Concept Drift

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Overview

Concept drift studies how changing data patterns or target relationships affect models after deployment, especially in streams such as network traffic, malware, and time-series forecasts. Methods detect changes using prediction errors, statistical tests such as MMD and CUSUM, or shifts in representations, then respond through retraining, online updates, ensembles, replay, or memory of recurring regimes. Evaluation uses synthetic streams with controlled abrupt, gradual, and recurring shifts alongside chronological real-world benchmarks, often measuring detection delay, accuracy, labeling needs, and computational cost. A central challenge is balancing quick adaptation against retaining useful knowledge: model updates can hide drift from error-based detectors, while weak signals, delayed labels, false alarms, and limited budgets complicate reliable intervention.

Latest papers

CardsList

92 papers11 papers in the last four weeks, up 38% on the four weeks before. 0.1% of all new papers.

  1. DRIFT: Drift-Resilient Invariant-Feature Transformer for DGA Detection

    May 11, 2026Chaeyoung Lee, Chaeri Jung, Seonghoon JeongTransformerConcept Drift

    Division of Artificial Intelligence Engineering Sookmyung Women’s University Seoul, Republic of Korea

  2. Causal Parametric Drift Simulation: A Digital Twin Framework for Classifier Robustness Evaluation

    May 10, 2026Julien Lafrance, Richard Khoury, Véronique TremblayConcept Drift

    Laval University

  3. Robust and Reliable AI for Predictive Quality in Semiconductor Materials Manufacturing with MLOps and Uncertainty Quantification

    May 8, 2026Min Gao, Julia Maria Perathoner, Anton Ludwig Bonin +2Concept DriftSemiconductor Manufacturing

    Merck Group, Versum Materials US LLC, Wilmington, USA · Merck Group, Merck Electronics KGaA, Darmstadt, Germany · Technical University of Darmstadt, Darmstadt, Germany +1

  4. McNdroid: A Longitudinal Multimodal Benchmark for Robust Drift Detection in Android Malware

    May 7, 2026Md Mahmuduzzaman Kamol, Jesus Lopez, Saeefa Rubaiyet Nowmi +5Concept DriftAndroid Malware Detection

    Department of Computer Science, University of Texas at El Paso · CrowdStrike

  5. Autonomous Drift Learning in Data Streams: A Unified Perspective

    May 2, 2026Xiaoyu Yang, En Yu, Jie LuConcept DriftContinual Learning

    Australian Artificial Intelligence Institute (AAII), Faculty of Engineering and Information Technology, University of Technology Sydney, Australia

  6. Self-Supervised Learning for Android Malware Detection on a Time-Stamped Dataset

    Apr 24, 2026Annan Fu, Hao Pei, Maryam TanhaConcept DriftAndroid Malware Detection

    Khoury College of Computer Sciences Northeastern University Vancouver, Canada

  7. Detecting Concept Drift in Evolving Malware Families Using Rule-Based Classifier Representations

    Apr 24, 2026Tomáš Kalný, Martin Jureček, Mark StampConcept DriftRule-Based Classification

    Faculty of Information Technology Czech Technical University, Thakurova 9, Prague, Czech · Department of Computer Science, San Jose State University, San Jose, CA, USA

  8. Adversarial Evasion in Non-Stationary Malware Detection: Minimizing Drift Signals through Similarity-Constrained Perturbations

    Apr 23, 2026Pawan Acharya, Lan ZhangConcept DriftAdversarial Attacks

    Northern Arizona University, Flagstaff, AZ, USA

  9. Catching Every Ripple: Enhanced Anomaly Awareness via Dynamic Concept Adaptation

    Apr 16, 2026Jiaqi Zhu, Shaofeng Cai, Jie Chen +3Online Anomaly DetectionConcept Drift

    School of Automation and the National Key Laboratory of Autonomous Intelligent Unmanned Systems, Beijing Institute of Technology, Beijing 100081, China · School of Computing, National University of Singapore, Singapore 117417 · Harbin Institute of Technology, Harbin 150001, China +2

  10. Robust Semi-Supervised Temporal Intrusion Detection for Adversarial Cloud Networks

    Apr 14, 2026Anasuya Chattopadhyay, Daniel Reti, Hans D. SchottenNetwork Intrusion DetectionCybersecurity

    German Research Center for Artificial Intelligence (DFKI), Germany · RPTU University Kaiserslautern-Landau, Germany

  11. GeM-EA: A Generative and Meta-learning Enhanced Evolutionary Algorithm for Streaming Data-Driven Optimization

    Apr 14, 2026Yue Wu, Yuan-Ting Zhong, Ze-Yuan Ma +1Evolutionary OptimizationSurrogate-Assisted Optimization

    South China University of Technology, Guangzhou, China

  12. Drift-Aware Online Dynamic Learning for Nonstationary Multivariate Time Series: Application to Sintering Quality Prediction

    Apr 10, 2026Yumeng Zhao, Shengxiang Yang, Xianpeng WangNon-Stationary Time Series ForecastingConcept Drift

    the National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Northeastern University, Shenyang, China · De Montfort University, Leicester, U.K. · Innovative Artificial Intelligence Cluster, Digital Future Institute, De Montfort University, Leicester, U.K. +1

  13. Chameleons do not Forget: Prompt-Based Online Continual Learning for Next Activity Prediction

    Apr 1, 2026Marwan Hassani, Tamara Verbeek, Sjoerd van StratenNext-Action PredictionPredictive Process Monitoring

    Department of Mathematics and Computer Science, Eindhoven University of Technology, The Netherlands

  14. Label-efficient Training Updates for Malware Detection over Time

    Mar 30, 2026Luca Minnei, Cristian Manca, Giorgio Piras +6Malware DetectionActive Learning

