Online Anomaly Detection

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Overview

Online anomaly detection studies how to flag unusual behavior in continuously arriving time series, logs, graphs, and sensor data, often before failures or attacks cause harm. Common approaches include prediction-residual and statistical change detectors, autoencoders and other learned representations, ensembles, and adaptive thresholds; newer systems also use drift detection, continual learning, or test-time adaptation. Work spans settings such as industrial telemetry, cloud logs, networks, and edge devices, where latency, memory, explanations, and operator feedback can matter as much as detection quality. A central tension is that adapting to changing data may help with drift but can add cost or false alarms, and recent benchmarks find that static methods can still outperform streaming ones, underscoring the need for chronological, realistic evaluations.

Latest papers

CardsList

57 papers6 papers in the last four weeks, down 25% on the four weeks before. 0.0% of all new papers.

  1. Online Open-World Wafer Defect Discovery using Hyperdimensional Computing

    Oct 20, 2026Quanling Zhao, Ava Emami, Tsuyoshi Idé +4Online Anomaly DetectionIndustrial Anomaly Detection

    University of California San Diego · IBM Research · Anderon

  2. KPI-Aware Multimodal Anomaly Detection for 5G and Open RAN Telemetry

    Oct 18, 2026Chiman Salavati, Liang Wu, Kelly Wan +2Multimodal Anomaly DetectionTime-Series Anomaly Detection

    University of Connecticut, Storrs, Connecticut, USA · Nokia, Sunnyvale, California, USA

  3. Distinguishing Process Change, Instrument Fault and Data-Path Corruption in Streaming Telemetry: A Reference Implementation and Benchmark

    Oct 11, 2026Oleksandr KlymenkoFault DiagnosisOnline Anomaly Detection

    Independent Researcher, Poland

  4. Smart Sensing for Safer Bridges: From Sensor Signals to AI-Driven Anomaly Detection

    Oct 2, 2026Rahul Jaiswal, Joakim Hellum, Halvor HeibergOnline Anomaly DetectionTime-Series Anomaly Detection

    Smart Sensor Systems AS Oslo, Norway

  5. What Streaming Anomaly Detection Finds (and Misses) in Industrial Time Series

    Sep 30, 2026Magali Parrino, Antoine Ajenjo, Emmanuel Remy +2Online Anomaly DetectionIndustrial Anomaly Detection

    EDF R&D, France · Inria, ENS, CNRS, PSL, France

  6. In a Streaming World, Should You Stand Still? A Comprehensive Benchmark of Anomaly Detection in Streams

    Sep 30, 2026Magali Parrino, Antoine Ajenjo, Emmanuel Remy +3Online Anomaly DetectionConcept Drift

    EDF R&D Chatou, France · ENS, PSL University, CNRS, Inria Paris, France · DI ENS, ENS, PSL University, CNRS, Inria Paris, France

  7. DynGraphAgentBench: A Benchmark for Agentic Lifecycle Control in Dynamic Graph Anomaly Detection

    Sep 27, 2026Yuwei Han, Lingwei Wei, Wooseong Yang +4Online Anomaly DetectionAI Agent Benchmarks

  8. Continuous Online Fault Detection for Mobile Robots via Adaptive Edge Models

    Sep 24, 2026Jordan Levy, Nicolas Verstaevel, Vincent Talon +1Robot Failure DetectionOnline Anomaly Detection

    IRIT, Université Toulouse Capitole, Toulouse, France · TwinswHeel, Soben, France

  9. Collaborative Streaming Anomaly Detection with Interactive Explanations and Ensemble Consensus

    Sep 20, 2026Diogo Risca, Afonso Lourenço, Ricardo Martins +1Online Anomaly DetectionInterpretable Anomaly Detection

    GECAD, ISEP, Polytechnic of Porto, Portugal · SISTRADE Software Consulting, Porto, Portugal

  10. What a gated sensing pipeline never looks at: bandwidth reduction and the misses behind it

    Sep 14, 2026Raghu Venkat, Tricha AnjaliActive PerceptionOnline Anomaly Detection

    Numberz.ai Inc., Alpharetta, GA

  11. TriCalRAG: A Three-Strategy, Retrieval-Augmented Benchmark for On-Premise LLM-Based Root Cause Analysis in AIOps

    Sep 13, 2026Rohit Patel, Susil Kumar Mohanty, Jeenal ChaudharyLLM Inference EfficiencyRetrieval-Augmented Generation

    Department of Computer Science and Engineering Indian Institute of Technology Jodhpur, Jodhpur, India

  12. Optimal Transport for Efficient, Unsupervised Anomaly Detection on Industrial Data

    Sep 12, 2026Abigail Langbridge, Fearghal O'Donncha, James T Rayfield +1Anomaly DetectionIndustrial Anomaly Detection

    Dyson School of Design Engineering Imperial College London* United Kingdom · AI for Sustainable Industry IBM Research Europe Dublin, Ireland · IBM T.J. Watson Research Center IBM Research NY, USA

  13. Structure-Aware Unsupervised Anomaly Detection for Spacecraft Telemetry with Adaptive EVT Thresholding

    Sep 9, 2026Óscar Alcarria, Rafael Sánchez, Javier Sempere +5Online Anomaly DetectionFault Detection

    Universidad de Castilla-La Mancha, Albacete, Spain · GMV GmbH, Darmstadt, Germany · GMV, Madrid, Spain

  14. Real-time and adaptive anomaly detection algorithm for cyclostationary models

    Sep 8, 2026Justyna Witulska, Tomasz Barszcz, Ireneusz Jabłoński +1Online Anomaly DetectionIndustrial Anomaly Detection

