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Anomaly Detection based on Compressed Data: an Information Theoretic Characterization

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posted on 12.10.2021, 01:26 by Alex MarchioniAlex Marchioni, Andriy Enttsel, Mauro MangiaMauro Mangia, Riccardo Rovatti, Gianluca SettiGianluca Setti
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.

History

Email Address of Submitting Author

alex.marchioni@unibo.it

ORCID of Submitting Author

0000-0002-3441-3634

Submitting Author's Institution

Univarsity of Bologna

Submitting Author's Country

Italy