Trust Mechanism Research Articles

A Trust Management Method Against Abnormal Behavior of Industrial Control Networks Under Active Defense Architecture

Trusted computing is a typical active defense technology. Trust management is a core support technology of trusted computing. However, when trust management is applied in the industrial control systems, how to identify malicious behavior effectively, model trust relationships, and make a decision based on behavior trustworthiness, meanwhile how to ensure deployed trust mechanism does not affect the control network’s availability, is a significant issue that has not been solved in the previous literature. This paper proposes a trust management method against abnormal behavior of industrial control networks under active defense architecture. Firstly, we review the difficulties of trust management when applied to industrial control networks and analyze abnormal behaviors of the control operations under unknown threats. Then we extract trust information, model the trust relationship of abnormal behaviors, and establish a trust update and decision-making mechanism under the availability constraints of industrial control networks. Furthermore, we provide a deployment method of the proposed trust management in a distributed control network. Finally, we take five typical abnormal operations on control instruction in an industrial control network as an example and perform a detailed analysis and experimental verification of the proposed method. The results prove that the proposed trust management method has good immunity to abnormal behaviors of the control flow and can be deployed in an industrial control system with availability constraints.

Peer-to-peer trust management in intelligent transportation system: An Aumann’s agreement theorem based approach

Vehicular ad hoc network (VANETs) has gained wide popularity such that it is necessary to incorporate trust among each node in the network. However, trust management among vehicles is a challenging task as malicious nodes are prone to disturb data transmission among different vehicles. The aim of this work is to establish the truth of consensus, to identify the malicious nodes with no further delay, by considering the decision of each vehicle on finding the trust values. The experimental analysis for the proposed approach done using the NS3 with CAIDA data set, the proposed scheme shows superior results compared to the other existing schemes for the detection rate of malicious nodes. It enhances the attack Detection Rate (DR) as 96.5% for the projected dual weighted trust evaluation technique. But, DR for the triumphing technique firecol is 74.9% and AODV is 60%. Thus, it is experimentally proved that dual weighted trust mechanism has high attack detection rate, comparatively. Also, proposed method outperforms very well with respect to the data transmission parameters like packet delivery ratio, energy Consumption and average latency comparatively over the existing mechanisms.

What post-mortem privacy may teach us about privacy

This paper approaches the debate about the protection of digital legacies through a medical confidentiality lens, capitalising on its outlier status in common law jurisdictions as a privacy-type duty that survives the death of the rightsholder. The discussion takes the case law in England and Wales and by the European Court of Human Rights on post-mortem medical confidentiality as a springboard for interrogating how these judgments navigate the traditional objections to post-mortem privacy. Whilst the legal duty of medical confidentiality, drawing on the professional duty of the Hippocratic Oath, acts in the first place as a trust mechanism between doctor and patient based on a reciprocity of interests, its incidental effect of protecting not just the rightsholder but also duty bearers and the industry, signals more complex operational dynamics. The post-mortem continuation of that duty in turn brings these other relationships to the surface. Indeed, the post-mortemness amplifies that confidentialities – and by extension information privacy - can rarely be located in an isolated, singular binary relationship between a duty bearer and a rightsholder but is entangled in the great messy sociality of life that involves multiple overlapping, interdependent relationships of relative trust. These may - upon the death of the primary rightsholder – make an appearance as concurrent or competing claims on her legacies and incidentally also carry her post-mortem privacy.

