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CODiT: Conformal Out-of-Distribution Detection in Time-Series Data for Cyber-Physical Systems

Published: 09 May 2023 Publication History

Abstract

Uncertainty in the predictions of learning enabled components hinders their deployment in safety-critical cyber-physical systems (CPS). A shift from the training distribution of a learning enabled component (LEC) is one source of uncertainty in the LEC's predictions. Detection of this shift or out-of-distribution (OOD) detection on individual datapoints has therefore gained attention recently. But in many applications, inputs to CPS form a temporal sequence. Existing techniques for OOD detection in time-series data for CPS either do not exploit temporal relationships in the sequence or do not provide any guarantees on detection. We propose using deviation from the in-distribution temporal equivariance as the non-conformity measure in conformal anomaly detection framework for OOD detection in time-series data for CPS. Computing independent predictions from multiple conformal detectors based on the proposed measure and combining these predictions by Fisher's method leads to the proposed detector CODiT with bounded false alarms. We illustrate the efficacy of CODiT by achieving state-of-the-art results in autonomous driving systems with perception (or vision) LEC. We also perform experiments on medical CPS for GAIT analysis where physiological (non-vision) data is collected with force-sensitive resistors attached to the subject's body. Code, data, and trained models are available at https://github.com/kaustubhsridhar/time-series-OOD

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Cited By

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  • (2024)Out-of-distribution Detection in Dependent Data for Cyber-physical Systems with Conformal GuaranteesACM Transactions on Cyber-Physical Systems10.1145/36480058:4(1-27)Online publication date: 26-Oct-2024
  • (2024)Memory-based Distribution Shift Detection for Learning Enabled Cyber-Physical Systems with Statistical GuaranteesACM Transactions on Cyber-Physical Systems10.1145/36438928:2(1-28)Online publication date: 15-May-2024
  • (2024)Evaluating the Utility of Conformal Prediction Sets for AI-Advised Image LabelingProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642446(1-19)Online publication date: 11-May-2024
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cover image ACM Conferences
ICCPS '23: Proceedings of the ACM/IEEE 14th International Conference on Cyber-Physical Systems (with CPS-IoT Week 2023)
May 2023
291 pages
ISBN:9798400700361
DOI:10.1145/3576841
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 09 May 2023

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Author Tags

  1. learning enabled components
  2. uncertainty
  3. cyber-physical systems
  4. time-series
  5. out-of-distribution
  6. conformal detection

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  • Research-article

Funding Sources

  • Army Research Office
  • U.S. Army Research Laboratory Cooperative Research Agreement
  • Air Force Research Laboratory and Defense Advanced Research Projects Agency

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ICCPS '23
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Overall Acceptance Rate 25 of 91 submissions, 27%

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Cited By

View all
  • (2024)Out-of-distribution Detection in Dependent Data for Cyber-physical Systems with Conformal GuaranteesACM Transactions on Cyber-Physical Systems10.1145/36480058:4(1-27)Online publication date: 26-Oct-2024
  • (2024)Memory-based Distribution Shift Detection for Learning Enabled Cyber-Physical Systems with Statistical GuaranteesACM Transactions on Cyber-Physical Systems10.1145/36438928:2(1-28)Online publication date: 15-May-2024
  • (2024)Evaluating the Utility of Conformal Prediction Sets for AI-Advised Image LabelingProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642446(1-19)Online publication date: 11-May-2024
  • (2024)Graph-Attention Diffusion for Enhanced Multivariate Time-Series Anomaly DetectionIEEE Open Journal of the Industrial Electronics Society10.1109/OJIES.2024.35010145(1353-1364)Online publication date: 2024
  • (2024)Online Distribution Shift Detection via Recency Prediction2024 IEEE International Conference on Robotics and Automation (ICRA)10.1109/ICRA57147.2024.10611114(16251-16263)Online publication date: 13-May-2024
  • (2024)Efficient Spatio-Temporal Out-of-Distribution Detection for Autonomous Systems2024 4th International Conference on Intelligent Technology and Embedded Systems (ICITES)10.1109/ICITES62688.2024.10777452(220-226)Online publication date: 20-Sep-2024
  • (2024)Generalized Out-of-Distribution Detection: A SurveyInternational Journal of Computer Vision10.1007/s11263-024-02117-4132:12(5635-5662)Online publication date: 23-Jun-2024
  • (2023)Lightning Talk: Trinity - Assured Neuro-symbolic Model Inspired by Hierarchical Predictive Coding2023 60th ACM/IEEE Design Automation Conference (DAC)10.1109/DAC56929.2023.10247803(1-2)Online publication date: 9-Jul-2023

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