Trust Evaluation Model for Internet of Things using Mobile Ad hoc Networks

Internet of Things (IoT) is a theory that embraces various objects and methods of communication to exchange information. Today, IoT is more a descriptive term of a vision that everything should be linked to the internet. As many as the advantages of IoT, its uniqueness poses a new problem in establishing a trustworthy environment amid some of the items due to the lack of appropriate implementation machineries. However, some common network security measures are not adequate to preserve the integrity of information and services exchanged over the internet. As a result, they remain vulnerable to threats ranging from cyber-physical layer and social layer data management risks. IoT in smart environments interrelates with mobile ad hoc network (MANET), becoming even more attractive and economically successful. This research proposes two different metrics approaches namely Social trust metrics and Quality of Service to evaluate the trustworthiness of IoT Applications using MANET nodes and designing trust metrics that are computed using multiple properties of trust and quality of service. A model would be designed and simulated in NS-2. The findings of the investigation into the evaluation of trustworthiness and network performance are presented. The proposed system model has 99.31% accuracy when there were 10%malicious nodes in the network. When the number of misbehaving nodes was increased to 50%, the accuracy level dropped to 98.75 percent, a difference of only 0.56%. The results show that the security and trustworthiness of the proposed system is an improvement over the existing models like Collaborative Reputation (CORE) trust model and Ant Based Evidence Distribution (trust) model. The proposed model can be used to address security challenges in a network environment. Keywords— Confidence, Honesty, IoT, MANET, QoS, Trustworthiness.

The Method of Group Control in Multi-Agent Robotic Systems Under the Influence of Destabilizing Factors

The problem of finding the optimal solution in a self-organizing autonomous group robotic system under conditions of uncertainty is considered. A method for assessing the quality of group management based on a statistical and probabilistic decision-making criterion under uncertainty conditions has been developed. A distinctive feature of the method is the use of trust metrics. This approach allows us to identify and reduce the influence of destabilizing factors in the process of information interaction in an autonomous group of cyber-physical objects. The results can be used in the development of algorithms for group control of swarms of autonomous robotic complexes.

Delivery of Healthcare Resources Using Autonomous Ground Vehicle Convoy Systems: An Overview

Utilizing military convoys in humanitarian missions allows for increased overall performance of healthcare logistical operations. To properly gauge performance of autonomous ground convoy systems in military humanitarian operations, a proper framework for comparative performance metrics needs to be established. Past efforts in this domain have had heavy focus on narrow and specialized areas of convoy performance such as human factors, trust metrics, or string stability analysis. This article reviews available Army doctrine for manned convoy requirements toward healthcare missions and establishes a framework to compare performance of autonomous convoys, using metrics such as spacing error, separation distance, and string stability. After developing a framework of comparison for the convoy systems, this article compares the performance of two autonomous convoys with unique convoy control strategies to demonstrate the application and utility of the framework.

Anticollusion Attack Strategy Combining Trust Metrics and Secret Sharing for Friendships Protection

Online social networks provide users with services such as online interaction, instant messaging, and information sharing. The friend search engine, a new type of social application, provides users with the service for querying the list of other individuals’ friends. Currently, the existing research focuses on independent attacks for friend search engines while ignoring the more complicated collusion attacks, which can expose more friendships that users are not willing to share. Compared with independent attackers, collusion attackers share query results by cooperating with each other. In this article, we propose a resistance strategy against collusion attacks to protect the friendship privacy. The proposed trust metric is based on users’ behaviors and is combined with Shamir’s secret sharing system, which can transform friendships into secrets. Through secret distribution and reconfiguration, only the participants who meet the query requirements can successfully reconstruct the secret, while the participants who do not meet the query conditions cannot successfully obtain the secret fragments even if they obtain the secret fragments. Experiments are conducted to verify the effectiveness of the proposed strategy and proved that this strategy can greatly limit the number of malicious attackers, greatly reduce the probability of successful collusion attacks, and reduce the number of victims.

A Comparative Analysis of Different Trust Metrics in User-User Trust-Based Recommender System

Information overload is the biggest challenges nowadays for any website, especially the e-commerce website. However, this challenge arises for the fast growth of information on the web (WWW) with easy access to the internet. Collaborative filtering based recommender system is the most useful application to solve the information overload problem by filtering relevant information for the users according to their interests. But, the existing system faces some significant limitations like as data sparsity, low accuracy, cold-start and malicious attacks. To alleviate the mentioned issues, the relationship of trust incorporates in the system where it can be between the users or items, and such system is known as the trust-based recommender system (TBRS). From the user perspective, the motive of the TBRS is to utilize the reliability between the users to generate more accurate and trusted recommendations. However, the aim of the paper is to present a comparative analysis of different trust metrics in the context of the type of trust definition of TBRS. Also, the study accomplishes on twenty-four trust metrics in terms of the methodology, trust properties & measurement, validation approaches, and the experimented dataset.

Enhanced Slope One Algorithm using Hierarchical Clustering and Trust Based Collaborative Filtering for Ecommerce Applications

Collaborative filtering algorithm will be one among the assisting techniques delivering customized suggestions in the area of ecommerce. Nevertheless, conservative techniques concentrated in operating with client’s review and will not take into account of alteration of customer’s desires along with reliability of rankings associated. Huge quantity of increase in clients along with items resulted in certain critical complexities. Fresh Suggestion strategies will be required. Slope One algorithm might perform well with the motivation of minimized inadequacy of rankings, enhanced precision of suggestion. On the other hand increase in number of clients, resulted increased consumption duration. Establishment of solutions for complexities to extend adjacency space via utilization of clustering strategies will be carried out. Fundamental motivation of the paper relies with investigating feasible influence of utilizing trust measures in enhancing the quality of suggestions. This paper highlighted the significance of Trust in determining solutions for providing suggestions. Slope one algorithm incorporated with hierarchical agglomerative clustering technique performed superiorly while evaluated with trust metrics and solved the problem of huge amount of information associated with Trust aware information.