Application of Internet of Things in Smart Factories under the Background of Industry 4.0 and 5G Communication Technology

The key identification element of the smart factory is the interconnection between devices, which solves the production method and development dilemma of the factory under Industry 3.0 and previous models. The new article published by Xinhua News Agency on January 16, 2022, advocates the idea of industry+ Internet, and its main goal is to realize intelligent production. At present, smart factories have become the main development direction of industrial enterprises in the world. 5G technology has been rapidly deployed with the development of mobile communication, and its performance has also been greatly improved compared to previous communication technologies. After China put forward the smart manufacturing 2025 plan, although a large number of enterprises are still lingering in the process of research, learning, and exploration, the idea of Industry 4.0 has taken root in various intelligent manufacturing enterprises, and the development route of Chinese manufacturing enterprises in the future has been ahead of schedule. Direction. Based on the basic theory of Industry 4.0, 5G wireless communication, Internet of Things, and smart factories, this paper firstly distributed questionnaires to 20 enterprises with smart factories by means of network and interview and reanalyzed the collected questionnaires by regression analysis method and then used the questionnaire scale analysis method to analyze the reliability and validity of the questionnaire and combined with the results of the questionnaire analysis to analyze the problems existing in the current smart factory. Finally, based on the background of Industry 4.0 and 5G communication technology, combined with the Internet of Things technology, the development layout of the smart factory is designed; that is, based on the elliptic curve encryption algorithm, the signature mechanism of mutual trust of all electronic devices in the IoT smart factory is set to improve the smart factory.

Integration of Multi-Class Service Paradigm With Generic Trust Mechanism for Innovation, Customization and Adaptability in MANETs

Trust-based mechanisms are widely used in wireless networks of different kinds for providing security against attack. Trust mechanism provides security from various attacks using both detective and preventive manner. This paper presents a quality service paradigm that can be integrated with any underlying trust mechanism. The paradigm includes different flags corresponding to different services incorporated in various routing packets. The paradigm provides flexible customization and adaptability as per the demand of communicating nodes for effective data transfer. Various quality service classes are designed to formulate route as per the requirement to minimize the routing overhead and balancing of load among nodes. This paradigm power is the trust mechanism with proactive action for detection of malicious nodes in the network. The proposed paradigm is incorporated in an established trust mechanism and compared with standard version of that trust mechanism for packet delivery ratio and routing overhead.

A Hybrid Clustered SFLA-PSO algorithm for optimizing the timely and real-time rumor refutations in Online Social Networks

Currently, the popularity of various social media platforms has made convenient communications and prompt information spreading in Online Social Networks (OSNs). However, it brings a serious threat to social stability and public safety when information is identified as false, misleading or inappropriate. Therefore, it is valuable that the timely and real-time rumor refutations are respectively studied to promptly and continually block the rumor spreading. Existing works on the rumor refutations are lacking in sufficient decomposition on the trust mechanism and ignore the analysis of continual blocking the rumor spreading. Motivated by these issues, this paper proposes a comprehensive Hybrid Clustered Shuffled Frog-Leaping Algorithm-Particle Swarm Optimization (HCSFLA-PSO) algorithm for promptly and continually blocking the rumor spreading in OSNs. Firstly, by making decomposition of social relations and analyzing degree of intimacy, self-reliability and credibility, a new trust mechanism of rumor refutations and a novel expression of trust degree are proposed. Secondly, a comprehensive HCSFLA-PSO algorithm is proposed by taking advantage of the clustered local search capability of the SFLA and the fast-convergence of the PSO algorithm collaborative for the rumor refutations, which includes CNP-HCSFLA-PSO sub-algorithm for the timely rumor refutation and CP-HCSFLA-PSO sub-algorithm for the real-time rumor refutation during the truth evolution according to different social relations with different trust degrees. Thirdly, a new concept of timeliness of information and a novel energy consumption model are proposed to solve the influence problem of continual updated truths. Finally, numerical simulations and ablation experiments are conducted to verify the effectiveness of our proposed algorithm.

