Anomaly Detection based on Compressed Data: an Information Theoretic Characterization

Fuente: arXiv
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Autori principali: Marchioni, Alex, Enttsel, Andriy, Mangia, Mauro, Rovatti, Riccardo, Setti, Gianluca
Natura: Preprint
Pubblicazione: 2021
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author Marchioni, Alex
Enttsel, Andriy
Mangia, Mauro
Rovatti, Riccardo
Setti, Gianluca
author_facet Marchioni, Alex
Enttsel, Andriy
Mangia, Mauro
Rovatti, Riccardo
Setti, Gianluca
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2110_02579
institution arXiv
publishDate 2021
record_format arxiv
spellingShingle Anomaly Detection based on Compressed Data: an Information Theoretic Characterization
Marchioni, Alex
Enttsel, Andriy
Mangia, Mauro
Rovatti, Riccardo
Setti, Gianluca
Information Theory
Signal Processing
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.
title Anomaly Detection based on Compressed Data: an Information Theoretic Characterization
topic Information Theory
Signal Processing
url https://arxiv.org/abs/2110.02579