Detection of Users’ Abnormal Behavior on Social Networks

  • Nour El Houda Ben Chaabene
  • , Amel Bouzeghoub
  • , Ramzi Guetari
  • , Samar Balti
  • , Henda Hajjami Ben Ghezala

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

Abstract

In just a few years, social networking sites have become the most popular landmarks on the Internet. They revolutionized the way we communicate, and socialized the Web. However, while it is now impossible to deny their impact, it can take a variety of forms, not all of them are positive. As a result, the detection of anomalies on social networks is a topic of current research that has attracted researchers since the 2000s. This problem is of crucial importance to prevent abnormal activities. So far, all existing works have been devoted to one-dimensional networks. Our approach attempts to provide a new anomaly detection method based on examining relationships between OSN users using multidimensional networks.

Original languageEnglish
Title of host publicationAdvanced Information Networking and Applications - Proceedings of the 34th International Conference on Advanced Information Networking and Applications, AINA 2020
EditorsLeonard Barolli, Flora Amato, Francesco Moscato, Tomoya Enokido, Makoto Takizawa
PublisherSpringer
Pages617-629
Number of pages13
ISBN (Print)9783030440404
DOIs
Publication statusPublished - 1 Jan 2020
Event34th International Conference on Advanced Information Networking and Applications, AINA 2020 - Caserta, Italy
Duration: 15 Apr 202017 Apr 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1151 AISC
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference34th International Conference on Advanced Information Networking and Applications, AINA 2020
Country/TerritoryItaly
CityCaserta
Period15/04/2017/04/20

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