A Trusted Routing Protocol Based on GeoDTN＋Nav in VANET

Because the node of vehicular ad-hoc networks has the characteristics of high mobility and encounter temporary, a trust management between the nodes in the routing process becomes more difficult. To solve this problem, this paper proposes a new trusted routing protocol in VANET based on GeoDTN＋Nav by using trust management model of Bayesian and the three opportunistic routing forwarding models, which includes four steps of the routing initialization, the routing discovery, the trusted routing establishment and the routing deletion. The proposed protocol not only improves the security of routing, but also has the lower time complexity. Besides, experimental results and analysis show that the protocol has achieved good performance in the removal ratio of malicious nodes, correct reception ratio of packet and the message payload.

Trust routing algorithm based on multiple decision factor theory in OSPF protocol

This paper presents a novel trust model based on multiple decision factor theory （MDFT） and a trust routing algorithm based on MDFT to exactly evaluate routing node trust and establish a trustworthy routing path. MDFT integrates four dimensional trust decision factors including behavior, state, recommend and node liveness to realize an exactly finer-grained trust evaluation. On the basis of MDFT, a trust routing algorithm is presented and validated in open shortest path first （OSPF） protocol. Simulation resuRs show that the algorithm can reflect the routing node trust accurately and has better dynamic response ability. Under the circumstance of existing deceptive nodes, the algorithm has better anti-deception performance and higher attack node detection rate than conventional algorithm.

Wireless Sensor Networks Routing Attacks Prevention with Blockchain and Deep Neural Network

Routing is a key function inWireless Sensor Networks(WSNs)since it facilitates data transfer to base stations.Routing attacks have the potential to destroy and degrade the functionality ofWSNs.A trustworthy routing system is essential for routing security andWSN efficiency.Numerous methods have been implemented to build trust between routing nodes,including the use of cryptographic methods and centralized routing.Nonetheless,the majority of routing techniques are unworkable in reality due to the difficulty of properly identifying untrusted routing node activities.At the moment,there is no effective way to avoid malicious node attacks.As a consequence of these concerns,this paper proposes a trusted routing technique that combines blockchain infrastructure,deep neural networks,and Markov Decision Processes(MDPs)to improve the security and efficiency of WSN routing.To authenticate the transmission process,the suggested methodology makes use of a Proof of Authority(PoA)mechanism inside the blockchain network.The validation group required for proofing is chosen using a deep learning approach that prioritizes each node’s characteristics.MDPs are then utilized to determine the suitable next-hop as a forwarding node capable of securely transmitting messages.According to testing data,our routing system outperforms current routing algorithms in a 50%malicious node routing scenario.

Trust Evaluation Model Based on Behavior Space Classification for Ad Hoc Networks

Trust management frameworks are used to evaluate and manage trust relationships between network nodes and enhance network security. However, trust management frameworks themselves are vulnerable to attacks. Attacks against trust management frameworks are described in this paper with a trust management framework to resist them. The trustworthiness between nodes is evaluated to classify node behavior using a three-dimensional classifier based on a fuzzy integral. Different behaviors are mapped to different behavioral spaces to detect malicious nodes and identify their behavior types. The security of ad hoc networks is then improved by various measures to handle different types of malicious behavior. Simula- tions of the model on the System In The Loop （SITL） platform show that this trust management framework can separate normal nodes and malicious nodes and can distinguish different types of malicious nodes.

Trusted GPSR protocol without reputation faking in VANET

In vehicular ad hoc network(VANET), misbehaviors of internal nodes, such as discarding packets, may lead to a rapid decline in packet delivery ratio. To solve this problem, an improvement of greedy perimeter stateless routing(GPSR) protocol is presented. In the new protocol, trustworthiness is considered in the route selection process. The trustworthiness is measured by an objective trust model based on the subjective trust model Dy Trust. And the reputation value which reflects the trustworthiness of each node is calculated and broadcasted by the intersection nodes. Specially, besides resisting the packet-discarding behavior of selfish nodes, this protocol also includes a location detection process to resist the location-faking behavior of malicious nodes. As a result, the selfish nodes and the malicious nodes can be excluded from the network. In addition, compared with improved GPSR protocol, the presented one is able to resist one kind of reputation-faking attack and has better performance in simulation.