Volunteered geographic information(VGI)has entered a phase where there are both a substantial amount of crowdsourced information available and a big interest in using it by organizations.But the issue of deciding the ...Volunteered geographic information(VGI)has entered a phase where there are both a substantial amount of crowdsourced information available and a big interest in using it by organizations.But the issue of deciding the quality of VGI without resorting to a comparison with authoritative data remains an open challenge.This article first formulates the problem of quality assessment of VGI data.Then presents a model to measure trustworthiness of information and reputation of contributors by analyzing geometric,qualitative,and semantic aspects of edits over time.An implementation of the model is running on a small data-set for a preliminary empirical validation.The results indicate that the computed trustworthiness provides a valid approximation of VGI quality.展开更多
The trustworthiness analysis and evaluation are the bases of the trust chain transfer. In this paper the formal method of trustworthiness analysis of a system based on the noninterfer- ence （NI） theory of the inform...The trustworthiness analysis and evaluation are the bases of the trust chain transfer. In this paper the formal method of trustworthiness analysis of a system based on the noninterfer- ence （NI） theory of the information flow is studied. Firstly, existing methods cannot analyze the impact of the system states on the trustworthiness of software during the process of trust chain trans- fer. To solve this problem, the impact of the system state on trust- worthiness of software is investigated, the run-time mutual interfer- ence behavior of software entitles is described and an interference model of the access control automaton of a system is established. Secondly, based on the intransitive noninterference （INI） theory, a formal analytic method of trustworthiness for trust chain transfer is proposed, providing a theoretical basis for the analysis of dynamic trustworthiness of software during the trust chain transfer process. Thirdly, a prototype system with dynamic trustworthiness on a plat- form with dual core architecture is constructed and a verification algorithm of the system trustworthiness is provided. Finally, the monitor hypothesis is extended to the dynamic monitor hypothe- sis, a theorem of static judgment rule of system trustworthiness is provided, which is useful to prove dynamic trustworthiness of a system at the beginning of system construction. Compared with previous work in this field, this research proposes not only a formal analytic method for the determination of system trustworthiness, but also a modeling method and an analysis algorithm that are feasible for practical implementation.展开更多
Weighted factor is given to access eontrol policies to express the importanceof policy and its effect on access control decision. According to this weighted access controlframework, a trustworthiness model for aceess ...Weighted factor is given to access eontrol policies to express the importanceof policy and its effect on access control decision. According to this weighted access controlframework, a trustworthiness model for aceess request is also given. In this model, we give themeasure of trustworthiness factor to access request- by using some idea of uncertainty reasoning ofexpert system, present and prove the parallel propagation formula of request trustworthiness factoramong multiple policies, and get thefinal trustworthiness factor to decide whether authorizing. Inthis model, authorization decision is given according to the calculation of request trustworthinessfactor, which is more understandable, more suitable for real requirement and more powerfulforsecurity enhancement than traditional methods. Meanwhile the finer access control granularity isanother advantage.展开更多
Under the global circumstances where data leakage gets more and more severe, we present a trustworthiness-based distribution model that aims at data leakage prevention （DLP）. In our model, first, the distributor cal...Under the global circumstances where data leakage gets more and more severe, we present a trustworthiness-based distribution model that aims at data leakage prevention （DLP）. In our model, first, the distributor calculates the user＇s trustworthiness based on his historical behaviors; second, according to the user＇s trustworthiness and his obtained file set overlapping leaked file set, the distributor accesses the probability of the user＇s intentional leak behavior as the subjective risk assessment; third, the distributor evaluates the user＇s platform vulnerability as an objective element; last, the distributor makes decisions whether to distribute the file based on the integrated risk assessment. The experiments indicate that the model can distinguish users of different types and make the probability of malicious users＇ requirements being denied much higher than that of honest users＇ requirements being denied, so that the model is capable of preventing data leakage validly.展开更多
