AbuSniff: Automatic Detection and Defenses Against Abusive Facebook Friends

Adversaries leverage social network friend relationships to collect sensitive data from users and target them with abuse that includes fake news, cyberbullying, malware, and propaganda. Case in point, 71 out of 80 user study participants had at least 1 Facebook friend with whom they never interact, either in Facebook or in real life, or whom they believe is likely to abuse their posted photos or status updates, or post offensive, false or malicious content. We introduce AbuSniff, a system that identifies Facebook friends perceived as strangers or abusive, and protects the user by unfriending, unfollowing, or restricting the access to information for such friends. We develop a questionnaire to detect perceived strangers and friend abuse.We introduce mutual Facebook activity features and show that they can train supervised learning algorithms to predict questionnaire responses. We have evaluated AbuSniff through several user studies with a total of 263 participants from 25 countries. After answering the questio

26 Apr 2018 ... Title:AbuSniff: Automatic Detection and Defenses Against Abusive Facebook Friends. Authors:Sajedul Talukder, Bogdan Carbunar · Download ...

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