Machine learning and human‐machine trust in healthcare:A systematic survey

As human‐machine interaction(HMI)in healthcare continues to evolve,the issue of trust in HMI in healthcare has been raised and explored.It is critical for the development and safety of healthcare that humans have proper trust in medical machines.Intelligent machines that have applied machine learning(ML)technologies continue to penetrate deeper into the medical environment,which also places higher demands on intelligent healthcare.In order to make machines play a role in HMI in healthcare more effectively and make human‐machine cooperation more harmonious,the authors need to build good humanmachine trust(HMT)in healthcare.This article provides a systematic overview of the prominent research on ML and HMT in healthcare.In addition,this study explores and analyses ML and three important factors that influence HMT in healthcare,and then proposes a HMT model in healthcare.Finally,general trends are summarised and issues to consider addressing in future research on HMT in healthcare are identified.

A Large-Scale Group Decision Making Model Based on Trust Relationship and Social Network Updating

With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.

Trusted Certified Auditor Using Cryptography for Secure Data Outsourcing and Privacy Preservation in Fog-Enabled VANETs

With the recent technological developments,massive vehicular ad hoc networks(VANETs)have been established,enabling numerous vehicles and their respective Road Side Unit(RSU)components to communicate with oneanother.The best way to enhance traffic flow for vehicles and traffic management departments is to share thedata they receive.There needs to be more protection for the VANET systems.An effective and safe methodof outsourcing is suggested,which reduces computation costs by achieving data security using a homomorphicmapping based on the conjugate operation of matrices.This research proposes a VANET-based data outsourcingsystem to fix the issues.To keep data outsourcing secure,the suggested model takes cryptography models intoaccount.Fog will keep the generated keys for the purpose of vehicle authentication.For controlling and overseeingthe outsourced data while preserving privacy,the suggested approach considers the Trusted Certified Auditor(TCA).Using the secret key,TCA can identify the genuine identity of VANETs when harmful messages aredetected.The proposed model develops a TCA-based unique static vehicle labeling system using cryptography(TCA-USVLC)for secure data outsourcing and privacy preservation in VANETs.The proposed model calculatesthe trust of vehicles in 16 ms for an average of 180 vehicles and achieves 98.6%accuracy for data encryption toprovide security.The proposedmodel achieved 98.5%accuracy in data outsourcing and 98.6%accuracy in privacypreservation in fog-enabled VANETs.Elliptical curve cryptography models can be applied in the future for betterencryption and decryption rates with lightweight cryptography operations.

From Standard Policy-Based Zero Trust to Absolute Zero Trust (AZT): A Quantum Leap to Q-Day Security

Cybercrime is projected to cost a whopping $23.8 Trillion by 2027. This is essentially because there’s no computer network that’s not vulnerable. Fool-proof cybersecurity of personal data in a connected computer is considered practically impossible. The advent of quantum computers (QC) will worsen cybersecurity. QC will be a boon for data-intensive industries by drastically reducing the computing time from years to minutes. But QC will render our current cryptography vulnerable to quantum attacks, breaking nearly all modern cryptographic systems. Before QCs with sufficient qubits arrive, we must be ready with quantum-safe strategies to protect our ICT infrastructures. Post-quantum cryptography (PQC) is being aggressively pursued worldwide as a defence from the potential Q-day threat. NIST (National Institute of Standards and Technology), in a rigorous process, tested 82 PQC schemes, 80 of which failed after the final round in 2022. Recently the remaining two PQCs were also cracked by a Swedish and a French team of cryptographers, placing NIST’s PQC standardization process in serious jeopardy. With all the NIST-evaluated PQCs failing, there’s an urgent need to explore alternate strategies. Although cybersecurity heavily relies on cryptography, recent evidence indicates that it can indeed transcend beyond encryption using Zero Vulnerability Computing (ZVC) technology. ZVC is an encryption-agnostic absolute zero trust (AZT) approach that can potentially render computers quantum resistant by banning all third-party permissions, a root cause of most vulnerabilities. Unachievable in legacy systems, AZT is pursued by an experienced consortium of European partners to build compact, solid-state devices that are robust, resilient, energy-efficient, and with zero attack surface, rendering them resistant to malware and future Q-Day threats.