    Department of Electrical and Electronic Engineering, University of Cagliari, Italy · Department of Computer, Control and Management Engineering, Sapienza University, Rome, Italy · CINI, Rome, Italy

  15. Epistemic Compression: The Case for Deliberate Ignorance in High-Stakes AI

    Mar 26, 2026Steffen LukasDistribution Shift RobustnessModel Selection

    Charité – Universitätsmedizin Berlin, Germany

  16. Unlearning-based sliding window for continual learning under concept drift

    Mar 15, 2026Michal Wozniak, Marek Klonowski, Maciej Maczynski +1Task-Free Continual LearningConcept Drift

    Wroclaw University of Science and Technology Wrocław, Poland · Rochester Institute of Technology NY, USA

  17. Fingerprinting Concepts in Data Streams with Supervised and Unsupervised Meta-Information

    Mar 11, 2026Ben Halstead, Yun Sing Koh, Patricia Riddle +3Semantic Representation LearningConcept Drift

    University of Auckland · Eindhoven University of Technology · University of Waikato and LTCI, Télécom Paris, IP-Paris +1

  18. Dynamic Multi-period Experts for Online Time Series Forecasting

    Mar 10, 2026Seungha Hong, Sukang Chae, Suyeon Kim +2Online Time Series ForecastingTime Series Forecasting

    Pohang University of Science and Technology, Pohang, Republic of Korea · Kyungpook National University, Daegu, Republic of Korea

  19. When to Retrain after Drift: A Data-Only Test of Post-Drift Data Size Sufficiency

    Mar 9, 2026Ren Fujiwara, Yasuko Matsubara, Yasushi SakuraiConcept DriftDrifting Models

    SANKEN, The University of Osaka, Japan

  20. MAcPNN: Mutual Assisted Learning on Data Streams with Temporal Dependence

    Mar 9, 2026Federico Giannini, Emanuele Della ValleOnline Continual LearningDecentralized Learning

    DEIB, Politecnico di Milano, Milano, Italy

  21. Don't Look Back in Anger: MAGIC Net for Streaming Continual Learning with Temporal Dependence

    Mar 9, 2026Federico Giannini, Sandro D'Andrea, Emanuele Della ValleContinual LearningOnline Continual Learning

    DEIB - Politecnico di Milano

  22. Learning Unbiased Cluster Descriptors for Interpretable Imbalanced Concept Drift Detection

    Mar 6, 2026Yiqun Zhang, Zhanpei Huang, Mingjie Zhao +5Concept DriftDistribution Shift Detection

    the School of Computer Science and Technology, Guangdong University of Technology, Guangzhou 510006, China · the Department of Computer Science, Hong Kong Baptist University, Hong Kong SAR, China · the Key Laboratory of Multimedia Trusted Perception and Efficient Computing, Ministry of Education of China, Xiamen University, Xiamen 361000, China +1

  23. Algorithmic Compliance and Regulatory Loss in Digital Assets

    Mar 4, 2026Khem Raj Bhatt, Krishna SharmaAnti-Money LaunderingAnti-Money Laundering Detection

  24. cPNN: Continuous Progressive Neural Networks for Evolving Streaming Time Series

    Mar 3, 2026Federico Giannini, Giacomo Ziffer, Emanuele Della ValleOnline Continual LearningConcept Drift

    DEIB, Politecnico di Milano, Milano, Italy

  25. When Should a Model Change Its Mind? An Energy-Based Theory and Regularizer for Concept Drift in Electrocardiogram (ECG) Signals

    Feb 25, 2026Timothy Oladunni, Blessing Ojeme, Kyndal Maclin +1Concept DriftElectrocardiography

    Department of Computer Science, Morgan State University, Baltimore, MD, USA.

  26. CaDrift: A Time-dependent Causal Generator of Drifting Data Streams

    Feb 23, 2026Eduardo V. L. Barboza, Jean Paul Barddal, Robert Sabourin +1Synthetic Data GenerationSynthetic Benchmark Generation

    LIVIA, École de Technologie Supérieure (ÉTS), Université du Québec, Montreal, QC, Canada · Graduate Program in Informatics (PPGIa), Pontifícia Universidade Católica do Paraná (PUCPR), Curitiba, PR, Brazil

  27. Drift Localization using Conformal Predictions

    Feb 23, 2026Fabian Hinder, Valerie Vaquet, Johannes Brinkrolf +1Concept DriftDistribution Shift Detection

    Bielefeld University—Faculty of Technology Inspiration 1, 33619 Bielefeld—Germany

  28. Monitoring the calibration of probability forecasts with an application to concept drift detection involving image classification

    Oct 29, 2025Christopher T. Franck, Anne R. Driscoll, Zoe Szajnfarber +1Concept DriftModel Calibration

  29. On the Reliability and Stability of Selective Methods in Malware Classification Tasks

    May 28, 2025Alexander Herzog, Aliai Eusebi, Lorenzo CavallaroMalware ClassificationSelective Prediction

    University College London and core64 London, United Kingdom · University College London London, United Kingdom

  30. Joint Detection of Fraud and Concept Drift inOnline Conversations with LLM-Assisted Judgment

    May 7, 2025Ali Şenol, Garima Agrawal, Huan LiuOnline Anomaly DetectionConcept Drift

    School of Computing and Augmented Intelligence, Arizona State University, Tempe, 85281, AZ, USA. · Department of Computer Engineering, Tarsus University, Takbaş M. Kartaltepe S., Tarsus, 33400, Mersin, Türkiye. · HumaConn AI Consulting, Arizona, USA.