DAKEs: Decentralized Authenticated Key Exchange Protocols via Blockchain for Smart City

Authenticated key exchange (AKE) is a classic problem in cryptography, where two participants want to exchange their secret keys without being guessed feasibly. Recently, there has been renewed interest in this problem in the smart city since millions of devices and servers in this environment may involve the problem. New challenges are raised at the same time. One of the greatest challenges is how to facilitate communication between participants. Traditionally, a trusted third party (TTP) is needed to provide a trusted way to exchange keys. However, devices in the smart city environment are usually distributed and trustless. A central trusted mechanism is not suitable for many applications in it. The second challenge is that the requirements in the applications of the smart city are diverse. Finally, a practical AKE protocol should be efficient and easy to integrate. To address these challenges, we provide a fully decentralized AKE protocol framework called DAKEs. To the best of our knowledge, DAKEs enjoy the most comprehensive security properties to fulfil diverse requirements. The decentralization of DAKEs is captured by using the blockchain while avoiding the availability problem of other similar blockchain-based schemes. Our test is conducted in a real-world test network of Ethereum. The result shows that DAKEs are efficient and at a low cost.

Trust and knowledge sharing among hospitals during COVID-19: the compound effect of four barriers to organisational trust for knowledge sharing

PurposeCOVID-19 highlighted the potential value of improving knowledge sharing (KS) processes among hospital estates and facilities management (HEFM) departments. Organisational trust (OT) is a recognised predictor of KS interactions, but the interplay of impersonal and interpersonal OT components is yet to be investigated fully. In response to recent calls, this study aims to explore the effect of organisational features on personal trust and OT components required for KS episodes, in the context of the English National Health Service (NHS).Design/methodology/approachA qualitative, exploratory grounded theory approach was selected, using primary data from 22 semi-structured interviews and secondary data from grey literature. A model of trust for KS among employees from geographically distributed units with pooled interdependence was synthesised from a review of the literature and used to connect the organisational features to different trust mechanisms.FindingsThis study identifies four organisational features with a compound barrier-effect on impersonal-based OT, interpersonal-based OT and personal trust for KS interactions: lack of professional development, inappropriate reward and incentive systems, reorganisations/organisational change and benchmarking.Research limitations/implicationsThis study sought to generate theory about the interplay of organisational barriers and trust components required for KS, not to describe HEFM KS across the entire NHS. Future studies with more comprehensive data collections can build on this exploratory study by quantitatively testing the compound barrier effect of the organisational features.Practical implicationsPractitioners can benefit from the insights into the barriers inhibiting trust mechanisms required for effective KS processes. These can inform policymakers in English and potentially other health-care systems in designing enhanced collaborative arrangements, which are required as future crises, e.g. pandemics and climate change hazards, will require increasingly complex solutions.Originality/valueThis study addresses the interplay between personal trust, impersonal OT and interpersonal OT for KS by identifying the compound barrier effects of underlying organisational barriers common to personal trust and OT.

Research on the influence mechanism of university-enterprise collaboration: Evidence From five southern coastal provinces in China

Taking university-enterprise collaborative innovation in five southern coastal provinces of China as subjects, empirical research is implemented by constructing a theoretical model of the effects of interface resource integration, interface conflict management, interface connection mechanisms, and enterprise absorptive capacity on the university-enterprise collaborative innovation performance with the partial least squares structural equation modeling and fuzzy-set qualitative comparative analysis. A total of 245 valid questionnaires were collected from five coastal provinces in south China. The research results show that the interface resource integration, interface connection mechanisms, and enterprise absorptive capacity has direct significant positive impacts on the collaborative innovation performance. Interface conflict management has no significant impact on school-enterprise collaborative innovation performance. Moreover, the interface connection mechanism acts as an intermediary. Therefore, it is suggested that university-enterprise should integrate resources with complementing, interacting, and sharing resources; construct the profit and risk-sharing mechanism, communication and trust mechanism, and organizational learning mechanism.

Research on the influence mechanism of university-enterprise collaboration: Evidence From five southern coastal provinces in China.

