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A Program Threat Judgement Model Based on Fuzzy Set Theory

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Information Technology and Intelligent Transportation Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 455))

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Abstract

In the age of information security, whether a program is threatening or not is a crucial problem to solve. In this paper, a novel threat program judgment model based on fuzzy set theory is proposed. In the model, we derive a new evaluation function from multi-factor determined fuzzy synthetic function. Using the function, the program threat is evaluated by the membership of programs with great threat. Furthermore, we realize the judgment model and the experiment data shows its feasibility and effectiveness.

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References

  1. Nath H, Mehtre BM (2014) Static malware analysis using machine learning methods recent trends in computer networks and distributed systems security. Springer, Heidelberg

    Google Scholar 

  2. Feng Y, Anand S, Dillig I (2014) Apposcopy: semantics-based detection of android malware through static analysis. In: Proceedings of the 22nd ACM SIGSOFT international symposium on foundations of software engineering. ACM, pp 576–587

    Google Scholar 

  3. Kruegel C (2014) Full System Emulation: achieving successful automated dynamic analysis of evasive malware. In: Proceeding of BlackHat USA security conference

    Google Scholar 

  4. Vinod P, Jain H, Golecha YK, Gaur SM, Laxmi V (2010) MEDUSA: MEtamorphic malware dynamic analysis usingsignature from API. In: Proceedings of the 3rd international conference on security of information and networks. ACM, pp 263–269

    Google Scholar 

  5. Bayer U, Moser A, Kruegel C, Kirda E (2006) Dynamic analysis of malicious code. J Comput Virol 2(1):67–77

    Article  Google Scholar 

  6. Zhang B, Yin J, Hao J (2005) Using fuzzy pattern recognition to detect unknown malicious executables code., Fuzzy systems and knowledge discovery. Springer, Heidelberg

    Google Scholar 

  7. Fu W, Wei B, ZHAO R, Pang J (2010) Fuzzy reasoning model for analysis of program maliciousness. J Commun, vol 31(1)

    Google Scholar 

  8. Kaspersky Lab: antivirus software (2006). http://www.kaspersky.com/

  9. Egele M, Scholte T, Kirda E, Kruegel C (2012) A survey on automated dynamic malware-analysis techniques and tools. ACM Comput Surv 44:1C49

    Article  Google Scholar 

  10. Baoqing Hu (2010) Fundamentals of fuzzy theory. Fuzzy systems and mathematics, 2nd edn. pp 45–45

    Google Scholar 

  11. Zadeh Lotfi A (1965) Fuzzy sets. Inf control 8(3):338–353

    Article  MathSciNet  MATH  Google Scholar 

  12. Thomas B (1763) An essay towards solving a problem in the doctrine of chances. By the late Rev. Mr. Bayes, FRS communicated by Mr. Price, in a letter to John Canton, A.M.F.R.S. Philosophical Transactions, Giving Some Account of the Present Undertakings, Studies and Labours of the Ingenious in Many Considerable Parts of the World 53:370C418

    Google Scholar 

  13. Zadeh LA (1968) Probability measures of fuzzy events. J Math Anal Appl 23(2):421–427

    Article  MathSciNet  MATH  Google Scholar 

  14. Kukov M, Mirko N (2013) Principles of inclusion and exclusion for fuzzy sets. Fuzzy Sets Syst 232:98–109

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgments

This work is supported by National Natural Science Foundation of China under Grant No. 61472447, and also supported by Shanghai Commission of Science and Technology Research Project under Grant No. 13DZ1108800.

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Correspondence to Xiaochuan Zhang .

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Zhang, X., Pang, J., Zhang, Y., Liang, G. (2017). A Program Threat Judgement Model Based on Fuzzy Set Theory. In: Balas, V., Jain, L., Zhao, X. (eds) Information Technology and Intelligent Transportation Systems. Advances in Intelligent Systems and Computing, vol 455. Springer, Cham. https://doi.org/10.1007/978-3-319-38771-0_22

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  • DOI: https://doi.org/10.1007/978-3-319-38771-0_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-38769-7

  • Online ISBN: 978-3-319-38771-0

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