Detecting Hacked Twitter Accounts based on Behavioural Change

Meike Nauta, Mena Badieh Habib, Maurice van Keulen

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

3 Citations (Scopus)
774 Downloads (Pure)

Abstract

Social media accounts are valuable for hackers for spreading phishing links, malware and spam. Furthermore, some people deliberately hack an acquaintance to damage his or her image. This paper describes a classification for detecting hacked Twitter accounts. The model is mainly based on features associated with behavioural change such as changes in language, source, URLs, retweets, frequency and time. We experiment with a Twitter data set containing tweets of more than 100 Dutch users including 37 who were hacked. The model detects 99% of the malicious tweets which proves that behavioural changes can reveal a hack and that anomaly-based features perform better than regular features. Our approach can be used by social media systems such as Twitter to automatically detect a hack of an account only a short time after the fact allowing the legitimate owner of the account to be warned or protected, preventing reputational damage and annoyance.
Original languageEnglish
Title of host publicationProceedings of the 13th International Conference on Web Information Systems and Technologies (WEBIST 2017)
Subtitle of host publication19-31, 2017, Porto, Portugal
EditorsTim A. Majchrzak, Paolo Traverso, Karl-Heinz Krempels, Valérie Monfort
PublisherINSTICC Institute for Systems and Technologies of Information, Control and Communication
Pages19-31
ISBN (Print)978-989-758-246-2
DOIs
Publication statusPublished - Apr 2017
Event13th International Conference on Web Information Systems and Technologies, WEBIST 2017 - Porto, Portugal
Duration: 25 Apr 201727 Apr 2017
Conference number: 13

Conference

Conference13th International Conference on Web Information Systems and Technologies, WEBIST 2017
Abbreviated titleWEBIST
CountryPortugal
CityPorto
Period25/04/1727/04/17

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