The Critical Role of Middle Leaders in Schools:Cultivating a Culture of Trust and Supporting Educational Reform

This research delves into the often-underappreciated role of middle leaders in educational organizations,highlighting their significance as the linchpins between senior leadership and classroom teachers.Utilizing qualitative research methods,the study investigates the multifaceted responsibilities,challenges,and contributions of middle leaders in schools.Findings indicate that middle leaders foster a culture of trust within the institution by providing mentorship and guidance to new teachers.They undertake substantial tasks,such as team coordination,grade direction,and student supervision,in addition to their teaching duties.Despite their pivotal role,middle leaders often face mounting pressures and heavy workloads.This research underscores the need to recognize and support middle leaders in educational settings,acknowledging their vital role in fostering cohesion and facilitating the implementation of educational reforms.

Trust beyond Technology Algorithms: A Theoretical Exploration of Consumer Trust and Behavior in Technological Consumption and AI Projects

In an era dominated by artificial intelligence (AI), establishing customer confidence is crucial for the integration and acceptance of AI technologies. This interdisciplinary study examines factors influencing customer trust in AI systems through a mixed-methods approach, blending quantitative analysis with qualitative insights to create a comprehensive conceptual framework. Quantitatively, the study analyzes responses from 1248 participants using structural equation modeling (SEM), exploring interactions between technological factors like perceived usefulness and transparency, psychological factors including perceived risk and domain expertise, and organizational factors such as leadership support and ethical accountability. The results confirm the model, showing significant impacts of these factors on consumer trust and AI adoption attitudes. Qualitatively, the study includes 35 semi-structured interviews and five case studies, providing deeper insight into the dynamics shaping trust. Key themes identified include the necessity of explainability, domain competence, corporate culture, and stakeholder engagement in fostering trust. The qualitative findings complement the quantitative data, highlighting the complex interplay between technology capabilities, human perceptions, and organizational practices in establishing trust in AI. By integrating these findings, the study proposes a novel conceptual model that elucidates how various elements collectively influence consumer trust in AI. This model not only advances theoretical understanding but also offers practical implications for businesses and policymakers. The research contributes to the discourse on trust creation and decision-making in technology, emphasizing the need for interdisciplinary efforts to address societal challenges associated with technological advancements. It lays the groundwork for future research, including longitudinal, cross-cultural, and industry-specific studies, to further explore consumer trust in AI.

Trust and relationship commitment on cooperative performance of supply chain

Creating and sustaining trust in cooperative performances of the supply chain constitute critical strategic components.To study the influences of organizational and individual trust on the quality of commitment and cooperative performance,the relationships among organizational trust,individual trust,commitment and cooperative performances of the supply chain are discussed by case analysis.Questionnaire investigation is used to study the trust and relationship commitment among supply chain partnerships on cooperative performance.Results show that both organizational and individual trust are positively correlated with cooperative performance.The indirect effects of organizational trust on cooperative performance through relationship commitment is significantly greater than its direct effects.However,the indirect effects of individual trust on cooperative performance through relationship commitment is significantly less than its direct effects.It provides all essential basis for enterprises to establish and develop stable supply chain partnerships and to enhance competitive advantages.

Quantum Communication Networks and Trust Management: A Survey

This paper summarizes the state of art in quantum communication networks and trust management in recent years.As in the classical networks,trust management is the premise and foundation of quantum secure communication and cannot simply be attributed to security issues,therefore the basic and importance of trust management in quantum communication networks should be taken more seriously.Compared with other theories and techniques in quantum communication,the trust of quantum communication and trust management model in quantum communication network environment is still in its initial stage.In this paper,the core technologies of establishing secure and reliable quantum communication networks are categorized and summarized,and the trends of each direction in trust management of quantum communication network are discussed in depth.

The Mechanism about Key and Credential on Trusted Computing Platform and the Application Study

Trusted Computing technology is quickly developing in recent years. This technology manages to improve the computer security and archive a trusted computing environment. The core of trusted computing technology is cryptology. In this paper, we analyze the key and credential mechanism which is two basic aspects in the cryptology application of trusted computing. We give an example application to illustrate that the TPM enabled key and credential mechanism can improve the security of computer system.

