Trust evaluation is an effective method to detect malicious nodes and ensure security in wireless sensor networks (WSNs). In this paper, an efficient dynamic trust evaluation model (DTEM) for WSNs is proposed, which implements accurate, efficient, and dynamic trust evaluation by dynamically adjusting the weights of direct trust and indirect trust and the parameters of the update mechanism. To achieve accurate trust evaluation, the direct trust is calculated considering multitrust including communication trust, data trust, and energy trust with the punishment factor and regulating function. The indirect trust is evaluated conditionally by the trusted recommendations from a third party. Moreover, the integrated trust is measured by assigning dynamic weights for direct trust and indirect trust and combining them. Finally, we propose an update mechanism by a sliding window based on induced ordered weighted averaging operator to enhance flexibility. We can dynamically adapt the parameters and the interactive history windows number according to the actual needs of the network to realize dynamic update of direct trust value. Simulation results indicate that the proposed dynamic trust model is an efficient dynamic and attack-resistant trust evaluation model. Compared with existing approaches, the proposed dynamic trust model performs better in defending multiple malicious attacks.

The fault-tolerance control in scale-free wireless sensor networks against cascading failure is analysed in this paper. Based on the node load redistribution and constant capacity of the scale-free wireless sensor networks, a new load distribution model is proposed under a single random node failure. By the probability generating function method, the relationships between the load and the largest connected component after cascading failures is given. The influence of the single random node failure load distribution parameters and topological parameters on the size of the cascading failure is analysed, and then the critical load value of the cascading failure in the power law load distribution is obtained. The scale of cascading failure is proportional to the degree distribution coefficient and power exponent, and it can be controlled by the critical load value. Once the network load parameter is beyond the critical load value, a random node failure will cause the whole network cascading failure. In this paper, the load redistribution rule is proposed, which can enhance the cascading failure critical load value fault-tolerance accuracy. Meanwhile, the degree distribution and the exponential correlation parameters can effectively compensate for the influence of the cascading failure and enhance the fault-tolerant ability in scale-free wireless sensor networks.

Wireless sensor networks have been studied extensively for their broad range of applications, especially in an environment with no infrastructure. And the nodes failures, link errors, and malicious node attacks are likely to occur quite frequently in wireless sensor networks. It affects the stability and reliability of data transmission. In this paper, we present a security fault-tolerant routing for multi-layer non-uniform clustered wireless sensor networks to improve the security reliability of network operation and data transmission. First, we establish the multi-layer non-uniform clustered network topology, which can effectively avoid the intercluster load imbalance; clustering can effectively reduce the network energy consumption and improve the network reliability. In the cluster head selection process, the trust model and the fuzzy logic are utilized to evaluate the qualification of sensors to become a cluster head. The routing algorithm uses the priority level and the trust value to select the security cluster head as the next hop and builds a route path between the different layers through the cluster head. Secondly, according to the multi-layer of the network topology structure, we present a fault-tolerant algorithm based on rollback strategy. Theoretical analysis and simulations show that the algorithm has the high packet receiving rate by BS and balanced energy consumption. It has good performance in fault tolerance and stability of data transmission, it avoids the hot issue in energy consumption and achieves the network load balance, and it prolongs the entire network life time.

As cloud computing has been popularized massively and rapidly, individuals and enterprises prefer outsourcing their databases to the cloud service provider (CSP) to save the expenditure for managing and maintaining the data. The outsourced databases are hosted, and query services are offered to clients by the CSP, whereas the CSP is not fully trusted. Consequently, the security shall be violated by multiple factors. Data privacy and query integrity are perceived as two major factors obstructing enterprises from outsourcing their databases. A novel scheme is proposed in this paper to effectuatek‐nearest neighbors(kNN)query andkNNquery authentication on an encrypted outsourced spatial database. An asymmetric scalar‐product‐preserving encryption scheme is elucidated, in which data points and query points are encrypted with diverse encryption keys, and the CSP can determine the distance relation between encrypted data points and query points. Furthermore, the similarity search tree is extended to build a novel verifiable SS‐tree that supports efficientkNNquery andkNNquery verification. It is indicated from the security analysis and experiment results that our scheme not only maintains the confidentiality of outsourced confidential data and query points but also has a lowerkNNquery processing and verification overhead than the MR‐tree.

The number of services on the internet has experienced explosive growth, and the rapid and accurate discovery of required services among a vast array of similarly functioning services with differing degrees of quality has become a critical and challenging aspect of service computing. In this paper, we propose a trusted service discovery algorithm based on an ant colony system (TSDA-ACS). The algorithm integrates a credibility-based trust model with the ant colony search algorithm to facilitate the discovery of trusted web services. During the evaluation process, the trust model employs a pseudo-stochastic proportion to select nodes, where nodes with higher reputation have a greater probability of being chosen. The ant colony uses a voting method to calculate the credibility of service nodes, factoring in both credibility and non-credibility from the query node’s perspective. The algorithm employs an information acquisition strategy, a trust information merging strategy, a routing strategy, and a random wave strategy to guide ant search. To evaluate the effectiveness of the TSDA-ACS, this paper introduces the random walk search algorithm (RW), the classic max–min ant colony algorithm (MMAS), and a trustworthy service discovery based on a modified ant colony algorithm (TSDMACS) for comparison with the TSDA-ACS algorithm. The experiments demonstrate that this method can achieve the discovery of trusted web services with high recall and precision rates. Finally, the efficacy of the proposed algorithm is validated through comparison experiments across various network environments.