Google scholar arxiv informatics ads IJAIS publications are indexed with Google Scholar, NASA ADS, Informatics et. al.

Call for Paper

-

November Edition 2021

International Journal of Applied Information Systems solicits high quality original research papers for the November 2021 Edition of the journal. The last date of research paper submission is October 15, 2021.

Spambot Detection: A Review of Techniques and Trends

I. A. Adegbola, R. G. Jimoh Published in Security

International Journal of Applied Information Systems
Year of Publication: 2014
© 2013 by IJAIS Journal
10.5120/ijais14-451115
Download full text
  1. I A Adegbola and R G Jimoh. Article: Spambot Detection: A Review of Techniques and Trends. International Journal of Applied Information Systems 6(9):7-10, March 2014. BibTeX

    @article{key:article,
    	author = "I. A. Adegbola and R. G. Jimoh",
    	title = "Article: Spambot Detection: A Review of Techniques and Trends",
    	journal = "International Journal of Applied Information Systems",
    	year = 2014,
    	volume = 6,
    	number = 9,
    	pages = "7-10",
    	month = "March",
    	note = "Published by Foundation of Computer Science, New York, USA"
    }
    

Abstract

Spambot is a new way of creating and spreading spam using a robot in web 2. 0 environment. Application such as blogs, face book, twitter and various form of social networking provides an enabling environment for spammers to deploy an intelligent program capable of imitating human behaviour to spread unsolicited message like spyware or malware and even content that can be use to perpetrate unwholesome act . This paper seems to harvest all past and current technique used in identification and detection of this type of spam and examine the trend in this type of spamming activities to suggest a research area for the researchers into spam management and detection.

Reference

  1. A. Luis von, B. Manuel, and L. John, "Telling humans and computers apart automatically," Commun. ACM, vol. 47, pp. 56-60, 2004.
  2. K. Chellapilla and P. Simard, "Using Machine Learning to Break Visual Human Interaction Proofs (HIPs)," in NIPS, 2004.
  3. Y. Jeff and A. Ahmad Salah El, "Usability of CAPTCHAs or usability issues in CAPTCHA design," in Proceedings of the 4th symposium on Usable privacy and security Pittsburgh, Pennsylvania: ACM, 2008.
  4. P. -N. Tan and V. Kumar, "Discovery of Web Robot Sessions Based on their Navigational Patterns," Data Mining and Knowledge Discovery, vol. 6, pp. 9-35, 2002.
  5. K. Park, V. S. Pai, K. -W. Lee, and S. Calo, "Securing Web Service by Automatic Robot Detection," USENIX 2006 Annual Technical Conference Refereed Paper, 2006.
  6. L. Yiqun, C. Rongwei, Z. Min, M. Shaoping, and R. Liyun, "Identifying web spam with user behavior analysis," in Proceedings of the 4th international workshop on Adversarial information retrieval on the web Beijing, China: ACM, 2008.
  7. H. Yu, Y. Liu, M. Zhang, L. Ru, and S. Ma, "Web Spam Identification with User Browsing Graph," in Information Retrieval Technology, 2009, pp. 38-49.
  8. P. Hayati, K. Chai, V. Potdar, and A. Talevski, "HoneySpam 2. 0: Profiling Web Spambot Behaviour," in 12th International Conference on Principles of Practise in Multi-Agent Systems, Nagoya, Japan, 2009, pp. 335-344.
  9. G. Jan, bel, H. Thorsten, and T. Philipp, "Towards Proactive Spam Filtering (Extended Abstract)," in Proceedings of the 6th International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment Como, Italy: Springer- Verlag, 2009.
  10. J. Nitin and L. Bing, "Opinion spam and analysis," in Proceedings of the international conference on Web search and web data mining Palo Alto, California, USA: ACM, 2008.
  11. F. Benevenuto, T. Rodrigues, V. Almeida, J. Almeida, C. Zhang, and K. Ross, "Identifying Video Spammers in Online Social Networks," in AIRWeb '08 Beijing, China, 2008.
  12. H. Paul, K. Georgia, and G. -M. Hector, "Fighting Spam on Social Web Sites: A Survey of Approaches and Future Challenges," IEEE Internet Computing, vol. 11, pp. 36-45, 2007.
  13. Jaber Karimpour, Ali A Noroozi and Somayeh Alizadeh. Article: Web Spam Detection by Learning from Small Labeled Samples. International Journal of Computer Applications 50(21):1-5, July 2012. Published by Foundation of Computer Science, New York, USA.
  14. M. Sree Vani , R. Bhramaramba , D. Vasumati and O. Yaswanth Babu. Article: A Survey on Link Based Algorithm for Web Spam Detection . International Journal of Current Engineering and Technology, Vol. 3,No. 2 (June- 2013). Published by Inpressco International Press Corporation
  15. Apichat Taweesiriwate, Bundit Manaskasemsak, Arnon Rungsawang, "Web Spam Detection Using Link-Based Ant Colony Optimization," aina, pp. 868-873, 2012 IEEE 26th International Conference on Advanced Information Networking and Applications, 2012.
  16. Cailing Dong, Bin Zhou, "Effectively Detecting Content Spam on the Web Using Topical Diversity Measures," wi-iat, vol. 1, pp. 266-273, 2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, 2012
  17. Mohammed Al-Kabi , Heider Wahsheh, Izzat Alsmadi , Emad Al-Shawakfa, Abdullah Wahbeh , Ahmed Al-Hmoud. "Content-based analysis to detect Arabic web spam"Article: Published online before print April 19, 2012, doi: 10. 1177/0165551512439173 Journal of Information Science June 2012 vol. 38 no. 3 284-296
  18. A. Zinman and J. Donath, "Is Britney Spears spam," in Fourth Conference on Email and Anti-Spam Mountain View, California, 2007.
  19. 031072208 (2005-10-01). "Web 2. 0: Compact Definition". Scholar. googleusercontent. com. Retrieved 2013-06-15.
  20. P. Hayati and V. Potdar, "Toward Spam 2. 0: An Evaluation of Web 2. 0 Anti-Spam Methods " in 7th IEEE International Conference on Industrial Informatics Cardiff, Wales, 2009.
  21. R. Cooley, B. Mobasher, and J. Srivastava, "Web mining: information and pattern discovery on the World Wide Web," in Tools with Artificial Intelligence, 1997. Proceedings. , Ninth IEEE International Conference on, 1997, pp. 558-567.

Keywords

Antispam, Spambot, Detection, Behaviour, web 2.0 browser, Trend