Towards Privacy-anomaly Detection: Discovering Correlation between Privacy and Security-anomalies
Author(s) -
Muhammad Imran Khan,
Simon N. Foley,
Barry O’Sullivan
Publication year - 2020
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2020.07.048
Subject(s) - computer science , anonymity , anomaly (physics) , anomaly detection , normative , information privacy , computer security , internet privacy , data mining , law , physics , political science , condensed matter physics
In this paper a notion of privacy-anomaly detection is presented where normative privacy is modelled using k-anonymity. Based on the model, normative privacy-profiles are constructed, and deviation from normative privacy-profile at runtime is labelled as a privacy-anomaly. Furthermore, the paper investigates whether there is a correlation between security-anomalies and privacy-anomalies, that is, whether the privacy-anomalies labelled by privacy-anomaly detection system are detected by conventional security-anomaly detection system used for detecting malicious accesses to databases by insiders.
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