Trust Assessment Research Articles

Does Journalism Still Matter? The Role of Journalistic and non-Journalistic Sources in Young Peoples’ News Related Practices

In today's hybrid media environment new content creators challenge the status of professionally produced journalism and blur the lines between professional and non-professional content. Growing up in this information landscape, younger generations have developed news-related practices and attitudes that lie in stark contrast to those of previous generations. In addition, discrepancies exist between news definitions and the use practices of young people. We conducted focus groups with German adolescents (15–17 years), young adults (18–24 years) and adults (40–53 years) in August 2020 to uncover young peoples’ orientation toward news and journalism. Our study indicates that the boundaries of what journalism is and what it is not are becoming increasingly indistinct. However, distinctions do emerge between the journalistic and non-journalistic sources that adolescents and young adults use and the functions they associate with them according to their information needs. Differences between the age groups become apparent in their motivations to stay informed which highlights the important role non-journalistic sources play in information behaviour and opinion formation. For teenage participants especially, Social Media Influencers (SMIs) are relevant within these processes, which are linked to a perceived social duty-to-keep-informed. Moreover, findings from the focus groups highlight cohort-specific differences regarding the understanding of journalism and, consequently, differences in the assessment of trust and reliability as well as the verification strategies that are applied. In sum, for young participants journalism is a reliable source of information, especially in the case of current events and for crosschecking online information, while non-journalistic sources fulfil social needs.

GATrust: A Multi-Aspect Graph Attention Network Model for Trust Assessment in OSNs

Social trust assessment that characterizes a pairwise trustworthiness relationship can spur diversified applications. Extensive efforts have been put in exploration, but mainly focusing on applying graph convolutional network to establish a social trust evaluation model, overlooking user feature factors related to context-aware information on social trust prediction. In this article, we aim to design a new trust assessment framework GATrust which integrates multi-aspect properties of users, including user context-specific information, network topological structure information, and locally-generated social trust relationships. GATrust can assigns different attention coefficients to multi-aspect properties of users in online social networks, for improving the prediction accuracy of social trust evaluation. The framework can then learn multiple latent factors of each trustor-trustee pair to establish a social trust evaluation model, by fusing graph attention network and graph convolution network. We conduct extensive experiments on two popular real-world datasets and the results exhibit that our proposed framework can improve the precision of social trust prediction, outperforming the state-of-the-art in the literature by 4.3% and 5.5% on both two datasets, respectively.

Trust assessment-based stable and attack resistant grouping strategy for data dissemination in IoV

The coalescence of vehicular ad hoc network (VANET) with the internet of things (IoT) results in the concept of the internet of vehicles (IoV). IoV structures a strong backbone for intelligent transport system (ITS), however due to highly dynamic vehicular networks, the trustworthiness of disseminated messages is significant since a fake message might cause fatal mishaps on the road. To address these issues, in this article trust assisted grouping approach has been proposed to limit the malicious communication among vehicles in both dense and sparse traffic scenarios and enhance security. The key highlights consolidated in our proposed approach incorporate trust-based GH selection based on direct and indirect trust assessment parameters. Trust assessment is performed by roadside unit (RSU) to maintain the degree of trust among vehicles of the group by evaluating direct trust assessment-based parameters like realisation, reputation, experience and indirect trust assessment-based parameters like suggestion factor. Vehicle attaining supreme trust value is elected as group head, which enhances trust among group members. The performance and accuracy of our approach is rigorously evaluated under various trust assessment parameters in both sparse and dense scenarios.

Assessment of Social Trust in Relatives of Discharged Patients With Personal Consent and Other Relatives of Patients.

Lack of social trust in the physician–patient relationship will disrupt health. Since social trust has not been sufficiently studied in patients' companions, this study investigates and compares social trust and its dimensions in companions of patients discharged against medical advice with total patients’ companions in the emergency room. In this cross-sectional descriptive-comparative study, 385 patients’ companions were enrolled. This study was done by a questionnaire with five subscales: honesty, frankness, cooperative tendency, confidence, and trust. Data were analyzed using descriptive statistics and analytical statistics methods. In this study, there was no significant difference between the mean score of social trust between companions of patients discharged against medical advice (61.11 ± 9.01) and patients discharged after treatment (62.27 ± 6.97). There was a significant relationship between the mean score of the 2 groups only in the frankness domain (P-value = .001). The level of social trust in the patients’ companions was moderate in both groups. Companions of discharged patients after completing the treatment process are more explicit than the companions of patients discharged against medical advice.

The Epistemic Trust Assessment—An experimental measure of epistemic trust.

