과제정보
연구 과제번호 : 스마트TV 2.0 소프트웨어 플랫폼
연구 과제 주관 기관 : 정보통신기술진흥센터, 한국연구재단
참고문헌
- H. Tamada, M. Nakamura, A. Monden, and K. Matsumoto, "Java birthmark Detecting the software theft," IEICE Transactions on Information and Systems, Vol. 88, No. 9, pp. 2148-2158, Sep. 2005.
- G. Myles and C. Collberg, "k-gram Based Software Birthmarks," Proc. of the 2005 ACM Symposium on Applied Computing, pp. 314-318, 2005.
- H. Tamada, K. Okamoto, M. Nakamura, A. Monden, and K. Matsumoto, "Design and evaluation of dynamic software birthmarks based on api calls," Info. Science Technical Report NAIST-IS-TR2007011, ISSN(2007), 0919-9527.
- D. Kim, Y. Han, S. Cho, H. Yoo, J. Woo, Y. Nah, M. Park, and L. Chung, "Measuring similarity of windows applications using static and dynamic birthmarks," Proc. of the 28th Annual ACM Symposium on Applied Computing, pp. 1628-1633, ACM, Mar. 2013.
- Smith T. F., and Waterman M. S., "Identification of Common Molecular Subsequences," Journal of Molecular Biology, Vol. 147, No. 1, pp. 195-197, 1981. https://doi.org/10.1016/0022-2836(81)90087-5
- Rognes, T., "Faster Smith-Waterman database searches with inter-sequence SIMD parallelisation," BMC Bioinformatics, Vol. 12, No. 1, pp. 221, 2011. https://doi.org/10.1186/1471-2105-12-221
- S. Park, and H. Han, "Software Similarity Detection Using Integration of Static and Dynamic Birthmarks," KIISE Winter Conference 2015, Dec. 2015.
- Wang, X., Jhi, Y., Zhu, S., and Liu, P., "Detecting software theft via system call based birthmarks," Proc. of 25th Annual Computer Security Applications Conference, pp. 149-158, 2009.
- S. Park, and H. Han, "Detecting Software Similarity Using API Sequences on Static Major Paths," Journal of KIISE, Vol. 41, No. 12, pp. 1007-1012, Dec. 2014. https://doi.org/10.5626/JOK.2014.41.12.1007
- Intel Pin. [Online]. Available: https://software.intel.com/en-us/articles/pin-a-dynamic-binary-instrumentation-tool
- S. Schleimer, D. S. Wilkerson, and A. Aiken, "Winnowing: Local algorithms for document fingerprinting," Proc. of the 2003 ACM SIGMOD International Conference on Management of Data, pp. 76-85, 2003.
- A System for Detecting Software Plagiarism - MOSS, [Online]. Available: http://theory.stanford.edu/-aiken/moss/