Identification of Malicious Posts in Facebook Social Networks

Authors(3) :-Sanjeev Dhawan, Kulvinder Singh, Sanjay Sagwal

A social network provides interconnectivity between millions of users. In social networks numbers of applications are available like Twitter, Google+ and Facebook through which people can connect with each other. In Facebook, user can add number of users and their friends in friend list. When a user adds more friends and their friends in his friend list then may be some of them could be malicious users and spread malicious spamís or misinformation through posts on user wall. In this paper, an attempt has been made to present comparative analysis of various existing techniques with different parameters to detect malicious posts in online social networks. This paper is divided into four sections. Section I covers introduction of social networks that includes brief discussion on Facebook. In section II literature review on different existing techniques proposed by different researchers to detect and prevent social network from malicious posts posted by malicious users. Section III presents proposed work and at last section IV presents comparison between existing techniques with their pros and cons.

Authors and Affiliations

Sanjeev Dhawan
Faculty of Computer Science and Engineering, Department of Computer Science and Engineering, University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra, Haryana, India
Kulvinder Singh
Faculty of Computer Science and Engineering, Department of Computer Science and Engineering, University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra, Haryana, India
Sanjay Sagwal
M. Tech. (Computer Engineering), University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra, Haryana, India

Social networks, Facebook, Posts, profile and Malicious users.

  1. 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.
  2. Ekta and Sanjeev Dhawan, "Classification of Data Mining and Analysis for Predicting Diabetes Subtypes using WEKA", Vivechana: National Conference on Advances in Computer Science and Engineering (ACSE-2016), pp. 1-5.
  3. 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.
  4. Sanjeev Dhawan and Ekta, "Implications of Various Fake Profile Detection Techniques in Social Networks", IOSR Journal of Computer Engineering (IOSR-JCE), AETM'16, 2016, pp. 49-55.
  5. 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
  6. Smith A, O’Hara K and Lewis P, "Visualizing the past: Annotating a life with linked open data", in: Web Science Conference ’11, 2011.
  7. 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.
  8. Cao Xiao, David Mandell Freeman and Theodore Hwa, "Detecting Clusters of Fake Accounts in Online Social Networks", 2015 ACM. ISBN 978-1-4503-3826-4 pp: 1-11.
  9. M. Nandhini and Bikram Bikash Das, "An Assessment And Methodology For Fraud Detection In Online Social Network", Second International Conference on Science Technology Engineering and Management (ICONSTEM) 2016, pp: 104-108.
  10. G. Stringhini, C. Kruegel, and G. Vigna, "Detecting spammers on social networks," in ACSAC ’10: Proceedings of the 26th Annual Computer Security Applications Conference. ACM Request Permissions, 2012, pp. 1-9.
  11. Haewoon Kwak, Changhyun Lee, Hosung Park, and Sue Moon, "What is Twitter, a Social Network or a News Media?", International World Wide Web Conference Committee (IW3C2),ACM 2010, pp. 1-10.
  12. Anwar M, Fong PW, "A visualization tool for evaluating access control policies in Facebook-style social network systems", In: Proceedings of the 27th annual ACM symposium on applied computing, ACM 2012, pp. 1443-1450.
  13. S. Abu-Nimeh, T. M. Chen, and O. Alzubi, "Malicious and Spam Posts in Online Social Networks," Computer, vol. 44, no. 9, IEEE 2011, pp. 23-28.

Publication Details

Published in : Volume 2 | Issue 5 | September-October 2017
Date of Publication : 2017-10-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 43-46
Manuscript Number : CSEIT1724212
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Sanjeev Dhawan, Kulvinder Singh, Sanjay Sagwal, "Identification of Malicious Posts in Facebook Social Networks", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 5, pp.43-46, September-October.2017
URL : http://ijsrcseit.com/CSEIT1724212

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