Time-Series Anomaly Detection

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Overview

Time-series anomaly detection seeks unusual points, intervals, or changes in relationships among signals, often when labeled failures are scarce and early warnings matter. Common approaches forecast or reconstruct normal behavior and flag large residuals; others use density models, learned representations, graphs, causal structure, or ensembles to capture dependencies and changing operating regimes. Research spans univariate and multivariate benchmarks as well as industrial, medical, network, and edge-device settings, with growing attention to localization, explanations, and compute limits. A central tension is that results depend heavily on evaluation metrics, thresholds, windowing, and anomaly types, while strong benchmark scores may not carry over to distribution shifts or real-time deployment.

Latest papers

CardsList

208 papers35 papers in the last four weeks, up 169% on the four weeks before. 0.2% of all new papers.

  1. skchange: Fast and Flexible Algorithms for Changepoint Detection

    Aug 20, 2026Martin Tveten, Johannes Voll Kolstø, Per August Jarval MoenChange-Point DetectionTime-Series Anomaly Detection

    Department of Statistics and Machine Learning, Norwegian Computing Center · Department of Mathematics, University of Oslo

  2. Digital Twin-Based Intrusion Detection for Vehicle Powertrain CAN Bus Systems

    Aug 17, 2026Araf Rahman, M Sabbir Salek, Mashrur ChowdhuryNetwork Intrusion DetectionCybersecurity

    Glenn Department of Civil Engineering Clemson University, Clemson, South Carolina, 29634

  3. Digital Twin Degradation: Detecting Cyber Physical Attacks via Temporal Inconsistencies

    Aug 17, 2026Konstantinos E. Kampourakis, Vasileios Gkioulos, Sokratis KatsikasCPS SecurityCybersecurity

    Norwegian University of Science and Technology (NTNU), 2802 Gjøvik, Norway

  4. FirstDiff: One-Step Diffusion-Based Anomaly Detection for Multivariate Time Series via Initial Noise Prediction

    Aug 16, 2026Ali Boudaghi, Alireza Nemati, Hadi ZareTime-Series Anomaly DetectionAnomaly Detection

  5. High-Order Liquid Evidence Modeling for Continuous and Subtle GNSS Spoofing Detection in Autonomous Driving

    Aug 12, 2026Muhammad Ayub Sabir, Junbiao Pang, Fatima AshrafAutonomous DrivingTime-Series Anomaly Detection

    Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China

  6. JAPE: Joint Anomaly Prediction and Intrinsic Explanation in Multivariate Time Series

    Aug 12, 2026Yian Wei, Yuanyuan Yao, Lu Chen +2Interpretable Anomaly DetectionTime-Series Anomaly Detection

    Zhejiang University · RMIT University · Aalborg University

  7. Towards an approach to multivariate outlier detection for District Heating System data

    Aug 11, 2026Rajko Turudija, Dušan Stojiljković, Milan Zdravković +1Isolation ForestIndustrial Anomaly Detection

    Faculty of Mechanical Engineering University of Niš ul. Aleksandra Medvedeva 14, 18000 Niš, Serbia

  8. An Explainable GNN Framework for Component-Level Anomaly Diagnosis

    Aug 10, 2026Sena Ozgunay, Louise Trav{é}-Massuy{è}s, Jean-Michel Loubes +1Industrial Anomaly DetectionRoot Cause Analysis

    Comue de Toulouse, LAAS-DISCO, IMT · Comue de Toulouse, LAAS-DISCO · REGALIA, IMT +1

  9. Agentic Anomaly Detection with ORCA-Style Dynamic Inductive Bias Adaptation in Multimodal Wearable Time Series Data

    Aug 9, 2026Anushka Roy, Jyotirmoy Singh, Shreea Bose +1Multimodal Anomaly DetectionTime-Series Anomaly Detection

    Department of Electrical and Electronics Engineering BITS Pilani, Hyderabad Campus · Department of Computer Science & Information Systems BITS Pilani, Hyderabad Campus · Department of Computer Science & Information Systems2026 BITS Pilani, Hyderabad Campus

