Abstract
Due to the significance and indispensability of detecting and suspending Twitter spammers, many researchers along with the engineers in Twitter Corporation have devoted themselves to kee** Twitter as spam-free online communities. Meanwhile, Twitter spammers are also evolving to evade existing detection techniques. In this paper, we make an empirical analysis of the evasion tactics utilized by Twitter spammers, and then design several new and robust features to detect Twitter spammers. Finally, we formalize the robustness of 24 detection features that are commonly utilized in the literature as well as our proposed ones. Through our experiments, we show that our new designed features are effective to detect Twitter spammers, achieving a much higher detection rate than three state-of-the-art approaches [35,32,34] while kee** an even lower false positive rate.
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References
A new look at spam by the numbers, http://scitech.blogs.cnn.com/
Acai Berry spammers hack Twitter accounts to spread adverts, http://www.sophos.com/blogs/gc/g/2009/05/24/acai-berry-spammers-hack-twitter-accounts-spread-adverts/
Auto Twitter, http://www.autotweeter.in/
Betweenness Centrality, http://en.wikipedia.org/wiki/Centrality
Botnet over Twitter, http://compsci.ca/blog/
Buy a follower, http://buyafollower.com/
Capture HPC, https://projects.honeynet.org/capture-hpc
F-measure, http://en.wikipedia.org/wiki/F1_score
Google Safe Browsing API, http://code.google.com/apis/safebrowsing/
Local Clustering Coefficient, http://wikipedia.org/wiki/Clustering_coefficient#Local_clustering_coefficienty
Low-Priced Twitter Spam Kit Sold on Underground Forums, http://news.softpedia.com/news/Low-Priced-Twitter-Spam-Kit-Sold-on-Underground-Forums-146160.shtml
New Koobface campaign spreading on Facebook, http://community.websense.com/blogs/securitylabs/archive/2011/01/14/new-koobface-campaign-spreading-on-facebook.aspx
The 2000 Following Limit Policy On Twitter, http://twittnotes.com/2009/03/2000-following-limit-on-twitter.html
The Twitter Rules, http://help.twitter.com/entries/18311-the-twitter-rules
Tweet spinning your way to the top, http://blog.spinbot.com/2011/03/tweet-spinning-your-way-to-the-top/
TweetDeck, http://www.tweetdeck.com/
Twitter account for sale, http://www.potpiegirl.com/2008/04/buy-sell-twitter-account/
Twitter API in Wikipedia, http://apiwiki.twitter.com/
Twitter phishing hack hits BBC, Guardian and cabinet minister, http://www.guardian.co.uk/technology/2010/feb/26/twitter-hack-spread-phishing
Twitter Public Timeline, http://twitter.com/public_timeline
Axelsson, S.: The base-rate fallacy and its implications for the difficulty of intrusion detection. In: Proceedings of the 6th ACM Conference on Computer and Communications Security, pp. 1–7 (1999)
Benevenuto, F., Magno, G., Rodrigues, T., Almeida, V.: Detecting Spammers on Twitter. In: Collaboration, Electronic messaging, Anti-Abuse and Spam Confference, CEAS (2010)
Benevenuto, F., Rodrigues, T., Almeida, V., Almeida, J., Gonalves, M.: Detecting Spammers and Content Promoters in Online Video Social Networks. In: ACM SIGIR Conference, SIGIR (2009)
Benevenuto, F., Rodrigues, T., Almeida, V., Almeida, J., Zhang, C., Ross, K.: Identifying Video Spammers in Online Social Networks. In: Int’l Workshop on Adversarial Information Retrieval on the Web, AirWeb 2008 (2008)
Cha, M., Haddadi, H., Benevenuto, F., Gummadi, K.: Measuring User Influence in Twitter: The Million Follower Fallacy. In: Int’l AAAI Conference on Weblogs and Social Media, ICWSM (2010)
Chu, Z., Gianvecchio, S., Wang, H., Jajodia, S.: Who is Tweeting on Twitter: Human, Bot, or Cyborg?. In: Annual Computer Security Applications Conference, ACSAC 2010 (2010)
Gao, H., Hu, J., Wilson, C., Li, Z., Chen, Y., Zhao, B.: Detecting and Characterizing Social Spam Campaigns. In: Proceedings of ACM SIGCOMM IMC, IMC 2010 (2010)
Griery, C., Thomas, K., Paxsony, V., Zhangy, M.: @spam: The Underground on 140 Characters or Less. In: ACM Conference on Computer and Communications Security, CCS (2010)
Ionescu, D.: Twitter Warns of New Phishing Scam, http://www.pcworld.com/article/174660/twitter_warns_of_new_phishing_scam.html
Koutrika, G., Effendi, F., Gyongyi, Z., Heymann, P., Garcia-Molina, H.: Combating spam in tagging systems. In: Int’l Workshop on Adversarial Information Retrieval on the Web, AIRWeb 2007 (2007)
Kwak, H., Lee, C., Park, H., Moon, S.: What is Twitter, a Social Network or a News Media?. In: Int’l World Wide Web, WWW 2010 (2010)
Lee, K., Caverlee, J., Webb, S.: Uncovering Social Spammers: Social Honeypots + Machine Learning. In: ACM SIGIR Conference, SIGIR (2010)
Leskovec, J., Faloutsos, C.: Sampling from large graphs. In: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, SIGKDD (2006)
Stringhini, G., Barbara, S., Kruegel, C., Vigna, G.: Detecting Spammers On Social Networks. In: Annual Computer Security Applications Conference, ACSAC 2010 (2010)
Wang, A.: Don’t follow me: spam detecting in Twitter. In: Int’l Conferene on Security and Cryptography, SECRYPT (2010)
Yang, C., Harkreader, R., Gu, G.: Die free or live hard? empirical evaluation and new design for fighting evolving twitter spammers (extended version). Technical report (2011)
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Yang, C., Harkreader, R.C., Gu, G. (2011). Die Free or Live Hard? Empirical Evaluation and New Design for Fighting Evolving Twitter Spammers. In: Sommer, R., Balzarotti, D., Maier, G. (eds) Recent Advances in Intrusion Detection. RAID 2011. Lecture Notes in Computer Science, vol 6961. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23644-0_17
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DOI: https://doi.org/10.1007/978-3-642-23644-0_17
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