eprintid: 1470859
rev_number: 36
eprint_status: archive
userid: 608
dir: disk0/01/47/08/59
datestamp: 2015-11-06 16:02:27
lastmod: 2021-09-26 22:10:44
status_changed: 2017-05-23 16:30:37
type: article
metadata_visibility: show
creators_name: Egele, M
creators_name: Stringhini, G
creators_name: Kruegel, C
creators_name: Vigna, G
title: Towards Detecting Compromised Accounts on Social Networks
ispublished: pub
divisions: UCL
divisions: B04
divisions: C05
divisions: F48
keywords: Twitter, feature extraction, facebook, training, reliability, uniform resource locators
note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
© 2015 IEEE.
abstract: Compromising social network accounts has become a profitable course of action for cybercriminals. By hijacking control of a popular media or business account, attackers can distribute their malicious messages or disseminate fake information to a large user base. The impacts of these incidents range from a tarnished reputation to multi-billion dollar monetary losses on financial markets. In our previous work, we demonstrated how we can detect large-scale compromises (i.e., so-called campaigns) of regular online social network users. In this work, we show how we can use similar techniques to identify compromises of individual high-profile accounts. High-profile accounts frequently have one characteristic that makes this detection reliable -- they show consistent behavior over time. We show that our system, were it deployed, would have been able to detect and prevent three real-world attacks against popular companies and news agencies. Furthermore, our system, in contrast to popular media, would not have fallen for a staged compromise instigated by a US restaurant chain for publicity reasons.
date: 2017-07
official_url: http://dx.doi.org/10.1109/TDSC.2015.2479616
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1051501
doi: 10.1109/TDSC.2015.2479616
lyricists_name: Stringhini, Gianluca
lyricists_id: GSTRI63
actors_name: Stringhini, Gianluca
actors_id: GSTRI63
actors_role: owner
full_text_status: public
publication: IEEE Transactions on Dependable and Secure Computing (TDSC)
volume: 14
number: 4
pagerange: 447-460
issn: 1545-5971
citation:        Egele, M;    Stringhini, G;    Kruegel, C;    Vigna, G;      (2017)    Towards Detecting Compromised Accounts on Social Networks.                   IEEE Transactions on Dependable and Secure Computing (TDSC) , 14  (4)   pp. 447-460.    10.1109/TDSC.2015.2479616 <https://doi.org/10.1109/TDSC.2015.2479616>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/1470859/1/thjp.pdf