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Markov Model of Cyber Attack Life Cycle Triggered by Software Vulnerability

Hoffmann Romuald

International Journal of Electronics and Telecommunications

2021

Vol. 67, No. 1

35--41

Software vulnerability life cycles illustrate changes in detection processes of software vulnerabilities during using computer systems. Unfortunately, the detection can be made by cyber-adversaries and a discovered software vulnerability may be consequently exploited for their own purpose. The vulnerability may be exploited by cyber-criminals at any time while it is not patched. Cyber-attacks on organizations by exploring vulnerabilities are usually conducted through the processes divided into many stages. These cyber-attack processes in literature are called cyber-attack live cycles or cyber kill chains. The both type of cycles have their research reflection in literature but so far, they have been separately considered and modeled. This work addresses this deficiency by proposing a Markov model which combine a cyber-attack life cycle with an idea of software vulnerability life cycles. For modeling is applied homogeneous continuous time Markov chain theory.

Genetic search for optimal personalized location areas for future PCS networks

Varadarajan R., Zheng J., Regentova E. E.

Systems Science

2009

Vol. 35, no 2

81-88

In Personal Communication Services (PCS) networks, mobile terminals (MT) are communicating frequently using a variety of services. A high-quality framework is needed for tracking consistently MTs in the system and delivering the services timely. Future PCS networks are expected to have smaller cells to address the transmission power concerns and reuse frequencies efficiently. Thus, MTs are expected to signal even more frequently under always update (AU) strategy adopted in current PCS networks, such as GSM . One pathway for solving the problem is the consideration of Location Areas (LA). The location update takes place only when the MT moves off the area. For call delivery the area is paged. Thus, another signaling component is introduced. In this paper, we propose the design of personalized LA's (PLAs) per an individual user. The model we use takes into account the MT's behavior in the network and the system parameters. The problem is known to be NP-complete of a high computational complexity. We provide a proof of the complexity and solve the problem by using the genetic search for finding a sub-optimal solution. It is shown that the cost of location management under the model and the designed search algorithm can be significantly lower than that consumed by AU mechanism.