Biblio

The proliferation of autonomous and connected vehicles on our roads is increasingly felt. However, the problems related to the optimization of the energy consumed, to the safety, and to the security of these do not cease to arise on the tables of debates bringing together the various stakeholders. By focusing on the security aspect of such systems, we can realize that there is a family of problems that must be investigated as soon as possible. In particular, those that may manifest as the system expands. Therefore, this work aims to model and simulate the behavior of a system of autonomous and connected vehicles in the face of a malware invasion. In order to achieve the set objective, we propose a model to our system which is inspired by those used in epidimology, such as SI, SIR, SIER, etc. This being adapted to our case study, stochastic processes are defined in order to characterize its dynamics. After having fixed the values of the various parameters, as well as those of the initial conditions, we run 100 simulations of our system. After which we visualize the results got, we analyze them, and we give some interpretations. We end by outlining the lessons and recommendations drawn from the results.

Wireless Personal Area Network is widely used in day to day life. It might be a static or dynamic environment. As the density of the nodes increases it becomes difficult to handle the situation. The need of multiple sensor node technology in a desired environment without congestion is required. The use of autonomic network provides one such solution. The autonomicity combines the local automate and address agnostic features that controls the congestion resulting in improved throughput, fault tolerance and also with unicast and multicast packets delivery. The algorithm LA based ANA in a Bluetooth based dynamic environment provide 20% increase in throughput compared with LACAS based Wireless Sensor Network. The LA based ANA leads with 10% lesser fault tolerance levels and extended unicast and multi-cast packet delivery.

In this paper, we consider a stochastic model to evaluate the system availability of an intrusion tolerant system (ITS), where the system undergoes the patch management with a periodic vulnerability checking strategy, i.e., a pull-type patch management. Based on the model, this paper discusses the appropriate timing for patch applying. In particular, the paper models the attack behavior of adversary and the system behaviors under reactive defense strategies by a composite stochastic reward net (SRN). Furthermore, we formulate the interval availability by applying the phase-type (PH) approximation to solve the Markov regenerative process (MRGP) models derived from the SRNs. Numerical experiments are conducted to study the sensitivity of the system availability with respect to the number of checking.

Popularization of the Internet-of-Things (IoT) has brought widespread concerns on IoT security, especially in face of several recent security incidents related to IoT devices. Due to the resource-constrained nature of many IoT devices, security offloading has been proposed to provide good-enough security for IoT with minimum overhead on the devices. In this paper, we investigate the inevitable risk associated with security offloading: the unprotected and unmonitored transmission from IoT devices to the offloaded security mechanisms. An important challenge in modeling the security risk is the dynamic nature of IoT due to demand fluctuations and infrastructure instability. We propose a stochastic model to capture both the expected and worst-case security risks of an IoT system. We then propose a framework to efficiently address the optimal robust deployment of security mechanisms in IoT. We use results from extensive simulations to demonstrate the superb performance and efficiency of our approach compared to several other algorithms.