The Epistemic Trust Assessment—An experimental measure of epistemic trust.

Supplemental Material for The Epistemic Trust Assessment—An Experimental Measure of Epistemic Trust

Supplemental Material for The Epistemic Trust Assessment—An Experimental Measure of Epistemic Trust

ConTrust: A Novel Context-Dependent Trust Management Model in Social Internet of Things

The global population is around 7.4 billion people. This population density requires connectivity to improve the standard of living by transmitting and receiving variety of services. As a result, numerous forms of communication among objects are required for our everyday living demands, independent of their nature. Furthermore, to create a good relationship, every object that is regarded as associate of another object should have distinct criteria such as scalability, interoperability, and trustworthiness. Many security threats, however, have an impact on the social interaction between objects in a social internet of things (SIoT) context, including illegal admittance and suspicious behavior owing to a lack of verification architecture. Others include attempting to provide a proper viewpoint of a malicious object to earn the trust of other objects. As a result, there is a requirement for an acceptable method to check the behavior of objects such as capability, commitment, reliability, and previous job satisfaction before proceeding with any type of job assignment. This will aid in distinguishing between malicious and trustworthy objects by anticipating their upcoming behavior, allowing better judgments regarding service assignment to be made. This study proposes a context-dependent trust management technique (ConTrust) for choosing and allocating jobs in a SIoT environment. The feature-property match approach, as well as the combination of capability, commitment, and satisfaction, were utilized to increase the efficiency of trust assessment and the resolution of context-dependent difficulties. The proposed trust model considers job characteristics, object capabilities and honesty, and the impact of malicious conduct. The experimental results show that the proposed ConTrust model is viable and capable of ensuring the reliability and efficacy of SIoT service sharing between objects as compared to the benchmark models considered in this work.

An Uncertainty Trust Assessment Scheme for Trustworthy Partner Selection in Online Games

An Uncertainty Trust Assessment Scheme for Trustworthy Partner Selection in Online Games

How can you trust Artificial Intelligence Systems? Objective, Subjective and Intersubjective parameters of Trust

The article studies the most urgent problem of artificial intelligence (AI) - the development of a methodology for assessing trust in AI systems. A universal range of assessment is proposed: objective, subjective and intersubjective parameters. When studying the objective parameters of trust assessment, a formal definition of AI is introduced to increase the validity of trust judgments. When studying subjective parameters as the basis of expert evaluation indicators, their internal logical inconsistency is revealed along with demonstrating the significance of these parameters for analyzing the success and safety of methods for computer simulation of cognitive functions. When studying the intersubjective parameters of trust, a unified format of trust data is proposed, an interdisciplinary organization of monitoring trust in AI systems is considered, and the main blocks of an expert system project are formed.

Trust Assessment Model Based on a Zero Trust Strategy in a Community Cloud Environment

The adoption of Cloud Computing services in everyday business life has grown rapidly in recent years due to the many benefits of this paradigm. The various collaboration tools offered by Cloud Computing have eliminated or reduced the notion of distance between entities of the same company or between different organizations. This has led to an increase in the need to share resources (data and services). Community Cloud environments have thus emerged to facilitate interactions between organizations with identical needs and with specific and high security requirements. However, establishing trust and secure resource sharing relationships is a major challenge in this type of complex and heterogeneous environment. This paper proposes a trust assessment model (SeComTrust) based on the Zero Trust cybersecurity strategy. First, the paper introduces a community cloud architecture subdivided into different security domains. Second, it presents a process for selecting a trusted organization for an exchange based on direct or recommended trust value and reputation. Finally, a system for promoting or relegating organizations in the different security domains is applied. Experimental results show that our model guarantees the scalability of a community cloud with a high success rate of secure and quality resource sharing.

Trust Assessment based Stable and Attack Resistant Grouping Strategy for Data Dissemination in IoV

Trust Assessment based Stable and Attack Resistant Grouping Strategy for Data Dissemination in IoV

CBiLSTM: A Hybrid Deep Learning Model for Efficient Reputation Assessment of Cloud Services

