拜網路的普及所賜，Facebook是現今最火紅的社交服務平台，使用人數也成驚人的指數成長。水能載舟，亦能覆舟，Facebook 所提供的社團功能除了能夠幫助使用者拉近彼此的距離外，卻也被不肖人士作為詐騙的新手法。為了杜絕該情況發生，因此提出一個新的服務幫助使用者避免受騙的情況發生。
此服務會透過使用者授予該應用程式相關權限後，嘗試去取得使用者社團的內容。透過這些擷取的內容，我們經過初步分析，再將這些資訊放入我們用來分類的模型。我們會將分類結果判斷該社團是否為廣告性社團。而我們將定期為使用者的社團做分析處理，並將結果以清單方式回傳給使用者，並加入適當建議，讓使用者更能清楚地了解潛在風險。而為了瞭解錯誤率等情況，我們會將該應用程式作實驗，並透過手動檢查與其他的應用程式作驗證，幫助我們更加瞭解應用程式的分析情形。最後，我們希望使用者能夠對於廣告性社團更有警覺心，也希望每個使用者在臉書上有更好的使用經驗。

With the popularity of Facebook, it has become the newest platform of spamming distributor. Our target is focusing on Facebook group pages, which is occupied with spam messages. With the huge amount of spam, user might feel disturbed, and even confront personal data leak. Therefore, it is necessary to solve this problem. We implement SVM algorithms to support our text filtering mechanism. And according to the group's features to evaluate each one. Lastly, based on the results, to send the appropriate advices to the users. We hope each user could have a better experience on Facebook.

Chapter1:Introduction
Chapter2:Background
Chpater3:Related Works
Chpater4:Method
Chpater5:Implementation
Chpater6:Discussion
Chpater7:Conclusion

