Biblio

Considered is a network of parallel wireless channels in which individual parties are engaged in secret communication under the protection of cooperative jamming. A strategic eavesdropper selects the most vulnerable channels to attack. Existing works usually suggest the defender allocate limited cooperative jamming power to various channels. However, it usually requires some strong assumptions and complex computation to find such an optimal power control policy. This paper proposes a probabilistic cooperative jamming scheme such that the defender focuses on protecting randomly selected channels. Two different cases regarding each channel’s eavesdropping capacity are discussed. The first case studies the general scenario where each channel has different eavesdropping capacity. The second case analyzes an extreme scenario where all channels have the same eavesdropping capacity. Two non-zero-sum Nash games model the competition between the network defender and an eavesdropper in each case. Furthermore, considering the case that the defender does not know the eavesdropper’s channel state information (CSI) leads to a Bayesian game. For all three games, we derive conditions for the existence of a unique Nash equilibrium (NE), and obtain the equilibria and the value functions in closed form.

Attacks by Jamming on wireless communication network can provoke Denial of Services. According to the communication system which is affected, the consequences can be more or less critical. In this paper, we propose to develop an algorithm which could be implemented at the reception stage of a communication terminal in order to detect the presence of jamming signals. The work is performed on Wi-Fi communication signals and demonstrates the necessity to have a specific signal processing at the reception stage to be able to detect the presence of jamming signals.

Wireless communication network (WCN) performance is primarily depends on physical layer security which is critical among all other layers of OSI network model. It is typically prone to anomaly/malicious user's attacks owing to openness of wireless channels. Cognitive radio networking (CRN) is a recently emerged wireless technology that is having numerous security challenges because of its unlicensed access of wireless channels. In CRNs, the security issues occur mainly during spectrum sensing and is more pronounced during distributed spectrum sensing. In recent past, various anomaly effects are modelled and developed detectors by applying advanced statistical techniques. Nevertheless, many of these detectors have been developed based on sensing data of one variable (energy measurement) and degrades their performance drastically when the data is contaminated with multiple anomaly nodes, that attack the network cooperatively. Hence, one has to develop an efficient multiple anomaly detection algorithm to eliminate all possible cooperative attacks. To achieve this, in this work, the impact of anomaly on detection probability is verified beforehand in developing an efficient algorithm using bivariate data to detect possible attacks with mahalanobis distance measure. Result discloses that detection error of cooperative attacks by anomaly has significant impact on eigenvalue-based sensing.