Taking university-enterprise collaborative innovation in five southern coastal provinces of China as subjects, empirical research is implemented by constructing a theoretical model of the effects of interface resource integration, interface conflict management, interface connection mechanisms, and enterprise absorptive capacity on the university-enterprise collaborative innovation performance with the partial least squares structural equation modeling and fuzzy-set qualitative comparative analysis. A total of 245 valid questionnaires were collected from five coastal provinces in south China. The research results show that the interface resource integration, interface connection mechanisms, and enterprise absorptive capacity has direct significant positive impacts on the collaborative innovation performance. Interface conflict management has no significant impact on school-enterprise collaborative innovation performance. Moreover, the interface connection mechanism acts as an intermediary. Therefore, it is suggested that university-enterprise should integrate resources with complementing, interacting, and sharing resources; construct the profit and risk-sharing mechanism, communication and trust mechanism, and organizational learning mechanism.

Fact-Checking Methodology and its Transparency: What Indian Fact-Checking Websites Have to Say?

ABSTRACT Among other preventive measures, fact-checking is considered as one of the effective ways to combat fake news. Fact-checkers promote rationality and assist citizens in making informed decisions. However, fact-checkers’ motives, methods and abilities are doubted and subjected to distrust. Lack of perceived trust is a major concern in the profession of fact-checking journalism. To build public trust, fact-checking organisations have been advised to be transparent about news production processes. Besides the trust mechanism, compliance to transparency is an important tenet of journalistic professionalism. This study seeks to analyse Indian fact-checkers’ explanations of their methodology for fact-checking claims and commitments to ensuring methodological transparency. Qualitative content analysis of declarations published by seven Indian fact-checkers on their websites demonstrates that fact-checking is conducted in a systemic and transparent manner. Transparency norm seems to have emerged as a governing principle in the context of fact-checking journalism. The findings of this study have been interpreted in the view of literature on journalistic transparency.

Necessary but not Sufficient: Assurance Mechanisms for Enhancing Trust in AI-enabled Job Screening

The use of algorithms and artificial intelligence (AI) in recruitment is now commonplace, yet research indicates candidates are wary of their use. This paper takes an institution-based trust perspective to investigate whether assurance mechanisms can enhance trust and acceptance of AI use in job applicant screening. Two experiments provide preliminary evidence for this proposition. In Study 1 (N = 267), we found that assurance in the form of governance by an ethical review board (compared to no information about review), enhanced candidate trust and acceptance of an AI applicant screening tool. Study 1 findings were broadly replicated in Study 2 (N = 653) which further showed that a combination of ethical review and direct human oversight of AI output enhanced trust and acceptance, but direct human oversight alone did not. However, low mean values of trust and acceptance suggest that even with assurance mechanisms in place, candidates were still sceptical. Qualitative findings indicate that human oversight and the use of AI tools to support human decisionmaking is important for people to trust AI use in recruitment and selection. Taken together, findings suggest that assurance mechanisms are necessary but not sufficient to garner trust and acceptance of AI use in recruitment.

Your Authenticity Makes Me Feeling Trusted? It depends on My Power Distance

In this study, we aim to explain why and when authentic leadership promotes positive follower behaviors. Drawing on the social information processing theory and previous research about authentic leadership, we introduce a new mechanism (i.e., feeling trusted by leader) to explain why authentic leadership plays a positive role in follower outcomes. Furthermore, combining social information processing theory and leadership research, we theorize that power distance is especially relevant to research about leadership and identify it as a moderator between authentic leadership and feeling trusted by leader. Using a multi-wave and multi-source data, we tested this moderated mediation model. The results indicated that authentic leadership had an additional positive influence on follower outcomes (i.e., work effort and OCB towards leaders) through feeling trusted by leader (after controlling the mechanism of trust in leader). And power distance weakens the relationship between authentic leadership and feeling trusted by leader.