The cloud market is characterized by fierce rivalry among cloud service providers. The availability of various services with identical functionalities on the market complicates the selection decision for service requesters. Although objective trust measurements can be used to evaluate the trustworthiness of services, they are not always available and are static in nature. Subjective approaches are not always viable because they often require repeated service invocations to collect client feedback. To overcome these limitations, we propose, in this paper, a reputation-based trust assessment approach that combines the Net Brand Reputation (NBR) measure with a deep learning-based sentiment analysis model using online user reviews. CBiLSTM is the name of the proposed deep learning model that hybridizes the Convolutional Neural Networks (CNN) and the Bidirectional Long Short-Term Memory (BiLSTM) layers. The CNN layers deal with text inputs’ high dimensionality, while the BiLSTM layer explores the context of the extracted features in both forward and backward directions. CBiLSTM was trained on a new dataset named CLOSER-DREAM, containing more than 13,000 reviews relating to several emerging cloud services to classify these reviews and assess the overall reputation of the cloud services providers. The results of the series of experiments that were conducted have shown that CBiLSTM outperforms the classic deep learning models with 98% of precision, 99% of recall, 98% as an F1-score, and 99.7% of accuracy. Also, CBiLSTM offered a reasonable training time of about 519ms with the CLOSER-DREAM dataset. The classification obtained by applying CBiLSTM was proven to be an effective method to calculate the NBR measure used for the reputation assessment of cloud service providers. The proposed technique yielded an NBR score of 98.3% for Google cloud services, which is close to the real/actual NBR of 96.25%.

Decision model with quantification of buyer-supplier trust in advanced technology enterprises

PurposeIn the buyer-supplier relationship of a high-technology enterprise, the concepts of trust and risk are closely intertwined. Entering into a buyer-supplier relationship inherently involves a degree of risk, since there is always an opportunity for one of the parties to act opportunistically. Purchasing and supply managers play an important role in reducing the firm's risk profile, and must make decisions about whether or not to enter into, or remain in, a relationship with a supplier based on a subjective assessment of trust and risk.Design/methodology/approachIn this paper, the authors seek to explore how trust in the buyer-supplier relationship can be quantitatively modeled in the presence of risk. The authors develop a model of trust between a buyer and supplier as a risk-based decision, in which a buyer decides to place trust in a supplier, who may either act cooperatively or opportunistically. The authors use a case study of intellectual property (IP) piracy in the electronics industry to illustrate the conceptual discussion and model development.FindingsThe authors produce a generalizable model that can be used to aid in decision-making and risk analysis for potential supply-chain partnerships, and is both a theoretical and practical innovation. However, the model can benefit a variety of high-technology enterprises.Originality/valueWhile the topic of trust is widely discussed, few studies have attempted to derive a quantitative model to support trust-based decision making. This paper advanced the field of supply chain management by developing a model which relates risk and trust in the buyer-supplier relationship.

Assessing Health Data Security Risks in Global Health Partnerships: Development of a Conceptual Framework.

BackgroundHealth care databases contain a wealth of information that can be used to develop programs and mature health care systems. There is concern that the sensitive nature of health data (eg, ethnicity, reproductive health, sexually transmitted infections, and lifestyle information) can have significant impact on individuals if misused, particularly among vulnerable and marginalized populations. As academic institutions, nongovernmental organizations, and international agencies begin to collaborate with low- and middle-income countries to develop and deploy health information technology (HIT), it is important to understand the technical and practical security implications of these initiatives.ObjectiveOur aim is to develop a conceptual framework for risk stratification of global health data partnerships and HIT projects. In addition to identifying key conceptual domains, we map each domain to a variety of publicly available indices that could be used to inform a quantitative model.MethodsWe conducted an overview of the literature to identify relevant publications, position statements, white papers, and reports. The research team reviewed all sources and used the framework method and conceptual framework analysis to name and categorize key concepts, integrate them into domains, and synthesize them into an overarching conceptual framework. Once key domains were identified, public international data sources were searched for relevant structured indices to generate quantitative counterparts.ResultsWe identified 5 key domains to inform our conceptual framework: State of HIT, Economics of Health Care, Demographics and Equity, Societal Freedom and Safety, and Partnership and Trust. Each of these domains was mapped to a number of structured indices.ConclusionsThere is a complex relationship among the legal, economic, and social domains of health care, which affects the state of HIT in low- and middle-income countries and associated data security risks. The strength of partnership and trust among collaborating organizations is an important moderating factor. Additional work is needed to formalize the assessment of partnership and trust and to develop a quantitative model of the conceptual framework that can help support organizational decision-making.

