期刊文献+

一种基于图的程序行为相似性比较方法 被引量:2

Approach for measuring software similarity based on graphs
下载PDF
导出
摘要 针对目前的软件盗版现象,在没有软件源代码的情形下提出一种程序相似性的比较方法。该方法是运用程序系统调用之间的参数依赖关系组成依赖图,对程序行为进行描述;在此基础上定义了一种动态程序胎记,用它比较两个功能类似的应用程序。最后的试验数据表明,该方法能够有效地检测出相似程度不一的各组程序之间的相似度,具有一定的可信度和适用性。 View of software piracy, this paper proposed an approach for measuring software similarity without seurcecode. It created dependence graphs to specify relationships between system call arguments for describing program behavior, based on which defined an dynamic software birthmark. It could be used to measure the similarity of two same-purpose applications. Experimental results indicate that the approach is effective in detecting similarity between two programs in groups of varying degrees similar, which proves its certain degree of credibility and applicability.
出处 《计算机应用研究》 CSCD 北大核心 2010年第2期532-536,551,共6页 Application Research of Computers
基金 国家自然科学基金资助项目(60803130)
关键词 软件剽窃 系统调用 动态软件胎记 相似性 software theft graphs system call dynamic software birthmark similarity
  • 相关文献

参考文献32

  • 1OKAMOTO K, TAMADA H, NAKAMURA M,et al. Dynamic software birthmarks based on API calls[ J]. IEICE Trans on Information and Systems, 2006, 89(8) :1751- 1763.
  • 2TAMADA H, OKAMOTO K, NAKAMURA M, et al. Dynamic software birthmarks to detect the theft of windows applications[ C]//Proc of International Symposium on Future Software Technology. 2004.
  • 3SCHULER D, DALLMEIER V. Detecting software theft with API call sequence sets [ C ]//Proc of Workshop on Software Reengineering.2006.
  • 4SCHULER D, DALLMEIER V, LINDIG C, et al. A dynamic:birthmark for Java[ C]//Proc of the 22nd IEEE/ACM International Conference on Automated Software Engineering. New York:ACM Press, 2007:274- 283.
  • 5CHRISTODORESCU M,JHA S,KRUEGEL C. Mining specifications of malicious behavior[ C ]//Proc of the 6th Joint Meeting European Software Engineering Conference and the ACM SIGSOFT International Symposium on Found Ations of Software Engineering. 2007:3-7.
  • 6TAMADA H, NAKAMURA M, MONDEN A, et al. Detecting the theft of programs using birthmarks, NAIST-IS-TR-2003014[ R]. Nara:Nara Institute of Science & Technology, 2003.
  • 7TAMADA H, NAKAMURA M, MONDEN A, et al. Design and evaluation of birthmarks for detecting theft of Java programs [ C ]//Proc of the LASTED International Conference on Software Engineering. 2004 : 569- 575.
  • 8MYLES G, COLLBERG C. Detecting software theft via whole program path birthmarks[ C ]//Proc of the 7th International Conference on Information Security. Berlin: Spfinger-Verlag, 2004:404- 415.
  • 9BUNKE H, SHEARER K. A graph distance metric based on the maximal common subgraph [ J]. Pattern Recognition Letters, 1998, 19(3-4) :255-259.
  • 10BUNKE H. Graph matching: theoretical foundations, algorithms, and applications [ C ]//Proc of Vision Interface Montreal. 2000:82- 88.

二级参考文献73

  • 1[2]Ottenstein K J.An algorithmic approach to the detection and prevenlion of plagiarism.ACM SIGCSE Bull,1976;8(4):30-41
  • 2[3]Wise M J.YAP3:Improved detection of similarities in computer programs and other texts.In:Proceedings of the SIGCSE'6.1996;130-134.http://citesecr.nj.nec.com/wise96yap.html.
  • 3[4]Rieger M.Effective Clone Detection Without Language Barriers.Ph D thesis,University of Berne,June 2005
  • 4[5]Precheh L,Malpohl G,Phippsen M.Jplag:Finding plagiarisms among a set of programs.Technical Report,Fakultat far Informatik,Universitar Karlsruhe,Germany,2000
  • 5Hofmeyr S A,Forrest S,Somayaji A. Intrusion Detection Using Sequences of System Calls[J].Journal of Computer Security,1998,6:151180.
  • 6Damashek M.Gauging Similarity with n-grams: Language Independent Categorization of Text[J].Science,1995,267:843-848.
  • 7Yihua Liao, Vemuri V R. Using Text Categorization Techniques for Intrusion Detection[J]. In 11th USENIX Security Symposium,2002.
  • 8Helman P,Bhangoo J. A Statistically Based System for Prioritizing Information Exploration under Uncertainty[J].IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans,1997,27(4):449-466.
  • 9Javitz H S,Valdes A. The NIDES Statistical Component: Description and Justification. Technical Report, Computer Science Laboratory, SRI International, Menlo Park, CA, March 1993.
  • 10Eleazar Eskin. Anomaly Detection over Noisy Data Using Learned Probability Distributions. In Proceedings of the Seventeenth International Conference on Machine Learning (ICML-2000), 2000.

共引文献71

同被引文献18

  • 1朱国强,刘真,李宗伯.对计算机系统中程序行为的分析和研究[J].计算机应用,2005,25(12):2739-2741. 被引量:2
  • 2邓爱萍,徐国梁,肖奔.基于串匹配方法的源代码复制检测技术研究[J].科学技术与工程,2007,7(10):2251-2254. 被引量:9
  • 3周以真.计算思维.中国计算机学会通讯,2007,3(11).
  • 4Repenning A, Webb D, Ioannidou A. Scalable game design and the development of a checklist for getting computational think- ing into public schools[C]// Proc. SIGCSE 10. ACM Press, WI,USA,2010.
  • 5Wing J M. Computational Thinking[J]. Communications o{ the ACM,2006,49(3).
  • 6Kozaczynski V, Ning J, Engberts A. Program Concept Recogni- tion and Transformation[J]. IEEE Trans. On Software Eengi- neering, 1992,18(12) : 1065-1075.
  • 7Duscasse S, Rieger M, Demeyer S. A Language Independent Ap- proach for Detecting Duplicated Code[C]//Int' 1 Conf. on Soft- ware Maintenance. 1999:109-118.
  • 8Krinke J. Identifying Similar Code with Program Dependence Graphs[C] // Proceedings Eighth Working Conference on Re- verse Engineering. 2001 : 301-309.
  • 9Lewis C M. How programming environment shapes perceptionl earning and goals: Logo vs. Scratch [C]//Proc. SIC, CSE 10. ACM Press, WI, USA, 2010.
  • 10邓爱萍.程序代码相似度度量算法研究[J].计算机工程与设计,2008,29(17):4636-4638. 被引量:23

引证文献2

二级引证文献5

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部