A New Method of Identifying Core Designers and Teams Based on the Importance and Similarity of Networks

In the process of product collaborative design, the association between designers can be described by a complex network. Exploring the importance of the nodes and the rules of information dissemination in such networks is of great significance for distinguishing its core designers and potential designer teams, as well as for accurate recommendations of collaborative design tasks. Based on the neighborhood similarity model, combined with the idea of network information propagation, and with the help of the ReLU function, this paper proposes a new method for judging the importance of nodes—LLSR. This method not only reflects the local connection characteristics of nodes but also considers the trust degree of network propagation, and the neighbor nodes’ information is used to modify the node value. Next, in order to explore potential teams, an LA-LPA algorithm based on node importance and node similarity was proposed. Before the iterative update, all nodes were randomly sorted to get an update sequence which was replaced by the node importance sequence. When there are multiple largest neighbor labels in the propagation process, the label with the highest similarity is selected for update. The experimental results in the related networks show that the LLSR algorithm can better identify the core nodes in the network, and the LA-LPA algorithm has greatly improved the stability of the original LPA algorithm and has stably mined potential teams in the network.

MANET of an Effective Defence Scheme for Suggestion Based Trust Model

The immovable nature of passing on packages through multi -bounce middle hubs is a critical problem in the versatile impromptu organizations (MANETs). The disseminated versatile hubs set up associations with structure the MANET, which may incorporate childish and getting into mischief hubs. Suggestion based trust the board is proposed in the creating as a system to evaluate through the acting up hubs while looking for a bundle conveyance course. Nonetheless, building a trust model that embraces suggestions by different hubs in the organization is a difficult issue because of the danger of deceptive proposals like reviling, voting form stuffing, and conspiracy. we examines the issues identified with assaults presented by getting rowdy hubs while proliferating suggestions in the current trust models. We propose a suggestion based trust model with a safeguard plot, which uses grouping method to progressively sift through assaults identified with exploitative proposals between certain time dependent on number of collaborations, similarity of data and closeness between the hubs. We evaluate the trust degree as two cases like direct and indirect trust values between neighboring nodes from source. To form a clustering routing network from similar trust values from S to D.The model is experimentally tried under a few portable and detached geographies in which hubs experience changes in their local prompting regular course changes. The observational investigation shows heartiness and exactness of the trust model in a dynamic MANET climate.

A genre trust model for defending shilling attacks in recommender systems

Shilling attacks have been a significant vulnerability of collaborative filtering (CF) recommender systems, and trust in CF recommender algorithms has been proven to be helpful for improving the accuracy of system recommendations. As a few studies have been devoted to trust in this area, we explore the benefits of using trust to resist shilling attacks. Rather than simply using user-generated trust values, we propose the genre trust degree, which differ in terms of the genres of items and take both trust value and user credibility into consideration. This paper introduces different types of shilling attack methods in an attempt to study the impact of users’ trust values and behavior features on defending against shilling attacks. Meanwhile, it improves the approach used to calculate user similarities to form a recommendation model based on genre trust degrees. The performance of the genre trust-based recommender system is evaluated on the Ciao dataset. Experimental results demonstrated the superior and comparable genre trust degrees recommended for defending against different types of shilling attacks.