A Reliable and Efficient Task Offloading Strategy Based on Multifeedback Trust Mechanism for IoT Edge Computing

Facing multidemand tasks and massive heterogeneous resources in an IoT edge computing environment, it is a challenge to obtain reliable and quick response service and allocate application tasks to resource nodes that meet task requirements and user preference. Since IoT edge computing is facing different types of severe attacks, such as message attacks, swing attacks, collusion attack, node attacks, etc., providing a reliable service environment, trust evaluation between edge nodes is necessary. Existing trust computing schemes, however, suffer from a long response period and low malicious detection rate in a dynamic environment. To alleviate these issues, we propose a reliable and efficient task offloading strategy based on the multifeedback trust mechanism (TOSMFTM). First, a reliable and efficient architecture of TOSMFTM is established, which can effectively improve the ability of trust computing and task offloading. Second, according to the broker’s dynamic monitoring of data, a multifeedback trust aggregation model based on time attenuation and interaction frequency is proposed to provide a trusted running environment. Third, a trust weight <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> -means (TWK-means) clustering algorithm is designed based on resource attributes to enhance the reliability of service, and quickly and accurately cluster out resource nodes required by the task. Finally, we construct a task offloading model based on trust clustering to ensure user experience quality and promote system efficiency. Different from existing task processing models, which only focus on task offloading, our method also carries out resource preprocessing, trust evaluation, and resource clustering before task processing. The experiment verifies the effectiveness and feasibility of our TOSMFTM scheme.

Trust management for service migration in Multi-access Edge Computing environments

Multi-access Edge Computing relies on the concept of moving part of the cloud resources closer to the users to address limitations of the traditional cloud in order to reduce communication latency and increase security. This makes Multi-access Edge Computing (MEC) suitable for time-critical applications such as autonomous vehicles where they can support connectivity with a safe and more efficient experience. Nevertheless, MECs are generally deployed on constrained devices with limited resources, which may affect the infrastructure reliability and thus its trustworthiness.In this paper, we focus on a trust mechanism based on the interactions between MECs to increase reliability in the context of a service migration scenario, where MEC nodes can decide based on a trust score to which node to migrate their services and user information. Our proposed algorithm leverages ideas of the EigenTrust and RLIoT reputation system and combined with a novel correlation concept and a dynamic distance algorithm. From our simulations, our model shows better results in different scenarios and communication ranges. This work provides the core component of a complete trust management system for MECs and could be applied in various use cases.

Enhancing the Routing Security through Node Trustworthiness using Secure Trust Based Approach in Mobile Ad Hoc Networks

Mobile Ad Hoc Networks, also known as MANETs are the part of networks which utilizes the technologies like Internet of Things. Internet is filled with known as well as unknown sources which are still considered as a challenge. Considering the security challenges in the topology, infrastructure and bandwidth of these networks the below secure trust approach is proposed. Among all the existing and proposed approaches to provide the security to these networks seemed lengthy and complex. The study here focuses on the trust factor of the nodes to simulate the challenge of providing the secure transmission. The challenge is approached through calculations from the simulations based on node distribution and its trustworthiness. In order to evaluate the performance of the proposed secure trust mechanism, three scenarios are considered here. Routing between source ad destination without any trust calculation, routing with only direct trust factor and routing with proposed secure trust calculation from the node’s distributions. The goal of proposed method in this paper is about the secure routing for transmission by simulating the important factor Node trustworthiness using new trust mechanism proposed i.e. secure trust. The metrics from the simulations shows the efficient performance of the proposed method.

A novel task offloading algorithm based on an integrated trust mechanism in mobile edge computing

As a new computing model, mobile edge computing (MEC) is designed to better deal with various forms of service requests, such as computing intensity and delay sensitivity, in the era of big data and the Internet of Things (IoT). However, the development of MEC is still in its infancy, and many issues need to be further investigated. One of the key issues that needs to be addressed in MEC is rational task offloading. Due to the dynamic, real time and complex nature of the MEC environment, the security and reliability of edge data are becoming increasingly important. Based on the above problems, we construct a task offloading integrated trust evaluation mechanism and, combined with the double deep Q-network (DDQN) algorithm in deep reinforcement learning (DRL), propose a novel task offloading algorithm, named DDTMOA. Simulation results show that the DDTMOA algorithm can effectively reduce the average task response time and total system energy consumption while ensuring task offloading performance compared to other classical algorithms.