Behavior Measurement Model Based on Prediction and Control of Trusted Network

In order to construct the trusted network and realize the trust of network behavior,a new multi-dimensional behavior measurement model based on prediction and control is presented.By using behavior predictive equation,individual similarity function,group similarity function,direct trust assessment function,and generalized predictive control,this model can guarantee the trust of an end user and users in its network.Compared with traditional measurement model,the model considers different characteristics of various networks.The trusted measurement policies established according to different network environments have better adaptability.By constructing trusted group,the threats to trusted group will be reduced greatly.Utilizing trusted group to restrict individuals in network can ensure the fault tolerance of trustworthiness of trusted individuals and group.The simulation shows that this scheme can support behavior measurement more efficiently than traditional ones and the model resists viruses and Trojans more efficiently than older ones.

Design and Implementation of a Bootstrap Trust Chain

The chain of trust in bootstrap process is the basis of whole system trust in the trusted computing group （TCG） definition. This paper presents a design and implementation of a bootstrap trust chain in PC based on the Windows and today＇s commodity hardware, merely depends on availability of an embedded security module （ESM）. ESM and security enhanced BIOS is the root of trust, PMBR （Pre-MBR） checks the integrity of boot data and Windows kernel, which is a checking agent stored in ESM. In the end, the paper analyzed the mathematic expression of the chain of trust and the runtime performance compared with the common booring process. The trust chain bootstrap greatly strengthens the security of personal computer system, and affects the runtime performance with only adding about 12% booting time.

TPM Context Manager and Dynamic Configuration Management for Trusted Virtualization Platform

It is absolutely critical that trusted configuration management which significantly affects trust chain establishment, sealing storage and remote attestation, especially in trusted virtualization platform like Xen whose system configuration changes easily. TPM （trusted platform module） context manager is presented to carry out dynamic configuration management for virtual machine. It manages the TPM command requests and VM （virtual machine） configurations. The dynamic configuration representa- tion method based on Merkle hash tree is explicitly proposed against TCG （trusted computing group） static configuration representation. It reflects the true VM status in real time even if the configuration has changed, and it eliminates the invalidation of configuration representation, sealing storage and remote attestation. TPM context manager supports TCG storage protection, remote attestation etc, which greatly enhances the security on trusted virtualization platform.

Trust Degree of Web Services and Its Evaluation with Neural Network

The concept and definition of trust degree of Web service is given. Evaluating trust degree of Web services with the method of neural network from the aspect of trust history sequence is proposed. The principle of the method, applicable neural network structure, neural network construc ting, input standardization, training sample constructing, and the procedure of evaluating trust degree of Web services with trained neural network are described. Experiments show that it is feasible and effective to evaluate trust degree of Web Service with neural network.

Modelling the Roles of Cewebrity Trust and Platform Trust in Consumers’Propensity of Live-Streaming:An Extended TAM Method

Live streaming is a booming industry in China,involving an increasing number of Internet users.Previous studies show that trust is a cornerstone to develop ecommerce.Trust in the streaming industry is different from that of other e-commerce areas.There are two major dimensions of trust in the live streaming context:platform trust and cewebrity trust,which are both important for customers to adopt and reuse a specific live streaming service.We collected questionnaire data from 520 participates who have used live streaming services in China.We model the collected data and identified factors that can influence users’propensity by an extended technology acceptance model(TAM)method.According to our analysis,both cewebrity trust and platform trust will greatly influence users’intention to reuse a certain platform.Moreover,results also indicate that cewebrity trust is far more important than platform trust.These findings can lead to several management strategies to improve the adherence of users to streaming platforms.

A Trusted Host’s Authentication Access and Control Model Faced on User Action

The conception of trusted network connection （TNC） is introduced, and the weakness of TNC to control user＇s action is analyzed. After this, the paper brings out a set of secure access and control model based on access, authorization and control, and related authentication protocol. At last the security of this model is analyzed. The model can improve TNC＇s security of user control and authorization.