In order to analyze the trustworthiness of complex software systems,we propose a model of evidence-based software trustworthiness called trustworthiness derivation tree(TDT).The basic idea of constructing a TDT is to ...In order to analyze the trustworthiness of complex software systems,we propose a model of evidence-based software trustworthiness called trustworthiness derivation tree(TDT).The basic idea of constructing a TDT is to refine main properties into key ingredients and continue the refinement until basic facts such as evidences are reached.The skeleton of a TDT can be specified by a set of rules,which are convenient for automated reasoning in Prolog.We develop a visualization tool that can construct the skeleton of a TDT by taking the rules as input,and allow a user to edit the TDT in a graphical user interface.In a software development life cycle,TDTs can serve as a communication means for different stakeholders to agree on the properties about a system in the requirement analysis phase,and they can be used for deductive reasoning so as to verify whether the system achieves trustworthiness in the product validation phase.We have piloted the approach of using TDTs in more than a dozen real scenarios of software development.Indeed,using TDTs helped us to discover and then resolve some subtle problems.展开更多
Software trustworthiness includes many attributes.Reasonable weight allocation of trustworthy at-tributes plays a key role in the software trustworthiness measurement.In practical application,attribute weight usually ...Software trustworthiness includes many attributes.Reasonable weight allocation of trustworthy at-tributes plays a key role in the software trustworthiness measurement.In practical application,attribute weight usually comes from experts'evaluation to attributes and hidden information derived from attributes.Therefore,when the weight of attributes is researched,it is necessary to consider weight from subjective and objective as-pects.First,a novel weight allocation method is proposed by combining the fuzzy analytical hierarchy process(FAHP)method and the criteria importance though intercrieria correlation(CRITIC)method.Second,based on the weight allocation method,the trustworthiness measurement models of component-based software are estab-lished according to the seven combination structures of components.Third,the model reasonability is verified via proving some metric criteria.Finally,a case is carried out.According to the comparison with other models,the result shows that the model has the advantage of utilizing hidden information fully and analyzing the com-bination of components effectively.It is an important guide for measuring the trustworthiness measurement of component-based software.展开更多
For a more accurate and comprehensive assessment of the trustworthiness of component-based soft- ware system, the fuzzy analytic hierarchy process is introduced to establish the analysis model. Combine qualitative and...For a more accurate and comprehensive assessment of the trustworthiness of component-based soft- ware system, the fuzzy analytic hierarchy process is introduced to establish the analysis model. Combine qualitative and quantitative analyses, the impacts to overall trustworthiness by the different types of components are distinguished. Considering the coupling relationship between components, dividing the system into several layers from target layer to scheme layer, evaluating the scheme advantages disadvantages by group decision-making, the trustworthiness of a typical J2EE structured component-based software is assessed. The trustworthiness asses model of the software components provides an effective methods of operation.展开更多
The trustworthiness of virtual machines is a big security issue in cloud computing. In this paper, we aimed at designing a practical trustworthiness mechanism in virtual environment. With the assist of a third certifi...The trustworthiness of virtual machines is a big security issue in cloud computing. In this paper, we aimed at designing a practical trustworthiness mechanism in virtual environment. With the assist of a third certificate agent, the cloud user generates a trust base and extends it to its VMs. For each service running on the VM, a hash value is generated from all the necessary modules, and these hash values are organized and maintained with a specially designed hash tree whose root is extended from the user's trust base. Before the VM loads a service, the hash tree is verified from the coordinated hash value to check the trustworthiness of the service.展开更多
The present study examines the impact of induced social stress on facial trustworthiness judgments in individuals with schizophrenia(SCZ) and the associations between symptoms and trustworthiness ratings. Thirty-three...The present study examines the impact of induced social stress on facial trustworthiness judgments in individuals with schizophrenia(SCZ) and the associations between symptoms and trustworthiness ratings. Thirty-threeindividuals with SCZ and fortyhealthy controls (HC) were asked to rate the trustworthiness of 24 digitally morphed faces in two counterbalanced conditions.Mild social stress was induced by listening to loud noises from a busy street. BPRS, CAPE-42,and the Paranoia Scale measuredthe severity of symptoms. We did not observe significant differences in trustworthiness judgments between the patient and controlgroups. Social stress did not impact trust judgments. Paranoia was negatively connected to trustworthiness ratings in thecontrol group. Subjective rating of stress in noise condition was negatively associated with paranoia only in the control sample.In the patient group, a negative correlation was found between trustworthiness ratings in stress conditions and the severity ofself-reportednegative symptoms. Our results suggest that mild social stress does not significantly affect trustworthiness judgmentsin either patients with SCZ or in HC. Differences between the patient and control groups in trustworthiness judgmentswere negligible. Overall, the results of this study can be considered mainly negative and contrast with previous studies. The stressinduction paradigm or a smaller sample size might cause observed results. In controls, biased face perception was linked to traitparanoia. By contrast, in SCZ, other factors might impact trust perception and need further examination.展开更多
