A System to Filter Unnecessary Posts from OSN User Walls And Prevent Inference Attacks
A.A.Kothari , M.U.Kharat
Abstract
Now a day’s social Networks are more popular. Users are using multiple applications for social media. Users post their comments on their private space to avoid that unwanted content is displayed. To overcome this problem, Author proposes a system allowing OSN users to have a direct control on the messages posted on their walls. The system explores how to prevent personal information using learning algorithm. This paper describes how to launch inference attacks using released social networking applications data to predict private information. Then author have 3 different techniques which can be used in such situations.
Online social networks, information filtering, short text classification, Sanitization Techniques, policy-based personalization.
[1] Marco Vanetti, Elisabetta Binaghi, Elena Ferrari, Barbara Carminati, and Moreno Carullo “A System to Filter Unwanted Messages from OSN User Walls” IEEE Transactions on Knowledge and data engineering, vol. 25, no. 2, Feb 2013.
[2] N.J. Belkin and W.B. Croft, ” Information Filtering and Information Retrieval: Two Sides of the Same Coin? “ Comm. ACM, vol. 35, no. 12, pp. 29-38, 1992.
[3] R.J. Mooney and L. Roy, “Content-Based Book Recommending Using Learning for Text Categorization”, Proc. Fifth ACM Conf. Digital Libraries, pp. 195-204, 2000.
[4] S. Zelikovitz and H. Hirsh, “Improving Short Text Classification Using Unlabeled Background Knowledge”, Proc. 17th Intl Conf. Machine Learning (ICML 00), P. Langley, ed., pp. 1183-1190, 2000.
[5] S. Dumais, J. Platt, D. Heckerman, and M. Sahami, “Inductive Learning Algorithms and Representations for Text Categorization”, Proc. Seventh Intl Conf. Information and Knowledge Management (CIKM 98), pp. 148-155, 1998.
[6] B. Sriram, D. Fuhry, E. Demir, H. Ferhatosmanoglu, and M. Demirbas, “Short text classification in twitter to improve information filtering”, in Proceeding of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2010, 2010, pp. 841-842.
[7] J. Golbeck, “Combining provenance with trust in social networks for semantic web content filtering”, in Provenance and Annotation of Data, ser. Lecture Notes
[8] M. Vanetti, E. Binaghi, B. Carminati, M. Carullo, and E. Ferrari, “Content-Based Filtering in On-Line Social Networks”, Proc. ECML/PKDD Workshop Privacy and Security Issues in Data Mining and Machine Learning (PSDML 10), 2010.
[9] F. Sebastiani, “Machine Learning in Automated Text Categorization”, ACM Computing Surveys, vol. 34, no. 1, pp. 1-47, 2002.
[10] M. Chau and H. Chen, “A Machine Learning Approach to Web Page Filtering Using Content and Structure Analysis, Decision Support Systems”, vol. 44, no. 2, pp. 482-494, 2008.
[11] Carminati, B., Ferrari, E, Access control and privacy in web-based social networks, International Journal of Web Information Systems, pp. 395415, 2008.
[12] Churcharoenkrung N., Kim, Y.S., Kang, B.H., “Dynamic web content filtering based on users knowledge”, International Conference on Information Technology, Coding and Computing 1, pp. 184188 2005.
[13] Fang, L., LeFevre, K., Privacy wizards for social networking sites; In: WWW 10: Proceedings of the 19th international conference on World Wide Web, pp. 351360. ACM, New York, NY, USA, 2010.
[14] Fong, P.W.L., Anwar, M.M., Zhao, Z., “A privacy preservation model for facebook- style social network systems”, In: Proceedings of 14th European Symposium on Research in Computer Security (ESORICS), pp. 303320, 2009.
[15] A .A. Kothari and M .U. Kharat “ A Review on Message Filtering from Online Social Networks” Innovations and Trends in Computer and Communication Engineering (ITCCE-2014), pg 20-22
[A.A.Kothari , M.U.Kharat (2015) A System to Filter Unnecessary Posts from OSN User Walls And Prevent Inference Attacks IJIRCST Vol-2 Issue-4 Page No-71-76] (ISSN 2347 - 5552). www.ijircst.org
A.A.Kothari
Computer Department MET’s BKC IOE, Nashik, Savitribai Phule Pune University, India alpakothari21@gmail.com
