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.

[EN] Wireless Sensor Networks (WSNs) are vital for collecting data from remote environments. Nevertheless, the limited energy resources of sensor nodes render energy-efficient routing a critical concern for the successful operation of WSNs. To address these concerns, clustering, and routing are essential tasks in WSNs; clustering aims to organize sensor nodes into groups or clusters to minimize energy usage and prolong the network's lifespan. On the other hand, routing involves determining the optimum paths for transmitting data from the source nodes to the destination nodes. Nonetheless, it has been established that the current energy-efficient routing problem is an NP-hard, requiring a trade-off between energy and overall network performance. In this paper, we proposed a Hybrid Whale-Ant Optimization Algorithm (WAOA) for energy-efficient routing in WSNs. The proposed WAOA utilizes the Whale Optimization Algorithm (WOA) to find the suitable cluster head in the predefined search space, while the Ant Colony Optimization (ACO) searches the optimal route from the source cluster sensors to the cluster head within its predefined space. Linear programming construction is employed to formulate optimization problems for cluster head selection and search for the optimal route. The performance analysis demonstrates that the proposed WAOA performs better than MOORP, MMABC, and AZEBR by 5.78 %,16.11 %, and 18.52 %, respectively, in terms of network lifetime.

Internet of Things (IoT) technologies rapidly evolve and are used in many real-life applications. One of the core technologies used in various IoT applications is Radio Frequency IDentification (RFID) technology. RFID wirelessly and uniquely identifies the tagged objects without a direct line of sight. However, the research community had reported privacy and security-related concerns in RFID systems, where an adversary may tamper, eavesdrop, add, delete, or even modify the transmitted messages over an insecure communication channel. To address the issues mentioned above, we propose an Efficient, Secure, and practical ultra-lightweight RFID Authentication Scheme (ESRAS), which uses rank operation for low-cost tags. We utilize a simplistic bitwise exclusive-OR, circular left rotation, and a newly proposed ultra-lightweight rank operation to provide high security at low cost. The analysis of ESRAS concerning its security and performance shows that it effectively resists several known attacks and is relatively superior to the existing schemes regarding the computational and storage costs. Moreover, ESRAS shows more suitability for low-cost RFID tags and can be executed in a multimedia big data environment.

Over recent years, the Industrial Internet of Things and connectivity of the various sensors on the industrial and automaton front have played a crucial role in the manufacturing process. Production ventures are predominantly represented by Industry 4.0 so produce colossal information. Data outsourcing is one of the ways to manage the overhead of the massive data generated from the various resource-constrained devices utilized in the industrial environment. Therefore, the crowdsourced data from many organizations are outsourced to the cloud system. However, privacy and security challenges such as illegal admittance, data leakage are raised by the outsourced storage. Data authentication is an optimistic approach to establishing the integrity, confidentiality, and authenticity of the data. The certificateless signcryption scheme is most appropriate for lightweight devices established in the industrial ecosystem. In this article, we propose a privacy-conserving, lightweight data aggregation scheme to attain security in an industrial network. In the proposed model, the data owner collects the industrial data from various resource-constrained devices and sends this data to the data aggregator and proficiently data obtained by the industrial data user securely. Particularly, in this article, we propose a proficient certificateless aggregated signcryption scheme, which provides a data aggregation element in comparison to existing schemes. Our proposed scheme includes mutual authentication, public viability, integrity and confidentiality of data, volatile to key escrow, and privacy-preserving aspects for the industrial data. Performance evaluation and result analysis demonstrate that the proposed protocol performs better than other schemes significantly.