  10. A Picture is Worth a Thousand Tokens: How Vision Language Models Cut AI Energy Costs While Improving Accuracy

    Aug 7, 2026Bhavika Jalli, Nikhil Korati Prasanna, Jayanta ChoudhuryVision-Language ModelsEfficient VLM Inference

    Ericsson

  11. Grounded Well-Condition Anomaly Detection on the Volve Field: Constructed Labels, a Baseline, and a Dual-Head Model

    Aug 6, 2026Gospel Bassey, Samuel Bassey, Vincent FakiyesiIndustrial Anomaly DetectionFault Detection

    Independent Researcher. · College of Engineering, Biochemical Engineering. University of Georgia. · College of Engineering, EETI. University of Georgia.

  12. Enhancing Anomaly Resilience in Research Networks: A Large-Scale Forecasting Benchmark for Dynamic Security Baselining

    Aug 6, 2026Mohammad Arafath Uddin Shariff, Byrav RamamurthyNetwork Intrusion DetectionForecasting Benchmarks

    School of Computing University of Nebraska-Lincoln Lincoln, NE, USA

  13. Velocity- and Regime-Aware Detection of Intraday Options Market Manipulation, with Explainable Attribution

    Aug 5, 2026Alex Chen, Maria HybinetteFinancial Fraud DetectionTime-Series Anomaly Detection

    University of Georgia · Athens, GA, USA

  14. PRISM: Powerful Time Series to Image (TS2I) Representations for Multivariate Anomaly Detection

    Aug 4, 2026Mateusz Smendowski, Kamil Faber, Piotr Nawrocki +2Time Series Representation LearningTime-Series Anomaly Detection

    Faculty of Computer Science, AGH University of Krakow, al. A. Mickiewicza 30, 30-059 Krakow, Poland · Department of Computer Science, American University, 4400 Massachusetts Ave NW, Washington, DC 20016, USA

  15. TimeRLM: Recursive Language Models Enable Precise Anomaly Localization in Long-Context Time-Series

    Aug 4, 2026Nicolas Zumarraga, Lorenzo Steno, Ning Wang +9Language ModelingAnomaly Localization

    1Agentic Systems Lab, ETH Zürich · 3Seldon Technologies · 2Stanford University +4

  16. CARE: A Cascaded Framework for Efficient and Reliable Time Series Anomaly Detection

    Aug 3, 2026Zemin Chao, Qianhui Xu, Jianhe Cen +3Efficient Neural Network InferenceCost-Aware Inference

    Massive Data Computing Lab, Harbin Institute of Technology

  17. Behavioral Grammar: Detecting Adaptive Malware via Tiny Language Model Priors and Second-Order Temporal Analysis

    Aug 1, 2026Zihan LuoUnsupervised Anomaly DetectionMalware Analysis

  18. INCLAIR: Inception-Based Longitudinal Clinical Anomaly Detection with Informed Reasoning

    Jul 29, 2026Maxx Richard Rahman, Wolfgang MaassU-StatisticsInterpretable Anomaly Detection

    German Research Center for Artificial Intelligence (DFKI), Germany · Saarland University, Germany

  19. Domain-Prior-Regularized Graph Modeling for Anomaly Detection in Cyber-Physical Systems

    Jul 25, 2026Youngseok Hwang, Joonsung Kwon, Geonwoo Lee +1Cyber-Physical SystemsGraph Representation Learning

    Graduate School of Data Science, Seoul National University, Seoul, South Korea.

