The technology of Autonomous Vehicles (AVs) and Unmanned Aerial Vehicles (UAVs) has evolved and contributed to improving road safety and traffic efficiency in Intelligent Transportation Systems (ITS). ITS applications are dependent on a communication network formed between AVs and UAVs suffer from security and privacy issues owing to vulnerable wireless communication channels. Considering these issues, SP2AP, a Physically Unclonable Function (PUF) and Elliptic Curve Cryptography (ECC)-based efficient and reliable privacy-preserving authentication protocol for secure UAV-UAV communications in IoT systems is presented in this paper. The proposed protocol not only offers anonymity and untraceability features but also mitigates UAV capture attacks. A robust informal security analysis confirms that the SP2AP protocol safeguards against various known security attacks, such as masquerade, Man-In- The-Middle (MITM), Ephemeral Secret Leakage (ESL), replay, node tampering, cloning, etc. The proposed protocol offers other security features, including mutual authentication, secure key agreement, no clock synchronization, user anonymity, untraceability, (for/back)ward secrecy, property, and drone-to-drone direct authentication. The formal security proof is performed using the Real-OR-Random (ROR) model, and the Scyther tool also demonstrates that the SP2AP protocol is more robust in terms of security and privacy. Performance analysis evaluates computation and communication costs, which show better superiority compared to similar existing protocols.

With the rapid advancements in wireless communication technologies, Unmanned Aerial Vehicles (UAVs), also known as Small Unmanned Aerial Vehicles (SUAVs) or drones, have been increasingly used in various applications, including the civilian sector. As a result, the security of SUAVs has garnered significant attention from the research community. Furthermore, drones are resource-constrained in nature and can be vulnerable to various known cybersecurity attacks over wireless communication. In light of these considerations, we propose aProvablySecure andReliable Privacy-Preserving AuthenticationScheme forDrone-to-Drone Communications in Internet of Autonomous Things (PSRS-D2D). The proposed scheme employs a secure one-way cryptographic hash and Elliptic Curve Cryptography (ECC) to accomplish a certain level of security. We provide security and privacy analysis, comparing it with competing UAV authentication schemes. This ensures that the PSRS-D2D scheme can withstand various prominent security properties, including mutual authentication and strong anonymity, and is secure against several attacks, such as replay, impersonation, and Man-In-The-Middle (MITM) attacks. We evaluated the performance of the proposed scheme in terms of computational and communicational costs. Furthermore, we conducted a formal security analysis using the Real-Or-Random (ROR) model and the Scyther simulation tools, which demonstrate that our scheme offers significant advantages in terms of security and performance.

With the rapid proliferation of the Internet of Things (IoT), autonomous vehicles (AVs), or self-driving cars, rely heavily on real-time data sharing and message exchanges over wireless networks. AVs use sensors, artificial intelligence, machine learning, and advanced algorithms to perform various functions, enabling users to operate without human intervention. Owing to the flexibility and high mobility of drones, they could aid in the operations of AVs. However, the security and privacy are the main concerns; specifically, the threat of physical capture and violation of anonymity are the main hurdles for realization of secure communication among the AVs and drones. To address these challenges, we propose an anonymous and provably secure lightweight authentication protocol for unmanned-aerial-vehicle-assisted Internet of Autonomous Vehicles (SLAP-IoAV). The proposed protocol uses cryptographic primitives such as exclusive-OR operations, elliptic-curve cryptography, collision-resistant one-way hashing, and concatenation to ensure robust security. An informal security analysis found that SLAP-IoAV is secure against several known attacks, and a performance analysis established that the protocol has less computational and communication overhead than existing competitive protocols. Additionally, Scyther simulation results confirm that no security vulnerabilities are present. Overall, our protocol delivers superior security and performance, making it well-suited to real-world applications in the AV industry.

Intelligent Transportation Systems (ITS) dwell on Vehicular Ad-hoc NETworks (VANETs) for message dissemination to achieve the goal of traffic safety and efficiency. VANETs achieve communication among vehicles and roadside units via wireless communication. Hence, security and privacy are significant concerns to be addressed for an effective application of secure VANETs in any ITS. Researchers have addressed these issues with trust management-based schemes or cryptography-based schemes. While these schemes can secure VANETs, they have various limitations presenting hindrances in their deployment. In this context, we have proposed a Blockchain-assisted Trust Computation with a Conditional Privacy-preserving Authentication (BTC2PA) scheme for connected vehicles. The BTC2PA scheme uses a blockchain (Ethereum) assisted PKI infrastructure with digital signatures to achieve authentication for secure communication. Furthermore, it integrates a trust score computation scheme based on a reward and punishment mechanism to provide resistance against internal attacks. The feasibility and validity of the proposed BTC2PA scheme have been studied by implementation work in Rinkeby (Ethereum test network) and extensive simulations using NS-3. The results obtained show that the proposed BTC2PA scheme meets the security and privacy requirements while significantly improving the performance metrics such as communication, storage, computation cost, and end-to-end delay when compared to existing schemes.