Malicious Posts Detection in Online in Social Networks

Authors

  • Divya  Assistant Professor, RPIIT, Bastarar Kurukshetra, Haryana, India

Keywords:

Online Social Network , Facebook , posts, URL, Cybercriminals and Shares

Abstract

Online Social Networks provides different applications to users through which user can share their emotions in the form of text images and videos to their friends. User can also add new friends in their friend list also create groups of persons having same interest. When a user posts a new post on a group or on a page then it is difficult to justify that whether that post is normal post or malicious post. In this paper an attempt has been made to propose a mechanism to detect malicious posts in social network by analyzing the posts posted by user and number of likes and shares available on a post.

References

  1. G.Stringhini, C. Kruegel and G. Vigna, Detecting Spammers on Social Networks, in proceedings of the 26th Annual Computer Security Applications Conference (ACSAC), 2010, pp.1-9.
  2. De Wang, “Analysis and Detection of Low Quality Information in Social Networks”, ICDE Workshops 2014, IEEE 2014, pp.350-354.
  3. H. Gao, J. Hu, C. Wilson, Z. Li, Y. Chen, and B. Y. Zhao, “Detecting and characterizing social spam campaigns”, In IMC, 2010, pp.1-6.
  4. Pran Dev, Jyoti, Dr. Kulvinder Singh and Dr. Sanjeev Dhawan, “A Naive Algorithmic Approach for Detection of Users’ with Unusual Behavior in online Social Networks” International Journal of Software and Web Sciences (IJSWS), ISSN: 2279-0071pp: 37-41,2015.
  5. Ekta, Sanjeev Dhawan and Kulvinder Singh, “Feature Extraction and Content Investigation of Facebook User’s using Netvizz and Gephi”, Advances in Computer Science and Information Technology (ACSIT), ACSIT 2016, pp. 262-265.
  6. Divya, Dr. Kulvinder Singh and Dr. Sanjeev Dhawan, “Threshold Based Mechanism to Detect Malicious URL’s in Social Networks”, IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN: 2278-0661, p-ISSN: 2278-8727pp:18-21.
  7. J. Golbeck and M. Rothstein, “Linking social networks on the web with FOAF: a semantic web case study,” in Proceedings of the 23rd national conference on Artificial intelligence - Volume 2. Chicago, Illinois: AAAI Press, 2008, pp. 1138-1143.
  8. M.Rowe and F.Ciravegna, “Disambiguating identity through social circles and social data,” in Collective Intelligence Workshop ESWC 2008, Tenerife, Spain, IEEE 2008,  pp. 1-4
  9. Prateek Dewan, Ponnurangam Kumaraguru,” Towards Automatic Real Time Identification of Malicious Posts on Facebook”, 2015 Thirteenth Annual Conference on Privacy, Security and Trust (PST), IEEE 2015, pp.85-92
  10. Sazzadur Rahman, Ting-Kai Huang, Harsha V. Madhyastha, and Michalis Faloutsos,” Detecting Malicious Facebook Applications”, IEEE/ACM Transactions on Networking, IEEE 2015,  pp. 1-15
  11. Agichtein E, Castillo C, Donato D, Gionis A and Mishne G,” Finding high-quality content in social media”, Proceedings of the international conference on Web search Fake Identities in Social Media”, Journal of Service Science Research , 2012, pp.175-212.

IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2017-10-31

Issue

Volume 2, Issue 5, September-October-2017

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Divya, " Malicious Posts Detection in Online in Social Networks , IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 5, pp.790-792, September-October-2017.