    Oct 12, 2026Lukáš Prokeš, Vojtěch Staněk, Anton Firc +1Distribution Shift DetectionUnsupervised Anomaly Detection

  21. Feature-Context Consistency: Unsupervised Adversarial Detection with Drift Stability on Attributed Graphs

    Oct 12, 2026Firas Bayram, Maxime CordyGraph-Based Anomaly DetectionAnomaly Detection

    SnT, University of Luxembourg Luxembourg

  22. When LiDAR Fades, Radar Takes Over: LiDAR Reliability-Aware Adaptive Localization Under Airborne Obscurants

    Oct 9, 2026Moumita Mukherjee, Avijit Banerjee, Anton Koval +1Robot LocalizationLiDAR Odometry

    Robotics and AI Group, Department of Computer, Electrical and Space Engineering, Luleå University of Technology, Luleå, Sweden

  23. WaSA: Wavelet Scattering Autoencoders for Unsupervised Offline Detection of Malicious Clients in Federated Learning

    Oct 9, 2026Alessandro LicciardiWavelet Scattering TransformsByzantine-Robust Federated Learning

    Department of Mathematical Sciences, Politecnico di Torino, Turin, IT · National Institute of Nuclear Physics (INFN), Sezione di Torino, Turin, IT

  24. RIFT: Relative Isolation From Trees For Anomaly Detection

    Oct 8, 2026Mark Daniel Szalai, Gabor HorvathUnsupervised Anomaly DetectionAnomaly Detection

    Department of Networked Systems and Services, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, M˝uegyetem rkp. 3, Budapest, H-1111, Hungary

  25. Unsupervised Maneuver-Aware Acoustic Fault Detection for Autonomous Drones

    Oct 7, 2026Ali M Ali, Ziyi Tang, Nurdaulet Nazarbay +1Fault DetectionUnsupervised Anomaly Detection

    Department of Mechanical and Aerospace Engineering, Carleton University, Ottawa, ON, K1S-5B6, Canada · Department of Electrical and Computer Engineering at the University of Alberta, Edmonton, AB, Canada · The Hong Kong Polytechnic University, Hong Kong

  26. Pareto-optimal quantum kernel selection for unsupervised anomaly detection on real malware beaconing data

    Oct 7, 2026Boaz Micah, Nadia Milazzo, Maissa Beji +8Quantum Kernel MethodsUnsupervised Anomaly Detection

    Multiverse Computing, Parque Científico y Tecnológico de Gipuzkoa, Paseo de Miramón 170, Planta 2, 20014 Donostia / San Sebastián, Spain · IQM Quantum Computers, 4 rue Royale, 75008 Paris, France · Multiverse Computing, 7 rue de la Croix Martre, 91120 Palaiseau, Paris, France +3

  27. A Multi-Source Ultrasound Benchmark Revealing the Limits of Contemporary Self-Supervised Anomaly Detection Methods

    Oct 7, 2026Marco Riedenauer, Daniel Kienzle, Pratik Mayekar +1Medical Image Anomaly DetectionUnsupervised Anomaly Detection

    University of Augsburg

  28. Quasi-Binarized Autoencoders: An Architecture-Independent Information Bottleneck for Medical Image Anomaly Detection

    Oct 7, 2026Shouhei Hanaoka, Takahiro Nakao, Atsushi Takamatsu +2Medical Image Anomaly DetectionUnsupervised Anomaly Detection

    Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan · Department of Computational Diagnostic Radiology and Preventive Medicine, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan · Department of Radiology, Kanazawa University Hospital, 13-1 Takara-machi, Kanazawa, Ishikawa, 920-8641, Japan

  29. GRC-Net: Global Representation Consistency Network for Unsupervised Multimodal Anomaly Detection

    Oct 7, 2026Seyoung Jeong, Jong Pil Yun, Sang Jun LeeAnomaly DetectionIndustrial Anomaly Detection

    Jeonbuk National University, Jeonju, Republic of Korea · Korea Institute of Industrial Technology (KITECH), Incheon, Republic of Korea · Chung-Ang University, Seoul, Republic of Korea

  30. Deep Defence on Wheels: A Dual Intrusion Detection System Architecture for Comprehensive In-Vehicle Network Security

    Oct 5, 2026Shashwat Khandelwal, Shanker ShreejithNetwork Intrusion DetectionUnsupervised Anomaly Detection

    Trinity College Dublin, Ireland