earticle

논문검색

Anomaly Recognition in Online Social Networks

초록

영어

The popularity of social networking sites has increased throughout the decade and everything that gains immense popularity with great human involvement also brings many challenges and issues along with it. Similarly the excessive use of online social networking causes a great increase in anomalies. In social networking the anomalies are like fake account, account hack, identity theft, spams and many other illegitimate activities. It is thus necessary to detect such anomalous and suspicious behavior of any user at these social platforms, as they could have an adverse impact on users, especially on teenagers. In this paper, we propose various methodologies for early detection of suspicious and anomalous activities. We have done the analysis of various parameters of social networking and its graph like indegree, outdegree, active time of a node (user) and its behavior.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Proposed Work
  3.1 Inappropriate Content Share
  3.2 Silent Hacking of Account
  3.3 Fake Promotional Accounts
 4. Experimental Setup
 5. Observation and Analysis
  5.1 Sharing of Inappropriate Content
  5.2 Silent Hacking of Account
  5.3 Promotional Fake Accounts
 6. Conclusion
 References

저자정보

  • Ashish Rawat Department of Computer Science and Engineering, Jaypee University of Information Technology, Solan, Himachal Pradesh, India
  • Gunjan Gugnani Department of Computer Science and Engineering, Jaypee University of Information Technology, Solan, Himachal Pradesh, India
  • Minakshi Shastri Department of Computer Science and Engineering, Jaypee University of Information Technology, Solan, Himachal Pradesh, India
  • Pardeep Kumar Department of Computer Science and Engineering, Jaypee University of Information Technology, Solan, Himachal Pradesh, India

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