Reliability and Optimum Cost Analysis of Malware Infected System by Discrete-Time Negative Arrival Retrial Queue.

The failure of computer software system is inevitable and it is important to analyze the performance of the system. It is equally important to consider the cost factor that occurs during repair. This paper models malware infected system and analyzes its behavior using a hybrid technique. A likelihood estimation is used for filtering malwares and improving the performance of the system. A discrete-time single server retrial queue with two types of arrivals is modeled to address infected system characteristics. A request which is originally legitimate known as the positive arrival, who finds the host free gets instant service; otherwise it joins the buffer. The malware (request) which is not detected by the filter known as the negative arrival will lead to the breakdown of the server, irrespective of the fact that the server is idle or busy. Further, it is assumed that suspicious request has no impact on the system when the server is under repair. Once the server is affected by suspicious request, it is sent for repair immediately. The retrial, service, and repair times are arbitrarily distributed. Performance characteristics such as mean buffer size, mean waiting time have been obtained. The reliability measures such as server availability, failure frequency, probability of packet lost, reliability of the underlying queueing system have also been derived. A cost model has been developed. The efficacy of filtering method and its level of accuracy have been demonstrated experimentally. The infected system has been detected from the performance measures and reliability metrics. A comparative study with and without filtering has been discussed numerically. The optimum cost analysis has also been presented. [ABSTRACT FROM AUTHOR]