The insider on the outside: a novel system for the detection of information leakers in social networks

Giuseppe Cascavilla, Mauro Conti, David G. Schwartz, Inbal Yahav*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Confidential information is all too easily leaked by naive users posting comments. In this paper we introduce DUIL, a system for Detecting Unintentional Information Leakers. The value of DUIL is in its ability to detect those responsible for information leakage that occurs through comments posted on news articles in a public environment, when those articles have withheld material non-public information. DUIL is comprised of several artefacts, each designed to analyse a different aspect of this challenge: the information, the user(s) who posted the information, and the user(s) who may be involved in the dissemination of information. We present a design science analysis of DUIL as an information system artefact comprised of social, information, and technology artefacts. We demonstrate the performance of DUIL on real data crawled from several Facebook news pages spanning two years of news articles.

Original languageEnglish
Pages (from-to)470-485
Number of pages16
JournalEuropean Journal of Information Systems
Volume27
Issue number4
DOIs
StatePublished - 4 Jul 2018
Externally publishedYes

Funding

FundersFunder number
Detection and Prevention
Innovative Machine Learning Techniques?
Israel Ministry of Science and Technology
University of Padua
Cancer Center for Detection and Prevention
European CommissionPCIG11-GA-2012-321980
Ministero dell’Istruzione, dell’Università e della Ricerca
Università degli Studi di Padova
Ministry of Science and Technology, Israel

    Keywords

    • Cybersecurity
    • design science research
    • information leakers
    • online social networks
    • sensitive information
    • threat detection

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