  20. Optimizing Transformer Neural Network for Real-Time Outlier Detection on FPGAs

    Jul 24, 2026Ilia Sobakinskikh, Paul Alexander BilokonTransformer InferenceFinancial Time Series

  21. Unsupervised Consensus-Based Anomaly Detection for Spatiotemporal Malaria Incidence in Ghana

    Jul 23, 2026T. Ansah-Narh, Y. Asare AfraneHealthcareUnsupervised Anomaly Detection

    Ghana Space Science and Technology Institute, Ghana Atomic Energy Commission, P. O. Box LG 80, Legon, Accra, Ghana · Department of Medical Microbiology, University of Ghana Medical School, University of Ghana, Accra, Ghana

  22. Adaptive Two-Stage Online Learning for Service-Affecting Failure Detection in Mobile Core Networks

    Jul 20, 2026J. du Toit, G. Fita, J. Salzwedel +2Online Anomaly DetectionWireless Communications

    Department of Electrical and Electronic Engineering, Stellenbosch University, South Africa · Technology Strategy Planning, Architecture & Assurance, Vodacom Group Limited, South Africa · Core Data Networks Performance Management, Vodacom Group Limited, South Africa +1

  23. ClouDens: Operational Context-Aware Anomaly Detection for Large-scale Cloud System Monitoring

    Jul 20, 2026Thu T. H. Doan, Mohammad Saiful Islam, Andriy Miranskyy +3Cloud ComputingTime-Series Anomaly Detection

    Department of Computer Science, Gran Sasso Science Institute, L’Aquila, Italy · Department of Computer Science, Toronto Metropolitan University, Toronto, Canada · Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway +1

  24. Volatility-Aware Extreme Event Detection in High-Frequency Financial Markets

    Jul 20, 2026Maorufa Zaman, Haris Md SahedQuantitative FinanceLimit Order Book Modeling

    Department of Digital Business & Innovation

  25. Knowledge-Assisted Multi-Graph Dependency Learning for Multivariate Time Series Anomaly Detection in Multi-Stage Industrial Processes

    Jul 17, 2026Jaeyeong Lee, Taeseong Yoon, Wonmo Koo +1Graph Structure LearningGraph Representation Learning

    Department of Industrial and Systems Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea

  26. Lightweight Multi-Scale Anomaly Detection for Resource-Constrained Edge Devices

    Jul 14, 2026Raheen Junaid Wani, Smruti R. SarangiAutoencodersEdge Inference

    School of Information Technology Indian Institute of Technology, Delhi New Delhi, India 110016 · Department of Computer Science Indian Institute of Technology, Delhi New Delhi, India 110016

  27. Exploring Zero-Shot Foundation Models for Multivariate Time Series Anomaly Detection

    Jul 14, 2026Martin Uray, Saverio Messineo, Roland Kwitt +1Industrial Anomaly DetectionZero-Shot Anomaly Detection

    Josef Ressel Centre for Intelligent and Secure Industrial Automation, Salzburg University of Applied Sciences, Austria · Department of Artificial Intelligence and Human Interfaces, Paris Lodron University of Salzburg, Austria

  28. Did We Actually Fix It? An Independent Adversarial Stress-Test of Post-Point-Adjustment Evaluation Metrics for Time-Series Anomaly Detection

    Jul 12, 2026Zongye LyuAdversarial RobustnessAutomated Evaluation

    Faculty of Information Technology, Monash University, Melbourne, VIC 3800, Australia

  29. Federated Low-Rank Koopman Learning for Multivariate Time-Series Anomaly Detection in IoT Systems

    Jul 9, 2026Tung-Anh Nguyen, Van-Phuc Bui, Anh Tuyen Le +4Koopman Operator LearningEdge ML

    Faculty of Engineering and IT, University of Technology Sydney, Ultimo, NSW, 2007, Australia · Faculty of Information Technology, FPT University, Vietnam · School of Electrical and Electronic Engineering, Hanoi University of Science and Technology, Vietnam

  30. CAAD: Causality-Aware Multivariate Time Series Anomaly Detection via Multi-Scale Alignment and Structural Causal Consistency

    Jul 9, 2026Xin Wang, Yunshi Wen, Yanan He +4Industrial Anomaly DetectionTime-Series Anomaly Detection

    Stony Brook University · Stony Brook, New York, USA · Rensselaer Polytechnic Institute +4