The integration of large language models(LLMs)into financial applications has demonstrated remarkable potential for enhancing decision-making processes,automating operations,and delivering personalized services.Howeve...The integration of large language models(LLMs)into financial applications has demonstrated remarkable potential for enhancing decision-making processes,automating operations,and delivering personalized services.However,the high-stakes nature of financial systems demands a very high level of trustworthiness that current LLMs often fail to meet.展开更多
Developing trusted softwares has become an important trend and a natural choice in the development of software technology and applications. At present, the method of measurement and assessment of software trustworthin...Developing trusted softwares has become an important trend and a natural choice in the development of software technology and applications. At present, the method of measurement and assessment of software trustworthiness cannot guarantee safe and reliable operations of software systems completely and effectively. Based on the dynamical system study, this paper interprets the characteristics of be- haviors of software systems and the basic scientific problems of software trustworthiness complexity, analyzes the characteristics of complexity of software trustworthiness, and proposes to study the soft- ware trustworthiness measurement in terms of the complexity of software trustworthiness. Using the dynamical statistical analysis methods, the paper advances an invariant-measure based assessment method of software trustworthiness by statistical indices, and hereby provides a dynamical criterion for the untrustworthiness of software systems. By an example, the feasibility of the proposed dynamical statistical analysis method in software trustworthiness measurement is demonstrated using numerical simulations and theoretical analysis.展开更多
Developing trusted softwares has become an important trend and a natural choice in the development of software technology and applications, and software trustworthiness modeling has become a prerequisite and necessary...Developing trusted softwares has become an important trend and a natural choice in the development of software technology and applications, and software trustworthiness modeling has become a prerequisite and necessary means. To discuss and explain the basic scientific problems in software trustworthiness and to establish theoretical foundations for software trustworthiness measurement, combining the ideas of dynamical system study, this paper studies evolutionary laws of software trustworthiness and the dynamical mechanism under the effect of various internal and external factors, and proposes dynamical models for software trustworthiness, thus, software trustworthiness can be considered as the statistical characteristics of behaviors of software systems in the dynamical and open environment. By analyzing two simple examples, the paper explains the relationship between the limit evolutionary behaviors of software trustworthiness attributes and dynamical system characteristics, and interprets the dynamical characteristics of software trustworthiness and their evolutionary complexity.展开更多
Generative Adversarial Networks(GANs)have become valuable tools in medical imaging,enabling realistic image synthesis for enhancement,augmentation,and restoration.However,their integration into clinical workflows rais...Generative Adversarial Networks(GANs)have become valuable tools in medical imaging,enabling realistic image synthesis for enhancement,augmentation,and restoration.However,their integration into clinical workflows raises concerns,particularly the risk of subtle distortions or hallucinations that may undermine diagnostic accuracy and weaken trust in AI-assisted decision-making.To address this challenge,we propose a hybrid deep learning framework designed to detect GAN-induced artifacts in medical images,thereby reinforcing the reliability of AI-driven diagnostics.The framework integrates low-level statistical descriptors,including high-frequency residuals and Gray-Level Co-occurrence Matrix(GLCM)texture features,with high-level semantic representations extracted from a pre-trained ResNet18.This dual-stream approach enables detection of both pixel-level anomalies and structural inconsistencies introduced by GAN-based manipulation.We validated the framework on a curated dataset of 10,000 medical images,evenly split between authentic and GAN-generated samples across four modalities:MRI,CT,X-ray,and fundus photography.To improve generalizability to real-world clinical settings,we incorporated domain adaptation strategies such as adversarial training and style transfer,reducing domain shift by 15%.Experimental results demonstrate robust performance,achieving 92.6%accuracy and an F1-score of 0.91 on synthetic test data,and maintaining strong performance on real-world GAN-modified images with 87.3%accuracy and an F1-score of 0.85.Additionally,the model attained an AUC of 0.96 and an average precision of 0.92,outperforming conventional GAN detection pipelines and baseline Convolutional Neural Network(CNN)architectures.These findings establish the proposed framework as an effective and reliable solution for detecting GAN-induced hallucinations in medical imaging,representing an important step toward building trustworthy and clinically deployable AI systems.展开更多
