6533b835fe1ef96bd129f70f
RESEARCH PRODUCT
Assisted labeling for spam account detection on twitter
Marco MoranaFederico ConconeGiuseppe Lo ReClaudio Ruoccosubject
Social network021110 strategic defence & security studiesInformation retrievalSocial networkbusiness.industryComputer scienceSpam detectionSmart device0211 other engineering and technologies020206 networking & telecommunicationsUsability02 engineering and technologycomputer.software_genrePhishinglaw.inventionManual annotationlawComputer security0202 electrical engineering electronic engineering information engineeringBlacklistingMalwarebusinessCluster analysiscomputerdescription
Online Social Networks (OSNs) have become increasingly popular both because of their ease of use and their availability through almost any smart device. Unfortunately, these characteristics make OSNs also target of users interested in performing malicious activities, such as spreading malware and performing phishing attacks. In this paper we address the problem of spam detection on Twitter providing a novel method to support the creation of large-scale annotated datasets. More specifically, URL inspection and tweet clustering are performed in order to detect some common behaviors of spammers and legitimate users. Finally, the manual annotation effort is further reduced by grouping similar users according to some characteristics. Experimental results show the effectiveness of the proposed approach.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2019-06-01 |