Modeling of cyber-attacks obfuscation based on the attack analogous to the technique of insertion attacks

Document Type : Original Article

Authors

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Abstract

One of the most important threats of recent years in computer systems and cyber space is ambiguous cyber-attack. Obfuscation at the level of attack means change of attack, without change in behavior and change in the type of impact of attack on the victim. In this paper, a new classification method has been proposed for  modeling cyber attacks, a method based on the technique of insertion attacks. In this method, by increasing the wrong classification in attack strategies, the dependency between the warnings and precautions is separated; so, by increasing the length of the attack, network security managers cannot easily distinguish cyber-attacks. The proposed model is based on Bayesian algorithm. Tables and the assessment figures show the proper formulation of the mechanisms provided for the sequence of attacks so that the detection of obfuscation attacks is far less likely than clean attacks. By increasing the sequence of attacks, the correct classification accuracy tends to zero. The proposed method for obfuscation of the attacks due to the ability to mislead the intrusion detection systems and to create uncertainty in the sequence of the observed attacks, has better performance than the obfuscation logic at both code and action level. 

Keywords


   [1]      A.Kott, C.Wang, and R.F.Erbacher,Cyber defense and situational awareness, vol.62.Springer,2015.##
   [2]      I.You and K.Yim, “Malware Obfuscation techniques: A Brief Survey”, in Beoadband, Wireless Computing, Communication and Applications (BWCCA), International Conference, 2010.##
   [3]      H. Debar and M. Dacier, “Towards a taxonomy of intrusion-detection systems,” Computer Networks, vol. 31, no. 8, pp. 805 – 822, 1999.##
   [4]      S.Parsa,H.salehi,M.H.Alaeiyan,”Code Obfuscation to Prevent Symbolic Execution”, Journal of Electoronic & Cyber defence, Imam Hossein Comprhensive Univercity, Vol. 6,No. 1, 2018 (persion)##
   [5]      H.Du, “Probabilistic Modeling and Inference for Obfuscated Network Attack   Sequences”, PhD diss, Rochester, New York, 8-2014.##
   [6]      M.H.Najari,” The design and simulation of an efficient algorithm for modeling the obfuscation of cyber attacks based on action insertion”, M.Sc, Malek-e-Ashtar University, 2017 (persion)##
   [7]      N.Ghafori,” The design and simulation of an efficient algorithm for modeling the obfuscation of cyber attacks based on action alteration”, M.Sc, Malek-e-Ashtar University, 2017 (persion)##
   [8]      R. Aliabadi,” The design and simulation of an efficient algorithm for modeling the obfuscation of cyber attacks based on action removal”, M.Sc, Malek-e-Ashtar University, 2017 (persion)##
   [9]      L. Wang, A. Liu, and S. Jajodia, “Using attack graphs for correlating, hypothesizing, and predicting intrusion alerts,” Comput. Commun, vol. 29, no. 15, pp. 2917–2933, 2006.##
[10]      C. Phillips and L. P. Swiler, “A graph-based system for network-vulnerability analysis,” presented at the Proceedings of the 1998 workshop on new security paradigms, 1998, pp. 71–79.##
[11]      T. Tidwell, R. Larson, K. Fitch, and J. Hale, “Modeling internet attacks,” presented at the Proceedings of the 2001 IEEE Workshop on Information Assurance and security, 2001, vol. 59.##
[12]      K. Daley, R. Larson, and J. Dawkins, “A structural framework for modeling multi-stage network attacks,” presented at the Parallel Processing Workshops, 2002. Proceedings. International Conference on, 2002, pp. 5–10.##
[13]      S. Noel and S. Jajodia, “Advanced vulnerability analysis and intrusion detection through predictive attack graphs,” Crit. Issues C4I Armed Forces Commun. Electron. Assoc. AFCEA Solut. Ser. Int. J. Command Control, 2009##
[14]      Common Attack Pattern Enumeration and Classification (CAPEC) Schema Description, May2017##
[15]      Q.Xinzhou, l.Wenke,”Attack plan Recognition and prediction using causal network”, proceedings of the 20th Annual computer security Application conference, 2004.##
[16]      Grinstead, Charles Miller, and James Laurie Snell, eds. Introduction to probability. American Mathematical Soc, 1997.##
  • Receive Date: 01 December 2018
  • Revise Date: 21 January 2019
  • Accept Date: 05 March 2019
  • Publish Date: 20 February 2020