[1] Facebook tops billion user mark@the wall street journal, 2012. http://online. wsj.com/article/SB10000872396390443635404578036164027386112.html.
[2] Ricardo da Silva Torres and Alexandre X Falca ̃o. Content-based image retrieval: Theory and applications. RITA, 13(2):161–185, 2006.
[3] Enrico Blanzieri and Anton Bryl. A survey of learning-based techniques of email spam filtering. Artificial Intelligence Review, 29(1):63–92, 2008.
[4] Chih-Chung Chang and Chih-Jen Lin. Libsvm: a library for support vector machines. ACM Transactions on Intelligent Systems and Technology (TIST), 2(3):27, 2011.
[5] Facebook@wiki, 2013. http://en.wikipedia.org/wiki/Facebook#cite_ note-10.
[6] Statistics of facebook, 2013. http://newsroom.fb.com/content/default. aspx?NewsAreaId=22.
[7] G Hogben. Security issues and recommendations for online social networks, position paper. ENISA, European Network and Information Security Agency, 2007.
[8] Ralph Gross, Jianbo Shi, and Jeffrey F Cohn. Quo vadis face recognition? Carnegie Mellon University, The Robotics Institute, 2001.
[9] Wenyi Zhao, Rama Chellappa, P Jonathon Phillips, and Azriel Rosenfeld. Face recognition: A literature survey. Acm Computing Surveys (CSUR), 35(4):399– 458, 2003.
[10] Jacqui Cheng. Facial recognition slipped into google image search. ArsTechnica. com, May, 30, 2007.
[11] Google image search@google, 2013. https://www.google.com.tw/imghp?hl= zh-TW&tab=wi.
[12] Harry potter and digital fingerprints@deep links news, 2007. https://www. eff.org/deeplinks/2007/07/harry-potter-and-digital-fingerprints.
[13] Facebook help center@facebook, 2013. http://www.facebook.com/help/ 359046244166395.
[14] Facebook group@facebook, 2013. https://www.facebook.com/about/groups.
[15] Qiyun Wang, Huay Lit Woo, Choon Lang Quek, Yuqin Yang, and Mei Liu. Using the facebook group as a learning management system: An exploratory study. British Journal of Educational Technology, 43(3):428–438, 2012.
[16] Fabrıcio Benevenuto, Gabriel Magno, Tiago Rodrigues, and Virgılio Almeida. Detecting spammers on twitter. In Collaboration, electronic messaging, anti- abuse and spam conference (CEAS), volume 6, 2010.
[17] Shu-Hsun Lo. A neural tree with partial incremental learning capability and its application in spam filtering. 2007.
[18] Pranam Kolari, Tim Finin, and Anupam Joshi. Svms for the blogosphere: Blog identification and splog detection. In AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs, pages 92–99, 2006.
[19] Account stolen@appledaily, 2013. http://www.appledaily.com.tw/ appledaily/article/headline/20130309/34876090/.
[20] Ching-Tung Wu, Kwang-Ting Cheng, Qiang Zhu, and Yi-Leh Wu. Using visual features for anti-spam filtering. In Image Processing, 2005. ICIP 2005. IEEE International Conference on, volume 3, pages III–509. IEEE, 2005.
[21] Zoltan Gyongyi and Hector Garcia-Molina. Web spam taxonomy. In First in- ternational workshop on adversarial information retrieval on the web (AIRWeb 2005), 2005.
[22] Alexandros Ntoulas, Marc Najork, Mark Manasse, and Dennis Fetterly. De- tecting spam web pages through content analysis. In Proceedings of the 15th international conference on World Wide Web, pages 83–92. ACM, 2006.
[23] Alex Hai Wang. Don’t follow me: Spam detection in twitter. In Security and Cryptography (SECRYPT), Proceedings of the 2010 International Conference on, pages 1–10. IEEE, 2010.
[24] The twitter rules@twitter, 2009. http://help.twitter.com/forums/26257/ entries/18311.
[25] Hongyu Gao, Jun Hu, Christo Wilson, Zhichun Li, Yan Chen, and Ben Y Zhao. Detecting and characterizing social spam campaigns. In Proceedings of the 10th ACM SIGCOMM conference on Internet measurement, pages 35–47. ACM, 2010.
[26] Facebook advertisement checker@tonyq.org, 2013. http://spamgroup.tonyq. org/.
[27] Blacklist@urlblacklist, 2013. http://urlblacklist.com/?sec=download.
[28] Google blacklist@google, 2013. http://www.2600.com/googleblacklist/.
[29] Harris Drucker, Donghui Wu, and Vladimir N Vapnik. Support vector machines for spam categorization. Neural Networks, IEEE Transactions on, 10(5):1048– 1054, 1999.
[30] Le Zhang, Jingbo Zhu, and Tianshun Yao. An evaluation of statistical spam filtering techniques. ACM Transactions on Asian Language Information Pro- cessing (TALIP), 3(4):243–269, 2004.
[31] Google stop-words@google, 2013. http://code.google.com/p/stop-words/.
[32] Chinese corpus group@kip, 2013. http://rocling.iis.sinica.edu.tw/CKIP/
wordsegment.htm.
[33] Graph api (group)@facebook, 2013. http://developers.facebook.com/docs/
reference/api/group/.
[34] Fql (group members)@facebook, 2013. http://developers.facebook.com/
docs/reference/fql/group_member.
[35] Facebook php sdk@github, 2013. https://github.com/facebook/
facebook-php-sdk.
[36] Data use policy-other websites and applications@facebook, 2013. https://www.
facebook.com/about/privacy/your-info-on-other#applications.
[37] Na Wang, Heng Xu, and Jens Grossklags. Third-party apps on facebook: pri- vacy and the illusion of control. In Proceedings of the 5th ACM Symposium on Computer Human Interaction for Management of Information Technology, page 4. ACM, 2011.
[38] The oauth 2.0 authorization framework@ietf, 2012. http://tools.ietf.org/ html/draft-ietf-oauth-v2-31#section-1.2.
[39] Extended permissions@facebook, 2013. http://developers.facebook.com/ docs/reference/login/extended-permissions/.
[40] Access tokens@facebook, 2013. http://developers.facebook.com/docs/ facebook-login/access-tokens/.