Artificial Intelligence(AI)is changing healthcare by helping with diagnosis.However,for doctors to trust AI tools,they need to be both accurate and easy to understand.In this study,we created a new machine learning sy...Artificial Intelligence(AI)is changing healthcare by helping with diagnosis.However,for doctors to trust AI tools,they need to be both accurate and easy to understand.In this study,we created a new machine learning system for the early detection of Autism Spectrum Disorder(ASD)in children.Our main goal was to build a model that is not only good at predicting ASD but also clear in its reasoning.For this,we combined several different models,including Random Forest,XGBoost,and Neural Networks,into a single,more powerful framework.We used two different types of datasets:(i)a standard behavioral dataset and(ii)a more complex multimodal dataset with images,audio,and physiological information.The datasets were carefully preprocessed for missing values,redundant features,and dataset imbalance to ensure fair learning.The results outperformed the state-of-the-art with a Regularized Neural Network,achieving 97.6%accuracy on behavioral data.Whereas,on the multimodal data,the accuracy is 98.2%.Other models also did well with accuracies consistently above 96%.We also used SHAP and LIME on a behavioral dataset for models’explainability.展开更多
In this paper, the architecture of trustworthy and controllable networks is discussed to meet arising application requirements. After reviewing the lessons and experiences of success and failure in the Internet and su...In this paper, the architecture of trustworthy and controllable networks is discussed to meet arising application requirements. After reviewing the lessons and experiences of success and failure in the Internet and summarizing related work, we analyze the basic targets of providing trustworthiness and controllability. Then, the anticipant architecture is introduced. Based on the resulting design, several trustworthy and controllable mechanisms are also discussed.展开更多
Recent years see an increasing concern over the trustworthiness of Internet-based software. By analyzing the trustworthiness of Internet-based software and the nature of the Internet applications, we point out that, o...Recent years see an increasing concern over the trustworthiness of Internet-based software. By analyzing the trustworthiness of Internet-based software and the nature of the Internet applications, we point out that, on the one hand, due to the openness and dynamic nature of the Internet, the identity trustworthiness and the capability trustworthiness of the software are facing serious challenges; on the other hand, in order to ensure the trustworthiness of the whole system, emerging computing paradigms based on the collaboration of autonomous software need some impacts on the behavior of the software. Here we put forward a conceptual model for the trustworthiness of Internet-based software, and propose a trustworthy assurance framework for Internet-based virtual computing environment （iVCE）. This framework deals with the trustworthy properties of software on identity, capability and behavior in a combinated way. The authorization management in inter-domain computing environment, assurance on high availability of service and incentive mechanism for autonomic collaboration are taken as three core mechanisms of iVCE trustworthy assurance.展开更多
As trust becomes increasingly important in software domain,software trustworthiness--as a complex high-composite concept,has developed into a big challenge people have to face,especially in the current open,dynamic an...As trust becomes increasingly important in software domain,software trustworthiness--as a complex high-composite concept,has developed into a big challenge people have to face,especially in the current open,dynamic and ever-changing Internet environment.Furthermore,how to recognize and define trust problem from its nature and how to measure software trustworthiness correctly and effectively play a key role in improving users'trust in choosing software.Based on trust theory in the field of humanities and sociology,this paper proposes a measurable S2S(Social-to-Software)software trustworthiness framework,introduces a generalized indicator loss to unify three parts of trustworthiness result,and presents a whole metric solution for software trustworthiness,including the advanced J-M model based on power function and time-loss rate for ability trustworthiness measurement,the fuzzy comprehensive evaluation advanced-model considering effect of multiple short boards for basic standard trustworthiness,and the identity trustworthiness measurement method based on the code homology detecting tools.Finally,it provides a case study to verify that the solution is applicable and effective.展开更多
The integration of machine learning(ML)into geohazard assessment has successfully instigated a paradigm shift,leading to the production of models that possess a level of predictive accuracy previously considered unatt...The integration of machine learning(ML)into geohazard assessment has successfully instigated a paradigm shift,leading to the production of models that possess a level of predictive accuracy previously considered unattainable.However,the black-box nature of these systems presents a significant barrier,hindering their operational adoption,regulatory approval,and full scientific validation.This paper provides a systematic review and synthesis of the emerging field of explainable artificial intelligence(XAI)as applied to geohazard science(GeoXAI),a domain that aims to resolve the long-standing trade-off between model performance and interpretability.A rigorous synthesis of 87 foundational studies is used to map the intellectual and methodological contours of this rapidly expanding field.The analysis reveals that current research efforts are concentrated predominantly on landslide and flood assessment.Methodologically,tree-based ensembles and deep learning models dominate the literature,with SHapley Additive exPlanations(SHAP)frequently adopted as the principal post-hoc