Trust-based routing optimization using multi-ant colonies in wireless sensor network

Nowadays, with the advancement of new technologies such as the Internet of Things, new applications and intelligent networks, the use of wireless sensor network increased considerably. They are prone to a variety of attacks. Thus, network security is of utmost importance to researchers. In the past, methods such as cryptography, authentication and hash function were used to create security in this type of network. However, due to the limitations of this type of network, trust-based methods are used today. Finding a secure route for transferring data among available routes greatly increases security in this network. In this paper, we present aTrust-based Routing Optimization using Multi-Ant Colonies (MACRAT) scheme which is based on the improvement of the ant meta-heuristic algorithm and an improved method for trust assessment which is presented. The simulation results illustrate that MACRAT is more efficient than existing routing protocols. The results show that MACRAT improved by 10% in black hole detection compared to ESRT protocol and by 4% compared to M-CSO protocol, the packet loss rate in MACRAT improved by 30.14% compared to ESRT protocol and 6% compared to M-CSO protocol.

1288 Colorectal Cancer Surgery Service Provision During The COVID-19 Pandemic: An Assessment of a Single Trust

Abstract Aim Post-operative pulmonary complications in perioperative SARS-CoV-2 infection are associated with significant morbidity and mortality. To maintain a safe cancer service, the Countess of Chester Hospital adopted “Cold-site” operating and maintained ERAS principles for patients undergoing elective colorectal cancer surgery during the pandemic. A comparative assessment of service was undertaken for benchmarking purposes. Method A comparative retrospective audit was undertaken of consecutive patients undergoing elective colorectal cancer surgery from June to November 2019 and compared to June to November 2020. The Somerset Cancer Registry and electronic medical case records were used to obtain the dataset. Outcomes measured were approach to surgery; stoma rate; length of stay; level of care required; post-operative complications (>Clavien-Dindo 2) and survival at 30 days. Mann-Whitney U test and Chi-squared were used for analysis. Results There were 33 and 24 elective colorectal cancer operations in 2019 and 2020 respectively. There was no difference in the median age (64:69; p = 0.3) or ASA grade (p = 0.9). The median length of stay was 5 and 4 days respectively (p = 0.3). There was a 32.2% reduction in laparoscopic approach to surgery in 2020 (69.7% vs 37.5%; p = 0.02). There was no difference in the stoma rate (p = 0.9), post-operative complication rate (p = 0.7), ITU admission rate (p = 0.3), length of ITU stay (p = 0.6) and 30-day mortality rates (p = 0.4). Conclusions “Cold-site” operating allows robust ERAS care to be adopted to ensure comparative outcomes for patients undergoing colorectal cancer surgery and was associated with a non-significant trend to shorter hospital stay during the COVID-19 pandemic.

Trustee: A Trust Management System for Fog-Enabled Cyber Physical Systems

In this paper, we propose a lightweight trust management system (TMS) for fog-enabled cyber physical systems (Fog-CPS). Trust computation is based on multi-factor and multi-dimensional parameters, and formulated as a statistical regression problem which is solved by employing random forest regression model. Additionally, as the Fog-CPS systems could be deployed in open and unprotected environments, the CPS devices and fog nodes are vulnerable to numerous attacks namely, collusion, self-promotion, bad-mouthing, ballot-stuffing, and opportunistic service. The compromised entities can impact the accuracy of trust computation model by increasing/decreasing the trust of other nodes. These challenges are addressed by designing a generic trust credibility model which can countermeasure the compromise of both CPS devices and fog nodes. The credibility of each newly computed trust value is evaluated and subsequently adjusted by correlating it with a standard deviation threshold. The standard deviation is quantified by computing the trust in two configurations of hostile environments and subsequently comparing it with the trust value in a legitimate/normal environment. Our results demonstrate that credibility model successfully countermeasures the malicious behaviour of all Fog-CPS entities i.e., CPS devices and fog nodes. The multi-factor trust assessment and credibility evaluation enable accurate and precise trust computation and guarantee a dependable Fog-CPS system.