A Relay Selection Algorithm Based on User Trust Degree for D2D Communications

The emergence of 5G has promoted the rapid development of the Internet of Things(IOT), the dramatic increasing of mobile equipment has led to the increasing shortage of spectrum resources, D2D(Device-to-Device) communication technology is widely concerned for its ability to improve the utilization of spectrum resources. In order to expand the communication scope, relay nodes are introduced into D2D communications, as the third party of D2D relay communication, the quality of relay nodes directly affects the quality of communication process. In order to make more users willing to participate in relay communication, social relationship is introduced into D2D relay communication, However, as an explicit relationship between people, the function of social relationship in D2D communication is limited by the mobility of users and the variability of communication scenarios. In order to find a more reli­able relay node and upgrade the connection success rate of D2D relay communication, implicit social relationship between the users need to be mined. Aiming at that, user trust degree (UTD) is established in this paper. By combining the explicit relationship which is called the social connectivity degree with the implicit social relationship called the interest similarity degree, and considering the user’s movement, a relay selection algorithm is presented to help sender find a relay node with a deeper user trust, which can increase the user’s willingness to participate in D2D relay communication and upgrade the success rate of communication connection, so this algorithm can ensure the security of the relay node and can improve the throughput performance. Simulation results show that this algorithm can increase the success rate of connection, improve the overall throughput of the system and improve the user's communication expe­rience.

Trustworthy Jammer Selection with Truth-Telling for Wireless Cooperative Systems

In this paper, we propose a trustworthy friendly jammer selection scheme with truth-telling for wireless cooperative systems. We first utilize the reverse auction scheme to enforce truth-telling as the dominant strategy for each candidate friendly jammer. Specifically, we consider two auction cases: (1) constant power (CP) case and (2) the utility of the BS maximization (UBM) case. In both cases, the reverse auction scheme enforces truth-telling as the dominant strategy. Next, we introduce the trust category and trust degree to evaluate the trustworthiness of each Helper transmitter (Helper-Tx). Specifically, an edge controller calculates the reputation value of each Helper-Tx periodically using an additive-increase multiplicative-decrease algorithm by observing its jamming behavior. With the historical reputation values, the edge controller (EC) classifies a Helper-Tx into one of four trust categories and calculates its trust degree. Then, the EC selects the best Helper-Tx based on the trust category and trust degree. Lastly, we present numerical results to demonstrate the performance of our proposed jammer selection scheme.

Research on Trust Mechanism based on Delegation Relationship in Sharing Economy

Trust plays a very important role in the development of sharing economy. What’s more, delegation is taken one of evaluation factors as service trust computation. However, the sharing economy based on the delegation also brings security risk. Therefore, this paper proposes a novel trust mechanism based on delegation relationship. Firstly, the paper analyzes a variety of deception which exists in the delegation relationship, then puts forward the concept of the transaction evidence and commission evidence. Secondly, by combining these two kinds of evidence, a novel method is presented. It improves computing trust value algorithm in the commission relationship by applying the evidence theory from three aspects characteristics, relevance evaluation information of evidence and user trust degree. At last, the trust mechanism is established on account of the commission relationship. The effectiveness of this trust mechanism is testified through simulation & emulation experiments.

AgriTrust—A Trust Management Approach for Smart Agriculture in Cloud-based Internet of Agriculture Things

Internet of Things (IoT) provides a diverse platform to automate things where smart agriculture is one of the most promising concepts in the field of Internet of Agriculture Things (IoAT). Due to the requirements of more processing power for computations and predictions, the concept of Cloud-based smart agriculture is proposed for autonomic systems. This is where digital innovation and technology helps to improve the quality of life in the area of urbanization expansion. For the integration of cloud in smart agriculture, the system is shown to have security and privacy challenges, and most significantly, the identification of malicious and compromised nodes along with a secure transmission of information between sensors, cloud, and base station (BS). The identification of malicious and compromised node among soil sensors communicating with the BS is a notable challenge in the BS to cloud communications. The trust management mechanism is proposed as one of the solutions providing a lightweight approach to identify these nodes. In this article, we have proposed a novel trust management mechanism to identify malicious and compromised nodes by utilizing trust parameters. The trust mechanism is an event-driven process that computes trust based on the pre-defined time interval and utilizes the previous trust degree to develop an absolute trust degree. The system also maintains the trust degree of a BS and cloud service providers using distinct approaches. We have also performed extensive simulations to evaluate the performance of the proposed mechanism against several potential attacks. In addition, this research helps to create friendlier environments and efficient agricultural productions for the migration of people to the cities.