explanation technique.More importantly,the review further documents how the role of XAI has shifted:rather than being used solely as a tool for interpreting models after training,it is increasingly integrated into the modeling cycle itself.Recent applications include its use in feature selection,adaptive sampling strategies,and model evaluation.The evidence also shows that GeoXAI extends beyond producing feature rankings.It reveals nonlinear thresholds and interaction effects that generate deeper mechanistic insights into hazard processes and mechanisms.Nevertheless,several key challenges remain unresolved within the field.These persistent issues are especially pronounced when considering the crucial necessity for interpretation stability,the demanding scholarly task of reliably distinguishing correlation from causation,and the development of appropriate methods for the treatment of complex spatio-temporal dynamics.展开更多
Practical applications of smart cities and the Internet of Things(IoT)have multiplied,posing many difficulties in network performance,dependability,and security.Concerns of accessibility,reliability,sustainability,and...Practical applications of smart cities and the Internet of Things(IoT)have multiplied,posing many difficulties in network performance,dependability,and security.Concerns of accessibility,reliability,sustainability,and security too have arisen correspondingly because of the decentralized character of the smart city and IoT systems.Fog computing offers a foundation for various applications,including cognitive support,health and social services,intelligent transportation systems,and pervasive computing and communications.Fog computing can help enhance these apps'productivity and lower the end-to-end delay experienced by such time-sensitive applications.In this research,we propose a reliable and secure service delivery strategy at the network edge for smart cities.To improve the availability and dependability,along with the security of smart city applications,the approach employs a combined method uniting distributed fog servers in addition to mist servers with the help of an intrusion detection system.Simulation findings suggest a reduction of 40.3%in the delay incurred by each service request for highly dense areas and 60.6%for moderately dense environments.Furthermore,the system has low false-negative rates and high detection and accuracy rates,decreasing service requests 2%.展开更多
文摘Volunteered geographic information(VGI)has entered a phase where there are both a substantial amount of crowdsourced information available and a big interest in using it by organizations.But the issue of deciding the quality of VGI without resorting to a comparison with authoritative data remains an open challenge.This article first formulates the problem of quality assessment of VGI data.Then presents a model to measure trustworthiness of information and reputation of contributors by analyzing geometric,qualitative,and semantic aspects of edits over time.An implementation of the model is running on a small data-set for a preliminary empirical validation.The results indicate that the computed trustworthiness provides a valid approximation of VGI quality.
基金supported by the Natural Science Foundation of Jiangsu Province(BK2012237)
文摘The trustworthiness analysis and evaluation are the bases of the trust chain transfer. In this paper the formal method of trustworthiness analysis of a system based on the noninterfer- ence （NI） theory of the information flow is studied. Firstly, existing methods cannot analyze the impact of the system states on the trustworthiness of software during the process of trust chain trans- fer. To solve this problem, the impact of the system state on trust- worthiness of software is investigated, the run-time mutual interfer- ence behavior of software entitles is described and an interference model of the access control automaton of a system is established. Secondly, based on the intransitive noninterference （INI） theory, a formal analytic method of trustworthiness for trust chain transfer is proposed, providing a theoretical basis for the analysis of dynamic trustworthiness of software during the trust chain transfer process. Thirdly, a prototype system with dynamic trustworthiness on a plat- form with dual core architecture is constructed and a verification algorithm of the system trustworthiness is provided. Finally, the monitor hypothesis is extended to the dynamic monitor hypothe- sis, a theorem of static judgment rule of system trustworthiness is provided, which is useful to prove dynamic trustworthiness of a system at the beginning of system construction. Compared with previous work in this field, this research proposes not only a formal analytic method for the determination of system trustworthiness, but also a modeling method and an analysis algorithm that are feasible for practical implementation.
文摘Weighted factor is given to access eontrol policies to express the importanceof policy and its effect on access control decision. According to this weighted access controlframework, a trustworthiness model for aceess request is also given. In this model, we give themeasure of trustworthiness factor to access request- by using some idea of uncertainty reasoning ofexpert system, present and prove the parallel propagation formula of request trustworthiness factoramong multiple policies, and get thefinal trustworthiness factor to decide whether authorizing. Inthis model, authorization decision is given according to the calculation of request trustworthinessfactor, which is more understandable, more suitable for real requirement and more powerfulforsecurity enhancement than traditional methods. Meanwhile the finer access control granularity isanother advantage.
