Exploiting Spectrum Sensing Data for Key Management

In cognitive radio networks, secondary users (SUs) communicate on unused spectrum slots in the frequency bands assigned to primary users (PUs). Like any other wireless communication system, cognitive radio networks are ex- posed to physical layer attacks. In particular, we focus on two common at- tacks, namely, spectrum sensing data falsification and eavesdropping. Such attacks can be counteracted by using symmetric key algorithms, which how- ever require a complex key management scheme. In this paper we propose a novel algorithm that significantly reduces the complexity of the management of symmetric link keys by leveraging spectrum sensing data that is available to all nodes. In our algorithm, it is assumed that a primary secret key is pre-distributed to the legitimate SUs, which is needed every number of de- tection cycles. With the aid of the information provided in the primary key, our algorithm manipulates the collected samples so that a segment of the estimated sensing statistic at the two legitimate SUs can be used as a seed to generate a common symmetric link key. The link key is then employed to encrypt the transmitted data. Our algorithm exhibits very good performance in terms of bit mismatch rate (BMR) between two link keys generated at the two legitimate SUs. In addition, our solution is robust against the difference in the received signal to noise ratio between two legitimate SUs thus making it suitable for practical scenarios. Furthermore, our algorithm exploits the decision statistic that SUs use for spectrum sensing, hence, it does require neither extra processing nor extra time, allowing the SUs to quickly and securely tab into empty spectrum slots

Spectrum Sensing and Security Challenges and Solutions: Contemporary Affirmation of the Recent Literature

Cognitive radio (CR) has been recently proposed as a promising technology to improve spectrum utilization by enabling secondary access to unused licensed bands. A prerequisite to this secondary access is having no interference to the primary system. This requirement makes spectrum sensing a key function in cognitive radio systems. Among common spectrum sensing techniques, energy detection is an engaging method due to its simplicity and efficiency. However, the major disadvantage of energy detection is the hidden node problem, in which the sensing node cannot distinguish between an idle and a deeply faded or shadowed band. Cooperative spectrum sensing (CSS) which uses a distributed detection model has been considered to overcome that problem. On other dimension of this cooperative spectrum sensing, this is vulnerable to sensing data falsification attacks due to the distributed nature of cooperative spectrum sensing. As the goal of a sensing data falsification attack is to cause an incorrect decision on the presence/absence of a PU signal, malicious or compromised SUs may intentionally distort the measured RSSs and share them with other SUs. Then, the effect of erroneous sensing results propagates to the entire CRN. This type of attacks can be easily launched since the openness of programmable software defined radio (SDR) devices makes it easy for (malicious or compromised) SUs to access low layer protocol stacks, such as PHY and MAC. However, detecting such attacks is challenging due to the lack of coordination between PUs and SUs, and unpredictability in wireless channel signal propagation, thus calling for efficient mechanisms to protect CRNs. Here in this paper we attempt to perform contemporary affirmation of the recent literature of benchmarking strategies that enable the trusted and secure cooperative spectrum sensing among Cognitive Radios

State-of-the-art authentication and verification schemes in VANETs:A survey

Vehicular Ad-Hoc Networks (VANETs), a subset of Mobile Ad-Hoc Networks (MANETs), are wireless networks formed around moving vehicles, enabling communication between vehicles, roadside infrastructure, and servers. With the rise of autonomous and connected vehicles, security concerns surrounding VANETs have grown. VANETs still face challenges related to privacy with full-scale deployment due to a lack of user trust. Critical factors shaping VANETs include their dynamic topology and high mobility characteristics. Authentication protocols emerge as the cornerstone of enabling the secure transmission of entities within a VANET. Despite concerted efforts, there remains a need to incorporate verification approaches for refining authentication protocols. Formal verification constitutes a mathematical approach enabling developers to validate protocols and rectify design errors with precision. Therefore, this review focuses on authentication protocols as a pivotal element for securing entity transmission within VANETs. It presents a comparative analysis of existing protocols, identifies research gaps, and introduces a novel framework that incorporates formal verification and threat modeling. The review considers key factors influencing security, sheds light on ongoing challenges, and emphasises the significance of user trust. The proposed framework not only enhances VANET security but also contributes to the growing field of formal verification in the automotive domain. As the outcomes of this study, several research gaps, challenges, and future research directions are identified. These insights would offer valuable guidance for researchers to establish secure authentication communication within VANETs

Autonomic Vehicular Networks: Safety, Privacy, Cybersecurity and Societal Issues

Safety, efficiency, privacy, and cybersecurity can be achieved jointly in self-organizing networks of communicating vehicles of various automated driving levels. The underlying approach, solutions and novel results are briefly exposed. We explain why we are faced with a crucial choice regarding motorized society and cyber surveillance