동시출현 단어분석 기반 스팸 문자 탐지 기법
Coward Analysis based Spam SMS Detection Scheme
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초록
스팸 데이터 셋은 통상적으로 공개적으로 구하기 어렵고 기존 연구들은 대부분 스팸 이메일에 초점이 맞춰져 왔기 때문에 스팸 문자 메시지 자체 특성을 분석하는데 한계가 있었다. 스팸 이메일 특성 분석 활용 및 데이터 마이닝기법 등의 활용을 통한 기존 연구들이 있었지만, 영향력이 높은 단일 단어를 활용한 스팸 문자 탐지 기법에 한정되어 있다는 한계점이 있다. 본 논문에서는 싱가폴 대학교에서 공개적으로 공개한 스팸 문자메시지를 다 각도에서 실험 및 분석하여 스팸 문자의 특성을 밝히고 동시출현 단어분석 기반의 스팸 문자 탐지 기법을 제안한다. 성능평가결과, 제안하는 기법의 거짓 양성과 거짓 음성이 2%미만임을 보였다.
Abstract
Analyzing characteristics of spam text messages had limitations since spam datasets are typically difficult to obtain publicly and previous studies focused on spam email. Although existing studies, such as through the use of spam e-mail characterization and utilization of data mining techniques, there are limitations that influence is limited to high spam detection techniques using a single word character. In this paper, we reveal the characteristics of the spam SMS based on experiment and analysis from different perspectives and propose coward analysis based spam SMS detection scheme with a publicly disclosed spam SMS from the University of Singapore. With the extensive performance evaluations, we show false positive and false negative of the proposed method is less than 2%.
참고문헌 (10)
- T. M. Mahmoud, "SMS Spam Filtering Technique Based on Artificial Immune System", International Journal of Computer Science Issues(IJCSI), 9, pp.589~597 (2012)
- T. A. Almeida, "Contributions to the study of SMS spam filtering : new collection and results", Proceedings of the 11th ACM symposium on Document engineering, pp.259~262 (2011)
- J. M. Gómez Hidalgo, "Content Based SMS Spam Filtering", Proceedings of the 2006 ACM Symposium on Document Engineering, Amsterdam, The Netherlands, pp.107~114 (2006)
- Gordon V. Cormack, "Feature Engineering for Mobile(SMS)Spam Filtering", ACM SIGIR’07, pp.871~872 (2007)
- Huang Jie, "A Bayesian Approach for Text Filter on 3G Network", Proceedings of the 6th International Conference on Wireless Communications Networking and Mobile Computing, pp.1~5 (2010)
- Wuying Liu, "Index-based Online Text Classification for SMS Spam Filtering", Journal of Computers, 5(6), pp.844~851 (2010)
- Xia Hu, "Sampling of Mass SMS Filtering Algorithm Based on Frequent Time-domain Area", Proceedings of the Third International Conference on Knowledge Discovery and Data Mining, pp.548~551 (2010)
- Zi Chu, "Who is tweeting on twitter : human, bot, or cyborg?", In Gates, 21~30 (2010)
- Sarah Jane Delany, "SMS Spam Filtering : Methods and Data", Expert Systems with Applications, 39(10), pp.9899~9908 (2012)
- Almeida, T.A., "Towards SMS Spam Filtering : Results under a New Dataset", International Journal of Information Security Science (IJISS), 2(1), pp.1~18 (2013)