WEB MINING AGAINST PEDOPHILIA

Authors

  • Shweta Macwan Student, Information Technology, Wroclaw University of Science and Technology, Wroclaw, Poland – 50-370.
  • Dr. inż. Grzegorz Filcek Assistant Professor, Information Technology, Wroclaw University of Science and Technology, Wroclaw, Poland – 50-370.

Keywords:

Web mining, Web content mining, Pedophile, cyber-crime, cyberpedophilia, pedophilic activityQ

Abstract

The need of security over the web is the foremost necessity and handling the cybercrimes is a priority. The growing popularity of the social media has led the children to use the internet more for social communication than information gathering. Children needs to learn and grow with technology but child safety is also required. Pedophiles hunt for innocent children over such social media and chat room platforms which are not safe for the child. Due to lack of parental guidance, such cases lead to cybercrimes which kids are not aware of. Social media is not the only area where pedophilic activities takes place. The search on the search engine may also help in detecting a pedophile. Here, the main idea is to capture the pedophiles using the conversions made with a child and detecting it based on the pattern of words and language used by an adult. Also, with the help of the search engine’s query detection a pedophilic activity can be traced.

References

I. Gupta, Aditi, Ponnurangam Kumaraguru, and Ashish Sureka. "Characterizing pedophile conversations on the internet using online grooming." arXiv preprint arXiv:1208.4324 (2012).

II. NCMEC, National center for missing and exploited children, 2008

III. http://www.missingkids.com/missingkids/servlet/NewsEventServlet?LanguageCountry=en US&PageId=4303.

IV. Pranit Bari and P.M. Chawan,” Journal of Engineering, Computers & Applied Sciences” (JEC&AS) Volume 2, No.6, June 2013, ISSN No: 2319-5606

V. Guandong Xu, Yanchun Zhang and Lin Li ,”Web Mining and Social Networking”, pp 71-87, 2011, DOI 10.1007/978-1-4419-7735-9_4, ISBN:978-1-4419-7735-9, Springer US

VI. Patidar, Kamlesh, Preetesh Purohit, and Kapil Sharma. "Web Content Mining Using Database Approach and Multilevel Data Tracking Methodology for Digital Library 1." (2011).

VII. Dasha Bogdanova, Paolo Rosso, Thamar Solorio, Exploring high-level features for detecting cyberpedophilia, Computer Speech & Language, Volume 28, Issue 1, January 2014, Pages 108-120, ISSN 0885-2308

VIII. India McGhee, Jennifer Bayzick, April Kontostathis, Lynne Edwards, Alexandra McBride and Emma Jakubowski. Learning to identify Internet sexual predation.International Journal on Electronic Commerce,2011.

IX. Bogdanova, Dasha, Paolo Rosso, and Thamar Solorio. "On the impact of sentiment and emotion based features in detecting online sexual predators." Proceedings of the 3rd Workshop in Computational Approaches to Subjectivity and Sentiment Analysis. Association for Computational Linguistics, 2012.

X. Falcão Jr, Mário Sérgio Rodrigues, Enyo José Tavares Gonçalves, and Tciciana Linhares Coelho da Silva. "Behavioral Analysis for Child Protection in Social Network through Data Mining and Multiagent Systems." (2016).

XI. R. Cooley, B. Mobasher and J. Srivastava, "Web mining: information and pattern discovery on the World Wide Web," Proceedings Ninth IEEE International Conference on Tools with Artificial Intelligence, Newport Beach, CA, 1997,pp.558-567.doi:10.1109/TAI.1997.

XII. Olatz Arbelaitz, Ibai Gurrutxaga, Aizea Lojo, Javier Muguerza, Jesús Maria Pérez, Iñigo Perona, Web usage and content mining to extract knowledge for modelling the users of the Bidasoa Turismo website and to adapt it, Expert Systems with Applications, Volume 40, Issue 18, 15 December 2013, Pages 7478-7491, ISSN 0957-4174, http://dx.doi.org/10.1016/j.eswa.2013.07.040.

XIII. Tarique Anwar, Muhammad Abulaish, A social graph based text mining framework for chat log investigation, Digital Investigation, Volume 11, Issue 4, December 2014, Pages 349-362, ISSN 1742-2876

XIV. M. Ashcroft, L. Kaati and M. Meyer, "A Step Towards Detecting Online Grooming -- Identifying Adults Pretending to be Children," 2015 European Intelligence and Security Informatics Conference, Manchester, 2015, pp. 98-104.

XV. M. Munezero, M. Mozgovoy, T. Kakkonen, V. Klyuev and E. Sutinen, "Antisocial Behavior corpus for harmful language detection," 2013 Federated Conference on Computer Science and Information Systems, Krako??w, 2013, pp. 261-265.

XVI. Munezero, M., Montero, C. S., Kakkonen, T., Sutinen, E., Mozgovoy, M., & Klyuev, V. (2014). Automatic detection of antisocial behaviour in texts. Informatica, 38(1), 3-10.

XVII. Hofmann, Alfred, et al. "Detection of Child Sexual Abuse Media: Classification of the Associated Filenames."

XVIII. Matthieu Latapy, Clémence Magnien, Raphaël Fournier, Quantifying paedophile activity in a large P2P system, Information Processing & Management, Volume 49, Issue 1, January 2013, Pages 248-263, ISSN 0306-4573

XIX. Y. Shavitt and N. Zilberman, "On the Presence of Child Sex Abuse in BitTorrent Networks," in IEEE Internet Computing, vol. 17, no. 3, pp. 60-66, May-June 2013.

XX. Mathiesen, Kay. "The Internet, children, and privacy: the case against parental monitoring." Ethics and Information Technology 15.4 (2013): 263-274.

XXI. Abdelghani Guerbas, Omar Addam, Omar Zaarour, Mohamad Nagi, Ahmad Elhajj, Mick Ridley, Reda Alhajj, Effective web log mining and online navigational pattern prediction, Knowledge-Based Systems, Volume 49, September 2013, Pages 50-62, ISSN 0950-7051

XXII. T. Anwar and M. Abulaish, "Ranking Radically Influential Web Forum Users," in IEEE Transactions on Information Forensics and Security, vol. 10, no. 6, pp. 1289-1298, June 2015.

XXIII. K. Sudheer Reddy, M. Kantha Reddy and V. Sitaramulu, "An effective data preprocessing method for Web Usage Mining," 2013 International Conference on Information Communication and Embedded Systems (ICICES), Chennai, 2013, pp. 7-10.

XXIV. Westlake, Bryce, Martin Bouchard, and Richard Frank. "Assessing the validity of automated webcrawlers as data collection tools to investigate online child sexual exploitation." Sexual abuse: a journal of research and treatment (2015): 1079063215616818.

Database: http://www.perverted-justice.com/

Additional Files

Published

15-05-2017

How to Cite

Shweta Macwan, & Dr. inż. Grzegorz Filcek. (2017). WEB MINING AGAINST PEDOPHILIA . International Education and Research Journal (IERJ), 3(5). Retrieved from http://ierj.in/journal/index.php/ierj/article/view/906