Optimization Strategy Using Dynamic Metamodel Based on Trust Region and Biased Sampling Method

Combining a trust region method with a biased sampling method,a novel optimization strategy(TRBSKRG)based on a dynamic metamodel is proposed.Initial sampling points are selected by a maximin Latin hypercube design method,and the metamodel is constructed with Kriging functions.The global optimization algorithm is employed to perform the biased sampling by searching the maximum expectation improvement point or the minimum of surrogate prediction point within the trust region.And the trust region is updated according to the current known information.The iteration continues until the potential global solution of the true optimization problem satisfied the convergence conditions.Compared with the trust region method and the biased sampling method,the proposed optimization strategy can obtain the global optimal solution to the test case,in which improvements in computation efficiency are also shown.When applied to an aerodynamic design optimization problem,the aerodynamic performance of tandem UAV is improved while meeting the constraints,which verifies its engineering application.

Survey on Key Technology Development and Application in Trusted Computing

Trusted computing,which can effectively increase the credibility of information system,has made great achievements and is in continuous development. For country who is going to strengthen network construction like China,it is an important fundamental supporting technology worth researching. China is in the international forefront in the field of trusted computing. This paper gives comprehensive introductions to the new development and application of key technologies in trusted computing,such as various trusted platform modules(TPM、TCM、TPCM),TCG Software Stack(TSS),trusted cloud server and Trusted Execution Environment(TEE). We illustrate the progressing and application extension of these technologies and also point out some key problems worth studying in the future.

Broken Rotor Bar Fault Detection of Induction Motors Using a Joint Algorithm of Trust Region and Modified Bare-bones Particle Swarm Optimization

A precise detection of the fault feature parameter of motor current is a new research hotspot in the broken rotor bar(BRB) fault diagnosis of induction motors. Discrete Fourier transform(DFT) is the most popular technique in this field, owing to low computation and easy realization. However, its accuracy is often limited by the data window length, spectral leakage, fence e ect, etc. Therefore, a new detection method based on a global optimization algorithm is proposed. First, a BRB fault current model and a residual error function are designed to transform the fault parameter detection problem into a nonlinear least-square problem. Because this optimization problem has a great number of local optima and needs to be resolved rapidly and accurately, a joint algorithm(called TR-MBPSO) based on a modified bare-bones particle swarm optimization(BPSO) and trust region(TR) is subsequently proposed. In the TR-MBPSO, a reinitialization strategy of inactive particle is introduced to the BPSO to enhance the swarm diversity and global search ability. Meanwhile, the TR is combined with the modified BPSO to improve convergence speed and accuracy. It also includes a global convergence analysis, whose result proves that the TR-MBPSO can converge to the global optimum with the probability of 1. Both simulations and experiments are conducted, and the results indicate that the proposed detection method not only has high accuracy of parameter estimation with short-time data window, e.g., the magnitude and frequency precision of the fault-related components reaches 10^(-4), but also overcomes the impacts of spectral leakage and non-integer-period sampling. The proposed research provides a new BRB detection method, which has enough precision to extract the parameters of the fault feature components.

A GLOBALLY AND SUPERLINEARLY CONVERGENT TRUST REGION METHOD FOR LC^1 OPTIMIZATION PROBLEMS

A new trust region algorithm for solving convex LC 1 optimization problem is presented.It is proved that the algorithm is globally convergent and the rate of convergence is superlinear under some reasonable assumptions.

Merkle Tree Digital Signature and Trusted Computing Platform

Lack of efficiency in the initial key generation process is a serious shortcoming of Merkle tree signature scheme with a large number of possible signatures. Based on two kinds of Merkle trees, a new tree type signature scheme is constructed, and it is provably existentially unforgeable under adaptive chosen message attack. By decentralizing the initial key generation process of the original scheme within the signature process, a large Merkle tree with 6.87×10^10 possible signatures can be initialized in 590 milliseconds. Storing some small Merkle trees in hard disk and memory can speed up Merkle tree signature scheme. Mekle tree signature schemes are fit for trusted computing platform in most scenarios.