CFP last date
20 January 2025
Reseach Article

Real Time Detection of Suspicious URLs on Social Networking Sites Twitter

by Jyoti D. Halwar, Sandeep U. Kadam
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 123 - Number 7
Year of Publication: 2015
Authors: Jyoti D. Halwar, Sandeep U. Kadam
10.5120/ijca2015905384

Jyoti D. Halwar, Sandeep U. Kadam . Real Time Detection of Suspicious URLs on Social Networking Sites Twitter. International Journal of Computer Applications. 123, 7 ( August 2015), 6-9. DOI=10.5120/ijca2015905384

@article{ 10.5120/ijca2015905384,
author = { Jyoti D. Halwar, Sandeep U. Kadam },
title = { Real Time Detection of Suspicious URLs on Social Networking Sites Twitter },
journal = { International Journal of Computer Applications },
issue_date = { August 2015 },
volume = { 123 },
number = { 7 },
month = { August },
year = { 2015 },
issn = { 0975-8887 },
pages = { 6-9 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume123/number7/21969-2015905384/ },
doi = { 10.5120/ijca2015905384 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:12:00.691979+05:30
%A Jyoti D. Halwar
%A Sandeep U. Kadam
%T Real Time Detection of Suspicious URLs on Social Networking Sites Twitter
%J International Journal of Computer Applications
%@ 0975-8887
%V 123
%N 7
%P 6-9
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Twitter, FACEBOOK are very famous social networking site utilized by billions of individuals to exchange the data to one another. To communicate with one another over the long separation it is used. At the same time it additionally attracts the attacker in doing diverse assaults or get the data being imparted by their clients. Twitter users can send the messages to one another as tweets, that tweets have the size impediment of greatest 140 characters. So to share the large information addresses to that pages is used by providing links of that pages. And for this purpose URL shorting is used. Attackers send the suspicious URLS in tweets and move the clients to malignant pages. These URLs can also be shared on Facebook with followers and friends. This paper introduces a Near REAL TIME APPLICATION to detect the suspicious URLs which are shared on twitters public timeline. This application collects the tweets, extracts the features correlated to the URL redirect chain, and with the help of training classifier it classifies the URLs as Suspicious and Benign.

References
  1. S. Lee and J. Kim, “WarningBird: Detecting suspicious URLS in Twitter stream,” in Proc. NDSS, 2012.
  2. H. Kwak, C. Lee, H. Park, and S. Moon, “What is Twitter, a socialnetwork or a news media?” in Proc. WWW, 2010.
  3. Antoniades, I. Polakis, G. Kontaxis, E. Athanasopoulos, S. Ioannidis, E. P. Markatos, and T. Karagiannis, “we.b: The web of short URLS,” in Proc. WWW, 2011.
  4. Klien and M. Strohmaier, “Short links under attack: geographical analysis of spam in a URL shortener network,” in Proc. ACM HT, 2012.
  5. K. Thomas, C. Grier, J. Ma, V. Paxson, and D. Song, “Design andevaluation of a real-time URL spam filtering service,” in Proc. IEEE S&P, 2011.
  6. Whittaker, B. Ryner, and M. Nazif, “Large-scale automatic classification of phising pages,” in Proc. NDSS, 2010.
  7. M. Cova, C. Kruegel, and G. Vigna, “Detection and analysis of drive-by-download attacks and malicious JavaScript code,” in Proc. WWW, 2010.
  8. J. Zhang, C. Seifert, J. W. Stokes, and W. Lee, “ARROW: Generatingsignatures to detect drive-by downloads,” in Proc. WWW, 2011.
  9. J. Ma, L. K. Saul, S. Savage, and G. M. Voelker, “Beyond blacklists: Learning to detect malicious web sites from suspicious URLS,” in Proc. ACM KDD, 2009.
Index Terms

Computer Science
Information Sciences

Keywords

Suspicions URL Twitter URL redirection conditionnel redirection classification.