Hunting the Unknown

Elisa Constante, Jeremy den Hartog, M. Petkovic, Sandro Etalle, Mykola Pechenizkiy

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    11 Citations (Scopus)
    24 Downloads (Pure)


    Data leakage causes significant losses and privacy breaches worldwide. In this paper we present a white-box data leakage detection system to spot anomalies in database transactions. We argue that our approach represents a major leap forward w.r.t. previous work because: i) it significantly decreases the False Positive Rate (FPR) while keeping the Detection Rate (DR) high; on our experimental dataset, consisting of millions of real enterprise transactions, we measure a FPR that is orders of magnitude lower than in state-of-the-art comparable approaches; and ii) the white-box approach allows the creation of self-explanatory and easy to update profiles able to explain why a given query is anomalous, which further boosts the practical applicability of the system.
    Original languageUndefined
    Title of host publication28th Annual IFIP WG 11.3 Working ConferenceData and Applications Security and Privacy (DBSec)
    Place of PublicationBerlin
    Number of pages17
    ISBN (Print)978-3-662-43936-4
    Publication statusPublished - 2014

    Publication series

    NameLecture Notes in Computer Science


    • EWI-25142
    • SCS-Cybersecurity
    • Privacy
    • IR-92125
    • Data Security
    • Leakage Detection
    • METIS-306060
    • Anomaly Detection

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