The position-based routing of Vehicular Ad hoc Network (VANET) vulnerable to various security attacks because of dependency on computing, control, and communication technologies. The Internet of Things (IoT)-enabled VANET application leads to the challenges such as integrity, access control, availability, privacy protection, non-repudiation, and confidentiality. Several security solutions have been introduced for two decades in two categories as cryptography-based and trust-based. Due to the high computation complexity, cryptography-based solutions are outperformed by recent intelligent trust-based mechanisms. The trust-based techniques are lightweight and effective against the well-known security threats in VANET. The objective of this paper has to design a novel position-based routing in which the conduct of vehicles assessed to accomplish reliable VANET communications. Attack Resilient Position-based VANET Protocol (ARPVP) proposed to detect and prevent malicious vehicles in the network using the trust evaluation technique and artificial intelligence (AI). In the first phase of ARPVP, the periodic self-trust assessment algorithm has designed using various trust parameters to detect unreliable vehicles in the network. In the second phase of ARPVP, the position-based route formation algorithm has designed using the AI technique Ant Colony Optimization (ACO). ACO solves the problem of reliable route formation by neglecting the attacker's using a trust-based fitness function. The trust parameters of each vehicle as mobility, buffer occupancy, and link quality parameters had measured in both phases of ARPVP. Simulation outcomes of the proposed model outperformed state-of-art protocols in terms of average throughput, communication delay, overhead, and Packet Delivery Ratio (PDR).
The position-based routing of Vehicular Ad hoc Network (VANET) vulnerable to various security attacks because of dependency on computing, control, and communication technologies. The Internet of Things (IoT)-enabled VANET application leads to the challenges such as integrity, access control, availability, privacy protection, non-repudiation, and confidentiality. Several security solutions have been introduced for two decades in two categories as cryptography-based and trust-based. Due to the high computation complexity, cryptography-based solutions are outperformed by recent intelligent trust-based mechanisms. The trust-based techniques are lightweight and effective against the well-known security threats in VANET. The objective of this paper has to design a novel position-based routing in which the conduct of vehicles assessed to accomplish reliable VANET communications. Attack Resilient Position-based VANET Protocol (ARPVP) proposed to detect and prevent malicious vehicles in the network using the trust evaluation technique and artificial intelligence (AI). In the first phase of ARPVP, the periodic self-trust assessment algorithm has designed using various trust parameters to detect unreliable vehicles in the network. In the second phase of ARPVP, the position-based route formation algorithm has designed using the AI technique Ant Colony Optimization (ACO). ACO solves the problem of reliable route formation by neglecting the attacker's using a trust-based fitness function. The trust parameters of each vehicle as mobility, buffer occupancy, and link quality parameters had measured in both phases of ARPVP. Simulation outcomes of the proposed model outperformed state-of-art protocols in terms of average throughput, communication delay, overhead, and Packet Delivery Ratio (PDR).
Cloud storage is one of the service of cloud comput- ing. Cloud storage services are commercially popular because to their advantages. It allows data owners to move data from their local computing systems to the cloud. It offers high quality and on-demand data storage services to users. A cloud is essentially a large-scale distributed system; each piece of data is replicated on multiple geographically distributed servers to achieve high availability and high performance. A cloud service provider (CSP) keeps multiple replicas for user’s data on geographically distributed servers. A main problem of using the replication technique in clouds is that it is very expensive to achieve strong consistency on a worldwide scale. In this paper, we are reviewing consistency as a service (CaaS) model, a two-level auditing architecture and a heuristic auditing strategy (HAS) that reveals as many violations as possible.
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