DNS Cache Poisoning/Honeypot Analysis Based on Data Exfiltration Using Stochastic Petri Nets Method to Enhance Cyber Security Hygiene

Abstract

According to some experts, organizations make investments of huge sum of dollars concerning firewalls, encryption, and other tightly closed access devices, yet it is all naught, considering that none regarding these solutions tackle the weakest link within the safety chain. That speech perfectly captures the present day stress experienced by skilled network protection specialists. Researchers’ threat detection techniques can pick up a lot of false positive alarms throughout the detection process; false positive alarms are accountable for company’s unneeded system lock down. A stochastic model is necessary to represent a communication system since the nature of the traffic between them is unpredictable. SPN was utilized in this study to build statistical model for networks with security chains. By permitting the formalization of both real-time and non-Markovian behavior, the new stochastic Petri net formalism improves model fidelity. This allowed us to see special structures within the stochastic processes produced by SPN models. We have applied this principle by proposing an effective simulation method that supports deadlock detection and easy-to-compute point estimates and confidence intervals. The method is novel because it can automatically detect hidden regenerative structures that do not conform to different simple conditions, and can be easily determined by analytical methods.