    Faculty of Pure and Applied Mathematics and Hugo Steinhaus Center, Wrocław University of Science and Technology, Wrocław, 50-370, Poland · AGH University, Kraków, 30-059, Poland · Faculty of MINT, Brandenburg University of Technology, Cottbus, 03046, Germany

  15. RankShift: In-Database Detection and Explanation of Categorical Shifts

    Aug 28, 2026Omair Shafi AhmedDistribution Shift DetectionOnline Anomaly Detection

    Microsoft

  16. Single State Update Predictive Coding training for Time Series Forecasting and Anomaly Detection

    Aug 25, 2026Matteo Cardoni, Sam LerouxPredictive CodingOnline Anomaly Detection

    IDLab, Department of Information and Technology, Ghent University—imec, 9052 Ghent, Belgium

  17. Online Test-Time Adaptation for Generalizable Dynamic Graph Anomaly Detection

    Aug 20, 2026Jialun Zheng, Hanchen Yang, Jiannong Cao +3Anomaly DetectionTest-Time Adaptation

    Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China · Department of Computer Science, University of Illinois at Chicago (UIC), Chicago, IL, USA · Institute of Information Processing and Automation, Zhejiang University of Technology, Zhejiang, China

  18. Too Sure to Be Safe: Model Calibration for Reliable Log Anomaly Detection

    Aug 18, 2026Bin Li, Dongdong Wang, Siyang LuPost-Hoc CalibrationOnline Anomaly Detection

    School of Cyberspace Science and Technology, Beijing Jiaotong University, Beijing, China · University of Florida, Gainesville, FL, USA · School of Computer and Technology, Beijing Jiaotong University, Beijing, China

  19. Beat the Counter First: A Baseline for Temporal-Graph Anomaly Detectors

    Aug 16, 2026Omair Shafi Ahmed, Zohair ShafiGraph-Based Anomaly DetectionAnomaly Detection

    Microsoft · Northeastern University

  20. Memory-Bounded Continuation of Greedy Sampling for Continual Anomaly Detection

    Aug 15, 2026Yoon Gyo Jung, Jaewoo Park, Kuan-Chuan Peng +2Continual Anomaly DetectionAnomaly Detection

    Electrical and Computer Engineering Department Northeastern University Boston, MA, USA · AIVEX Inc. Seoul, South Korea · Mitsubishi Electric Research Laboratories (MERL) Cambridge, MA, USA

  21. Stylometric Defenses Against Author Impersonation in Software Repositories

    Aug 3, 2026Leonid Ravich, Michael FireOnline Anomaly DetectionStylometry

    Ben-Gurion University of the Negev, Computer Science Department

  22. Exploring Block Anomaly Detection In HDFS Log Data Analysis

    Jul 31, 2026WenYang Zhong, Tutut HerawanOnline Anomaly DetectionAnomaly Detection

    Department of Information Systems Faculty Of Computer Science And Information Technology Universiti Malaya, 50603 Kuala Lumpur, Malaysia

  23. Panda: Unsupervised Pelvic Anomaly Detection for Real-Time MR Imaging

    Jul 27, 2026Anika Knupfer, Maximilian Lindholz, Johanna Paula Müller +4Online Anomaly DetectionMedical Image Anomaly Detection

    Institute of Information Processing, Leibniz University Hannover, Hannover, Germany · CAIMED, L3S, Hannover, Germany · Department of Radiology, Charité Universitätsmedizin Berlin, Berlin, Germany +2

  24. Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models

    Jul 23, 2026Shoya Otsu, Kei Suzuki, Toshiaki Koike-Akino +2Online Anomaly DetectionLLMs for Cybersecurity

    Mitsubishi Electric Corporation, Japan. · Mitsubishi Electric Research Laboratories, Cambridge, MA, USA.

  25. Classical Hardware Acceleration of Quantum Autoencoders for Real-Time Anomaly Detection in Collider Experiments

    Jul 22, 2026Ivan Ge, Sagar Addepalli, Abhilasha Dave +1Online Anomaly DetectionQuantum Machine Learning

    Department of Physics, Stanford University, 450 Jane Stanford Way, Stanford, 94305, CA, USA. · SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, 94025, CA, USA.

  26. 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

  27. Clean-Reference Streaming Detection of Lens Occlusion and Photometric Transitions for Camera Tamper Monitoring

    Jul 16, 2026Bo Ma, WeiQi Yan, Jinsong WuOnline Anomaly DetectionFault Detection

    Auckland University of Technology, Auckland 1024, New Zealand · Guilin University of Electronic Technology, Guilin, China

  28. OOD-RL-Bench: A Benchmark Framework for Out-of-Distribution Detection in Reinforcement Learning

    Jul 14, 2026Emil Mittag, Richard Dazeley, Peter VamplewRL BenchmarksOnline Anomaly Detection

    Deakin University, Geelong, Victoria, 3220, Australia · Federation University Australia, Ballarat, Victoria, 3350, Australia

  29. Self-Adaptive Anomaly Detection with Reinforcement Learning and Human Feedback in Connected Vehicles

    Jul 9, 2026Matthias Weiß, Athreya Hosahalli Prakash, Maurice Artelt +3Online Anomaly DetectionConcept Drift

    Institute of Industrial Automation and Software Engineering (IAS), University of Stuttgart, Pfaffenwaldring 47, 70550 Stuttgart, Germany

  30. Predictive Conformal Slip Monitoring: An Empirical Evaluation of Rolling Split Conformal Prediction for Pre-Incident Traction Loss Detection

    Jul 2, 2026Varshith Roy KotlaOnline Anomaly DetectionConformal Prediction

    Department of CSE, Faculty of Science and Technology, The ICFAI Foundation for Higher Education, Hyderabad, India