基金Supported by the National High Technology Research and Development Program of China (863 Program) (2009AA01Z442, 2008AA01Z404)the National Natural Science Foundation of China (90718006, 60970114)
文摘Under the global circumstances where data leakage gets more and more severe, we present a trustworthiness-based distribution model that aims at data leakage prevention （DLP）. In our model, first, the distributor calculates the user＇s trustworthiness based on his historical behaviors; second, according to the user＇s trustworthiness and his obtained file set overlapping leaked file set, the distributor accesses the probability of the user＇s intentional leak behavior as the subjective risk assessment; third, the distributor evaluates the user＇s platform vulnerability as an objective element; last, the distributor makes decisions whether to distribute the file based on the integrated risk assessment. The experiments indicate that the model can distinguish users of different types and make the probability of malicious users＇ requirements being denied much higher than that of honest users＇ requirements being denied, so that the model is capable of preventing data leakage validly.
基金the National Natural Science Foundation of China (Nos.61832015 and 62072176)the Inria-CAS Joint Project Quasar and Shanghai Trusted Industry Internet Software Collaborative Innovation Center。
文摘In order to analyze the trustworthiness of complex software systems,we propose a model of evidence-based software trustworthiness called trustworthiness derivation tree(TDT).The basic idea of constructing a TDT is to refine main properties into key ingredients and continue the refinement until basic facts such as evidences are reached.The skeleton of a TDT can be specified by a set of rules,which are convenient for automated reasoning in Prolog.We develop a visualization tool that can construct the skeleton of a TDT by taking the rules as input,and allow a user to edit the TDT in a graphical user interface.In a software development life cycle,TDTs can serve as a communication means for different stakeholders to agree on the properties about a system in the requirement analysis phase,and they can be used for deductive reasoning so as to verify whether the system achieves trustworthiness in the product validation phase.We have piloted the approach of using TDTs in more than a dozen real scenarios of software development.Indeed,using TDTs helped us to discover and then resolve some subtle problems.
基金the Natural Science Foundation of Anhui Province (No.2108085MF204)the National Natural Science Foundation of China (Nos.62162014 and 62077029)the Program of the Abroad Visiting of Excellent Young Talents of Universities in Anhui Province (No.GXGWFX2019022)。
文摘Software trustworthiness includes many attributes.Reasonable weight allocation of trustworthy at-tributes plays a key role in the software trustworthiness measurement.In practical application,attribute weight usually comes from experts'evaluation to attributes and hidden information derived from attributes.Therefore,when the weight of attributes is researched,it is necessary to consider weight from subjective and objective as-pects.First,a novel weight allocation method is proposed by combining the fuzzy analytical hierarchy process(FAHP)method and the criteria importance though intercrieria correlation(CRITIC)method.Second,based on the weight allocation method,the trustworthiness measurement models of component-based software are estab-lished according to the seven combination structures of components.Third,the model reasonability is verified via proving some metric criteria.Finally,a case is carried out.According to the comparison with other models,the result shows that the model has the advantage of utilizing hidden information fully and analyzing the com-bination of components effectively.It is an important guide for measuring the trustworthiness measurement of component-based software.
基金Sponsored by the National High Technology Research and Development Program of China ("863"Program) (2009AA01Z433)
文摘For a more accurate and comprehensive assessment of the trustworthiness of component-based soft- ware system, the fuzzy analytic hierarchy process is introduced to establish the analysis model. Combine qualitative and quantitative analyses, the impacts to overall trustworthiness by the different types of components are distinguished. Considering the coupling relationship between components, dividing the system into several layers from target layer to scheme layer, evaluating the scheme advantages disadvantages by group decision-making, the trustworthiness of a typical J2EE structured component-based software is assessed. The trustworthiness asses model of the software components provides an effective methods of operation.
基金supported by the National Natural Science Foundation of China(No.6127249261572521)+1 种基金Natural Science Foundation of Shaanxi Provence(No.2013JM8012)Fundamental Research Project of CAPF(No.WJY201520)
文摘The trustworthiness of virtual machines is a big security issue in cloud computing. In this paper, we aimed at designing a practical trustworthiness mechanism in virtual environment. With the assist of a third certificate agent, the cloud user generates a trust base and extends it to its VMs. For each service running on the VM, a hash value is generated from all the necessary modules, and these hash values are organized and maintained with a specially designed hash tree whose root is extended from the user's trust base. Before the VM loads a service, the hash tree is verified from the coordinated hash value to check the trustworthiness of the service.
