Elie Bursztein
John C. Mitchell
ABSTRACT
Contemporary blogs receive comments and TrackBacks, which result in cross-references between blogs. We conducted a longitudinal study of TrackBack spam, collecting and analyzing almost 10 million samples from a massive spam campaign over a one-year period. Unlike common delivery of email spam, the spammers did not use bots, but took advantage of an official Chinese site as a relay. Based on our analysis of TrackBack misuse found in the wild, we propose an authenticated TrackBack mechanism that defends against TrackBack spam even if attackers use a very large number of different source addresses and generate unique URLs for each TrackBack blog.
- Clive Akass. Storm worm 'making millions a day'. http://www.pcw.co.uk/personal-computer-world/news/2209293/strom-worm-making-millions-day, Feb 2008.Google Scholar
- Six Apart. Six apart guide to comment spam. http://www.sixapart.com/pronet/comment_spam.Google Scholar
- Six Apart. Trackback technical specification. http://www.sixapart.com/pronet/docs/trackback_spec.Google Scholar
- Dotclear. Dotclear blog plateform. http://dotclear.org/.Google Scholar
- Tom Espiner. Filipino news site hit by trackback spam. ZDNet Asia, http://www.zdnetasia.com/news/security/0,39044215,61998878,00.htm, 2007.Google Scholar
- F-secure. F-secure blog. http://www.f-secure.com/weblog/.Google Scholar
- Jonathan Feinberg. Wordle. http://www.wordle.net/.Google Scholar
- Brad L. Graham. Bradland must see http comments. blog http://www.bradlands.com/weblog/comments/september_10_1999/, Sep. 1999.Google Scholar
- Ironport. Internet security trends. http://www.ironport.com/securitytrends, 2008.Google Scholar
- Chris Kanich, Christian Kreibich, Kirill Levchenko, Brandon Enright, Geoffrey M. Voelker, Vern Paxson, and Stefan Savage. Spamalytics: an empirical analysis of spam marketing conversion. In CCS'08: Proceedings of the 15th ACM conference on Computer and communications security, pages 3--14, New York, NY, USA, 2008. ACM. Google ScholarDigital Library
- J. Kirk. Former spammer: 'I know I'm going to hell'. http://www.macworld.com/article/58997/2007/07/spammer.html, July 2007.Google Scholar
- Pranam Kolari, Akshay Java, Tim Finin, Tim Oates, and Anupam Joshi. Detecting spam blogs: A machine learning approach. In 2006. Proceedings of the 21st National Conference on Artificial Intelligence (AAAI), 2006. Google ScholarDigital Library
- C. Kreibich, C. Kanich, K. Levchenko, B. Enright, G. Voelker, V. Paxson, and S. Savage. Spamcraft: An inside look at spam campaign orchestration. In USENIX, editor, LEET, 2009. Google ScholarDigital Library
- Craig Macdonald and Iadh Ounis. The trec blogs06 collection: Creating and analysing a blog test collection. DCS Technical Report Series, 2006.Google Scholar
- Ashraf Matrawy, Anil Somayaji, and P. C. Oorschot. Mitigating network denial-of-service through diversity-based traffic management. In ACNS'05, pages 104--121. Springer Science+Business Media, 2005. Google ScholarDigital Library
- Universal McCann. Power to the people - social media tracker wave.3. http://www.universalmccann.com/Assets/wave_3_20080403093750.pdf.Google Scholar
- Declan McCullagh and Anne Broache. Blogs turn 10-who's the father? http://news.cnet.com/2100-1025_3-6168681.html.Google Scholar
- Gilad Mishne, David Carmel, and Ronny Lempel. Blocking blog spam with language model disagreement. In In Proceedings of the First International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), 2005.Google Scholar
- Alexandros Ntoulas and Mark Manasse. Detecting spam web pages through content analysis. In In Proceedings of the World Wide Web conference, pages 83--92. ACM Press, 2006. Google ScholarDigital Library
- Automattic Production. Askimet trackback statistics. http://akismet.com/stats/.Google Scholar
- Dan Sandler and Andy Thomas. Trackback validator. http://seclab.cs.rice.edu/proj/trackback/.Google Scholar
- Technorati. State of the blogosphere. http://technorati.com/blogging/state-of-the-blogosphere/.Google Scholar
- Technorati. Technorati top 100 blogs. http://technorati.com/pop/blogs/.Google Scholar
- D. Watson. All spammers go to hell (posting to funsec list). http://www.mail- archive.com/[email protected]/msg03346.html, July 2007.Google Scholar
- Michal Zalewski. P0f2: "Dr. Jekyll had something to Hyde" passive OS fingerprinting tool. Web, 2006.Google Scholar
Index Terms
- TrackBack spam: abuse and prevention
Recommendations
Trackback-Rank: An Effective Ranking Algorithm for the Blog Search
IITA '08: Proceedings of the 2008 Second International Symposium on Intelligent Information Technology Application - Volume 03Today, most web pages are being created in the blog space or evolving into the blog space. A major problem is that a blog entry (blog page) includes non-traditional features of Web pages. Those are trackback links, bloggers' authority, tags, and users’ ...
@spam: the underground on 140 characters or less
CCS '10: Proceedings of the 17th ACM conference on Computer and communications securityIn this work we present a characterization of spam on Twitter. We find that 8% of 25 million URLs posted to the site point to phishing, malware, and scams listed on popular blacklists. We analyze the accounts that send spam and find evidence that it ...
Effect of Spam on Hashtag Recommendation for Tweets
WWW '16 Companion: Proceedings of the 25th International Conference Companion on World Wide WebPresence of spam tweets in a dataset may affect the choices of feature selection, algorithm formulation, and system evaluation for many applications. However, most existing studies have not considered the impact of spam tweets. In this paper, we study ...
Comments