142
Views
1
CrossRef citations to date
0
Altmetric
Original Articles

Statistics and recognition for software birthmark based on clustering analysis

Pages 308-324 | Received 03 Mar 2015, Accepted 18 Mar 2016, Published online: 21 Apr 2016

References

  • J. Al-Kofahi, G. Lisong, H.V. Nguyen, H.A. Nguyen, and T.N. Nguyen, Static detection of configuration-dependent bugs in configurable software, 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering (ICSE), 2015, Vol. 2, pp. 795–796.
  • F. Amiri, M.M. Rezaei Yousefi, C. Lucas, A. Shakery, and N. Yazdani, Mutual information-based feature selection for intrusion detection systems, J. Netw. Comp. Appl. 34 (2011), pp. 1184–1199. doi: 10.1016/j.jnca.2011.01.002
  • M. Boareto, J. Cesar, V.B.P. Leite, and N. Caticha, Supervised variational relevance learning, an analytic geometric feature selection with applications to omic datasets, ACM Comput. Biol. Bioinform. 12 (2015), pp. 705–711.
  • D. Bruschi, L. Martignoni, and M. Monga, Detecting self-mutating malware using control-flow graph matching, Detection Intrusions and Malware Vulnerability Assess. 4064 (2006), pp. 129–143. doi: 10.1007/11790754_8
  • H. Cheng, Z. Qin, W. Qian, and W. Liu, Conditional mutual information based feature selection, Proceedings of the Knowledge Acquisition and Modeling (KAM’08), IEEE, 2008, pp. 103–107.
  • T.M. Cover and J.A. Thomas, Elements of Information Theory, John Wiley & Sons, Stanford University, 2006.
  • S. Danicic, R.M. Hierons, and M.R. Laurence, On the computational complexity of dynamic slicing problems for program schemas, Math. Structures Comput. Sci. 21 (2011), pp. 1339–1362. doi: 10.1017/S0960129511000223
  • B. Fish, A. Khan, N. Hajj Chehade, C. Chien, and G. Pottie, Feature selection based on mutual information for human activity recognition, Proceedings of the 37th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), IEEE, 2012, pp. 1729–1732.
  • W. Gang, W. Jun, and W. Mingyu, Modular-transform based clustering, J. Appl. Statist. 40 (2013), pp. 2749–2759. doi: 10.1080/02664763.2013.790007
  • J.K.M. Han, Data Mining:Concepts and Techniques, Morgan Kaufmann, CA, 2001.
  • Y. Jeon and S. Yoon, Multi-threaded hierarchical clustering by parallel nearest-neighbor chaining [C], IEEE Trans. Parallel Distrib. Syst. 26 (2015), pp. 2534–2548. doi: 10.1109/TPDS.2014.2355205
  • J. Jia, N. Yang, C. Zhang, A. Yue, J. Yang, and D. Zhu, Object-oriented feature selection of high spatial resolution images using an improved relief algorithm, Comput. Comput. Technol. 5 (2013), pp. P619–626.
  • Y.X. Luo and D.Y. Fnag, Feature selection for software birthmark based on cluster analysis, Chinese J. ACTA Electron. NICA 41 (2013), pp. 2334–2338.
  • G. Myles and C. Collberg, K-gram based, Proceedings of the 2005 ACM Symposium on Applied Computing, New York, ACM, 2005, pp. 314–318.
  • S. Patel and T. Pattewar, Software birthmark based theft detection of Javascript programs using agglomerative clustering and improved frequent subgraph mining, 2014 International Conference on Advances in Electronics, Computers and Communications (ICAECC), 2014, pp. 1–6.
  • M. Shtern and V. Tzerpos, Methods for selecting and improving software clustering algorithms, Softw.-PracticeExpe. 44 (2014), pp. 33–46. doi: 10.1002/spe.2147
  • H. Tamada, M. Nakamura, A. Monden, and K. Matsumoto, Design and evaluation of birthmarks for detecting theft of java programs, Proceedings of the International Conference on Software Engineering, 2004, pp. 569–575.
  • Z. Tian, Q. Zheng, T. Liu, M. Fan, E. Zhuang, and Z. Yang, Software plagiarism detection with birthmarks based on dynamic key instruction sequences, Proceedings of the Int. Symp. on, 2015, Vol. 41, pp. 1217–1235.
  • UCI, Repository of machine learning databases [M/OL], 2016. Available at http://www.ics.uci.edu/~mlearn/MLRepository.html.
  • Weka Wiki, [M/OL], 2016. Available at http://weka.sourceforge.net/wiki.
  • Z. Xin, H. Chen, X. Wang, P. Liu, S. Zhu, B. Mao, and L. Xie, Replacement attacks on behavior based software birthmark, Proceedings of the 14th international conference on Information security, 2011, pp. 1–16.
  • B. Yadegari, B. Johannesmeyer, B. Whitely, and S. Debray, A generic approach to automatic deobfuscation of executable code, Proceedings of the Security and Privacy (SP), 2015, pp. P674–691.
  • W. Yanyan, W. Yanning, and R. Jiadong, A sequence clustering method for analyzing software fault feature, ICIC Express Lett. 8 (2014), pp. P1627–1632.
  • F. Ye, Z. Zhang, K. Chakrabarty, and X. Gu, Information-theoretic syndrome evaluation, statistical root-cause analysis, and correlation-based feature selection for guiding board-level fault diagnosis, Computer-Aided Des. Integr. Circuits Syst. 34 (2015), pp. P1014–1026. doi: 10.1109/TCAD.2015.2399438
  • L. Yu and H. Liu, Efficient feature selection via analysis of relevance and redundancy, J. Mach. Learn. Res. 5 (2004), pp. 1205–1224.
  • X. Zhou, X. Sun, G. Sun, and Y. Yang, A combined static and dynamic software birthmark based on component dependence graph, Proceedings of the 2008 Intelligent Software Birthmarks Information Hiding and Multimedia Signal Processing, IEEE, 2008, pp. 1416–1421.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.