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Anomaly Detection based on Compressed Data: an Information Theoretic Characterization
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  • Alex Marchioni ,
  • Andriy Enttsel ,
  • Mauro Mangia ,
  • Riccardo Rovatti ,
  • Gianluca Setti
Alex Marchioni
Univarsity of Bologna

Corresponding Author:[email protected]

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Andriy Enttsel
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Mauro Mangia
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Riccardo Rovatti
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Gianluca Setti
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We analyze the effect of lossy compression in the processing of sensor signals that must be used to detect anomalous events in the system under observation. The intuitive relationship between the quality loss at higher compression and the possibility of telling anomalous behaviours from normal ones is formalized in terms of information-theoretic quantities. Some analytic derivations are made within the Gaussian framework and possibly in the asymptotic regime for what concerns the stretch of signals considered.
Analytical conclusions are matched with the performance of practical detectors in a toy case allowing the assessment of different compression/detector configurations.
2023Published in IEEE Transactions on Systems, Man, and Cybernetics: Systems on pages 1-16. 10.1109/TSMC.2023.3299169