Research on the impact of consumer forgiveness on consumer continuous trust

Online shopping has become an important part of people’s life, but the current academic circles still lack attention to online shopping service recovery. Based on the online shopping service recovery scenario, this study takes the scenario experiment as the research method, discusses the influence mechanism of consumer continuous trust from the perspective of compensation and consumer forgiveness, and tests the moderating effect of online store reputation. Through empirical research, this paper obtains the following research findings: Both utilitarian compensation and spiritual compensation have a positive impact on consumer forgiveness, but spiritual compensation has a greater positive impact on consumer forgiveness; consumer forgiveness has a positive impact on consumer continuous trust, and consumer forgiveness plays a mediating effect between utilitarian compensation, spiritual compensation and consumer continuous trust; online store reputation plays a positive moderating effect in the impact of consumer forgiveness on consumer continuous trust. The research results of this paper are conducive to deepen the research on the relationship between compensation methods and consumer forgiveness, better explain the role of consumer forgiveness, consumer continuous trust and online store reputation in the impact mechanism of online shopping service recovery, and promote the healthy development of online shopping business model.

SPCBIG-EC: A Robust Serial Hybrid Model for Smart Contract Vulnerability Detection.

With countless devices connected to the Internet of Things, trust mechanisms are especially important. IoT devices are more deeply embedded in the privacy of people’s lives, and their security issues cannot be ignored. Smart contracts backed by blockchain technology have the potential to solve these problems. Therefore, the security of smart contracts cannot be ignored. We propose a flexible and systematic hybrid model, which we call the Serial-Parallel Convolutional Bidirectional Gated Recurrent Network Model incorporating Ensemble Classifiers (SPCBIG-EC). The model showed excellent performance benefits in smart contract vulnerability detection. In addition, we propose a serial-parallel convolution (SPCNN) suitable for our hybrid model. It can extract features from the input sequence for multivariate combinations while retaining temporal structure and location information. The Ensemble Classifier is used in the classification phase of the model to enhance its robustness. In addition, we focused on six typical smart contract vulnerabilities and constructed two datasets, CESC and UCESC, for multi-task vulnerability detection in our experiments. Numerous experiments showed that SPCBIG-EC is better than most existing methods. It is worth mentioning that SPCBIG-EC can achieve F1-scores of 96.74%, 91.62%, and 95.00% for reentrancy, timestamp dependency, and infinite loop vulnerability detection.

Will goal clarity lower team innovation? A moderated mediation model of inter-team trust

PurposeBased on two dominant perspectives, team climate and knowledge integration, on team innovation, this study aims to propose a moderated mediation model to examine the interactive effect of inter-team trust and goal clarity on team innovation through knowledge inflows into a team. Considering the two perspectives at the same time will provide a more complete picture on our understanding on team innovation.Design/methodology/approachThe research model is tested on 150 retail teams of a large apparel firm. Data are collected from two separate surveys, one to store managers and one to store staff members. Moderation mediation regression analysis is conducted on the survey data.FindingsThe regression analysis identified both a positive direct effect of goal clarity on innovation, and a negative moderating effect of goal clarity on the mediation of knowledge inflows between inter-team trust and innovation. In other words, inter-team trust is positively related to team innovation through knowledge inflows when goal clarity is low.Originality/valueIn this study, the authors identify an indirect and negative role of goal clarity on team innovation, and examine the mechanism and boundary of inter-team trust on team innovation. Managers are advised to foster a trusting environment and be aware of cognitive bias in their teams so that their teams can be more innovative.