ОБ АКТУАЛЬНЫХ НАПРАВЛЕНИЯХ СОЦИОЛОГИЧЕСКИХ ИССЛЕДОВАНИЙ ВНЕДРЕНИЯ ВСПОМОГАТЕЛЬНЫХ РЕПРОДУКТИВНЫХ ТЕХНОЛОГИЙ В БЕЛАРУСИ

Background. At present there are no scientifically substantiated data on the problems of introducing assisted reproductive technologies (ART) in the Republic of Belarus. The relevance of developing approaches, organizing opinion polls and processing data on a representative sample of Belarusians does not raise doubts in view of the relationship between social attitudes in the field of reproductive health and the national security of the country. Purpose. Substantiation of medical and sociological study of ART in the population of the Republic of Belarus. Material and methods. The bibliographic analysis included the study of Russian and foreign experience in assessing the sociological aspects of reproductology (materials of Springer Link, Oxford University Press, The New England Journal of Medicine, The British Medical Journal, the SCOPUS database of Elsevier, the EBSCO platform), as well as the analysis of the legislation of the Republic of Belarus in the field of reproductology. Results. In the country, the interests of the party that wants to become a parent (surrogate motherhood, donation) are respected as much as possible. The medicalized approach to the definition of ART methods in Belarus is typical, as in other post-Soviet countries, which are characterized by a classical (nuclear) understanding of the family. Taking into account the current trends in the development of the market for reproductive technologies and those techniques that are used in reproductive centers of the Republic of Belarus, it is necessary in the legislative framework to provide for the rules and possibilities of using such methods as hatching (dissection of the embryo membrane), intracytoplasmic sperm injection, intracytoplasmic sperm injection after selection according to morphological criteria, preimplantation diagnostics. Conclusions. The following areas are relevant for Belarus: 1) study of the awareness of the population of the Republic of Belarus about ART; 2) assessment of social trust in ART on the part of the population; 3) development of technologies for positive reproductive attitudes in society, including the use of ART.

Corporate social responsibility and brand loyalty in private higher education: mediation assessment of brand reputation and trust

ABSTRACT This study investigates the effects of corporate social responsibility (CSR) on brand reputation, brand trust, and brand loyalty in the context of higher education. The direct effect of CSR on brand loyalty, and indirect effects through brand reputation and brand trust have been investigated. Data for this study were collected from 300 students attending a private university in Malaysia. Partial least squares structural equation modeling was applied to assess the measurement model and test the proposed hypotheses. Study findings support all hypotheses. The results confirm the positive direct effect of CSR on brand reputation and brand loyalty, as well as the indirect effects of CSR on brand loyalty through brand reputation and brand trust. This study makes a unique theoretical contribution to the literature through assessing and comparing the mediating role of brand reputation and brand trust between CSR and brand loyalty using the Hierarchy of Effects Model.

VACCINE HESITANCY AND MEDICAL MISTRUST IN WOMEN CONSIDERING OR UNDERGOING FERTILITY TREATMENTS

To evaluate perceptions of COVID-19 vaccination in women considering or undergoing fertility treatment. IRB approval was obtained. Cross-sectional anonymous surveys of patients were collected from a single academic fertility center. Participants were randomized 1:1 to receive a one-page graphic of supplemental education providing basic facts and benefits regarding COVID-19 vaccination based on the ASRM COVID-19 taskforce recommendations. Beliefs related to COVID-19 vaccination was assessed with dichotomous, Likert scale and multiple-choice questions. Assessment of trust in the medical system was conducted via the Medical Mistrust Index (MMI). Descriptive data and chi-square analysis were used to compare responses between the intervention v. no intervention groups. To date, 1130/3595 surveys have been received, response rate = 31.4%. Except for age (35.87, SD=4.0 vs 35.68, SD=4.187 p<.05), both the intervention and non-intervention groups were similar in term of demographics, including education and race; participants were predominantly white (77.8%), married (89.2%), and nulliparous (68.6%). 30.3% reported that a loved one or themselves (7.5%) tested positive for COVID-19, 46.7% knew someone who had been hospitalized or who died of COVID-19, and 6.8% stated they would not get the vaccine. Most participants (54.8%) strongly disagreed or disagreed that the vaccine could affect future fertility. Among the participants who reported their vaccination status (N=790), 25.3% of the study population received one dose, 61.4% completed vaccination while 11% did not plan on getting vaccinated. Compared to those who intended to receive the vaccine, 97.9% v. 70.4% believed that the COVID-19 vaccine given during pregnancy does not cause genetic abnormalities in a fetus or infertility (98.8% v. 81.5%), that a more severe infection has been associated with pregnancy (81.3% v. 74.6%) and strongly disagreed (32.7% v. 1.7%) or disagreed (29.0% v. 1.7%) on having concerns on its impact on future pregnancies (p<.05). Similar patterns were seen with those with higher scores on the MMI and beliefs that the vaccines can cause harm. Participants in the intervention group were more likely to believe that COVID-19 vaccination does not cause genetic abnormalities in a fetus (98.0% v. 94.2%), does not cause infertility (99% v. 96.2%) and that a more severe infection has been associated with pregnancy (81.3% v. 74.6%) (all p <.05). Higher scores on the MMI but not the intervention was associated with vaccine hesitancy (p=.01). The majority of women in this study had received or planned to receive the COVID-19 vaccine. Participants with greater trust in the medical system were more likely to receive the vaccine. The intervention increased patient’s knowledge regarding the vaccine and most patients did not believe that COVID-19 vaccination negatively impacts infertility.