Indirect information linkage for OSINT through authorship analysis of aliases

Robert Layton, Charles Perez, Babiga Birregah, Paul Watters, Marc Lemercier

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

11 Citations (Scopus)

Abstract

In this paper we examine the problem of automatically linking online accounts for open source intelligence gathering. We specifically aim to determine if two social media accounts are shared by the same author, without the use of direct linking evidence. We profile the accounts using authorship analysis and find the best matching guess. We apply this to a series of Twitter accounts identified as malicious by a methodology named SPOT and find several pairs of accounts that belong to the same author, despite no direct evidence linking the two. Overall, our results show that linking aliases is possible with an accuracy of 84%, and using our automated threshold method improves our accuracy to over 90% by removing incorrectly discovered matches.

Original languageEnglish
Title of host publicationTrends and applications in knowledge discovery and data mining
Subtitle of host publicationPAKDD 2013 International Workshops: DMApps, DANTH, QIMIE, BDM, CDA, CloudSD: revised selected papers
EditorsJiuyong Li, Longbing Cao, Can Wang, Kay Chen Tan, Bo Liu, Jian Pei, Vincent S. Tseng
Place of PublicationBerlin ; Heidelberg
PublisherSpringer, Springer Nature
Pages36-46
Number of pages11
ISBN (Electronic)9783642403194
ISBN (Print)9783642403187
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event17th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2013 - Gold Coast, QLD, Australia
Duration: 14 Apr 201317 Apr 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer
Volume7867
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other17th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2013
Country/TerritoryAustralia
CityGold Coast, QLD
Period14/04/1317/04/13

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