基金supported by VedeckáGrantováAgentúra MŠVVaM SR a SAV,1/0493/23,1/0184/19Agentúra na Podporu Výskumu a Vývoja,APVV-20-0185Comenius University Science Park supported by the Research and Development Operational Programme funded by the ERDF,grant number ITMS 26240220086.
文摘The present study examines the impact of induced social stress on facial trustworthiness judgments in individuals with schizophrenia(SCZ) and the associations between symptoms and trustworthiness ratings. Thirty-threeindividuals with SCZ and fortyhealthy controls (HC) were asked to rate the trustworthiness of 24 digitally morphed faces in two counterbalanced conditions.Mild social stress was induced by listening to loud noises from a busy street. BPRS, CAPE-42,and the Paranoia Scale measuredthe severity of symptoms. We did not observe significant differences in trustworthiness judgments between the patient and controlgroups. Social stress did not impact trust judgments. Paranoia was negatively connected to trustworthiness ratings in thecontrol group. Subjective rating of stress in noise condition was negatively associated with paranoia only in the control sample.In the patient group, a negative correlation was found between trustworthiness ratings in stress conditions and the severity ofself-reportednegative symptoms. Our results suggest that mild social stress does not significantly affect trustworthiness judgmentsin either patients with SCZ or in HC. Differences between the patient and control groups in trustworthiness judgmentswere negligible. Overall, the results of this study can be considered mainly negative and contrast with previous studies. The stressinduction paradigm or a smaller sample size might cause observed results. In controls, biased face perception was linked to traitparanoia. By contrast, in SCZ, other factors might impact trust perception and need further examination.
文摘The integration of large language models(LLMs)into financial applications has demonstrated remarkable potential for enhancing decision-making processes,automating operations,and delivering personalized services.However,the high-stakes nature of financial systems demands a very high level of trustworthiness that current LLMs often fail to meet.
基金the National Basic Research Program of China (Grant No. 2005CB321900)the National Natural Science Foundation of China (Grant No. 60473091)
文摘Developing trusted softwares has become an important trend and a natural choice in the development of software technology and applications. At present, the method of measurement and assessment of software trustworthiness cannot guarantee safe and reliable operations of software systems completely and effectively. Based on the dynamical system study, this paper interprets the characteristics of be- haviors of software systems and the basic scientific problems of software trustworthiness complexity, analyzes the characteristics of complexity of software trustworthiness, and proposes to study the soft- ware trustworthiness measurement in terms of the complexity of software trustworthiness. Using the dynamical statistical analysis methods, the paper advances an invariant-measure based assessment method of software trustworthiness by statistical indices, and hereby provides a dynamical criterion for the untrustworthiness of software systems. By an example, the feasibility of the proposed dynamical statistical analysis method in software trustworthiness measurement is demonstrated using numerical simulations and theoretical analysis.
基金Supported partially by the National Basic Research Program of China (Grant No. 2005CB321900) the National Natural Science Foundation of China (Grant No. 60473091)
文摘Developing trusted softwares has become an important trend and a natural choice in the development of software technology and applications, and software trustworthiness modeling has become a prerequisite and necessary means. To discuss and explain the basic scientific problems in software trustworthiness and to establish theoretical foundations for software trustworthiness measurement, combining the ideas of dynamical system study, this paper studies evolutionary laws of software trustworthiness and the dynamical mechanism under the effect of various internal and external factors, and proposes dynamical models for software trustworthiness, thus, software trustworthiness can be considered as the statistical characteristics of behaviors of software systems in the dynamical and open environment. By analyzing two simple examples, the paper explains the relationship between the limit evolutionary behaviors of software trustworthiness attributes and dynamical system characteristics, and interprets the dynamical characteristics of software trustworthiness and their evolutionary complexity.
基金supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University(IMSIU)(grant number IMSIU-DDRSP2601).
