modeling of cyber-attacks

With the increasing rate of cyber-attacks, creating security for cyberspace has become more important and crucial. Therefore computers, computer networks and all current systems connected to the Internet are always at risk of cyber-attacks. In this paper, a novel technique based on alteration technique of attack is proposed by providing a new classification in the methods of obfuscation. In this method, by replacing the attacks that have similar characteristics in the attack strategies the attacker causes an increase in wrong classification and thus reduces the dependence between attack steps. Therefore, by increasing the length of the attack, network security managers cannot easily distinguish cyber-attacks. The proposed model was assessed based on the Bayesian algorithm. The results of the research and implementation of the model indicate that the accuracy of classification (in terms of log) by intrusion detection systems for the best case of clean attacks in the sequel of attack, is -0.02 and for obfuscation attacks at the action level is -0.19. For obfuscate attacks with the alternative technique it becomes -3 and for the insertion technique it decreases to -6.74. In the proposed model, as in the obfuscation-based insertion technique, the corresponding attack method has been used. Due to the difference in the type of ambiguity model, different results are obtained, and the combination of these two obfuscating techniques in cyber-attacks can bring better results to the attacker in deceiving the intrusion detection systems and creating uncertainties in the sequence of observed attacks.