文摘Generative Adversarial Networks(GANs)have become valuable tools in medical imaging,enabling realistic image synthesis for enhancement,augmentation,and restoration.However,their integration into clinical workflows raises concerns,particularly the risk of subtle distortions or hallucinations that may undermine diagnostic accuracy and weaken trust in AI-assisted decision-making.To address this challenge,we propose a hybrid deep learning framework designed to detect GAN-induced artifacts in medical images,thereby reinforcing the reliability of AI-driven diagnostics.The framework integrates low-level statistical descriptors,including high-frequency residuals and Gray-Level Co-occurrence Matrix(GLCM)texture features,with high-level semantic representations extracted from a pre-trained ResNet18.This dual-stream approach enables detection of both pixel-level anomalies and structural inconsistencies introduced by GAN-based manipulation.We validated the framework on a curated dataset of 10,000 medical images,evenly split between authentic and GAN-generated samples across four modalities:MRI,CT,X-ray,and fundus photography.To improve generalizability to real-world clinical settings,we incorporated domain adaptation strategies such as adversarial training and style transfer,reducing domain shift by 15%.Experimental results demonstrate robust performance,achieving 92.6%accuracy and an F1-score of 0.91 on synthetic test data,and maintaining strong performance on real-world GAN-modified images with 87.3%accuracy and an F1-score of 0.85.Additionally,the model attained an AUC of 0.96 and an average precision of 0.92,outperforming conventional GAN detection pipelines and baseline Convolutional Neural Network(CNN)architectures.These findings establish the proposed framework as an effective and reliable solution for detecting GAN-induced hallucinations in medical imaging,representing an important step toward building trustworthy and clinically deployable AI systems.
基金the King Salman center for Disability Research for funding this work through Research Group No.KSRG-2024-050.
文摘Artificial Intelligence(AI)is changing healthcare by helping with diagnosis.However,for doctors to trust AI tools,they need to be both accurate and easy to understand.In this study,we created a new machine learning system for the early detection of Autism Spectrum Disorder(ASD)in children.Our main goal was to build a model that is not only good at predicting ASD but also clear in its reasoning.For this,we combined several different models,including Random Forest,XGBoost,and Neural Networks,into a single,more powerful framework.We used two different types of datasets:(i)a standard behavioral dataset and(ii)a more complex multimodal dataset with images,audio,and physiological information.The datasets were carefully preprocessed for missing values,redundant features,and dataset imbalance to ensure fair learning.The results outperformed the state-of-the-art with a Regularized Neural Network,achieving 97.6%accuracy on behavioral data.Whereas,on the multimodal data,the accuracy is 98.2%.Other models also did well with accuracies consistently above 96%.We also used SHAP and LIME on a behavioral dataset for models’explainability.
基金Supported by the National Natural Science Foundation of China under Grant Nos. 60503052, 60573144, 90412012, and the National Grand Fundamental Research 973 Program of China under Grant No. 2003CB314804.
文摘In this paper, the architecture of trustworthy and controllable networks is discussed to meet arising application requirements. After reviewing the lessons and experiences of success and failure in the Internet and summarizing related work, we analyze the basic targets of providing trustworthiness and controllability. Then, the anticipant architecture is introduced. Based on the resulting design, several trustworthy and controllable mechanisms are also discussed.
文摘Recent years see an increasing concern over the trustworthiness of Internet-based software. By analyzing the trustworthiness of Internet-based software and the nature of the Internet applications, we point out that, on the one hand, due to the openness and dynamic nature of the Internet, the identity trustworthiness and the capability trustworthiness of the software are facing serious challenges; on the other hand, in order to ensure the trustworthiness of the whole system, emerging computing paradigms based on the collaboration of autonomous software need some impacts on the behavior of the software. Here we put forward a conceptual model for the trustworthiness of Internet-based software, and propose a trustworthy assurance framework for Internet-based virtual computing environment （iVCE）. This framework deals with the trustworthy properties of software on identity, capability and behavior in a combinated way. The authorization management in inter-domain computing environment, assurance on high availability of service and incentive mechanism for autonomic collaboration are taken as three core mechanisms of iVCE trustworthy assurance.
基金supported by the National Natural Science Foundation of China under Grant No.90818021the HeGaoJi Program of China under Grant No.2012zx01039-004-46the Information Security Program of National Development and Reform Commission of China under Grant No.2012-1424.
文摘As trust becomes increasingly important in software domain,software trustworthiness--as a complex high-composite concept,has developed into a big challenge people have to face,especially in the current open,dynamic and ever-changing Internet environment.Furthermore,how to recognize and define trust problem from its nature and how to measure software trustworthiness correctly and effectively play a key role in improving users'trust in choosing software.Based on trust theory in the field of humanities and sociology,this paper proposes a measurable S2S(Social-to-Software)software trustworthiness framework,introduces a generalized indicator loss to unify three parts of trustworthiness result,and presents a whole metric solution for software trustworthiness,including the advanced J-M model based on power function and time-loss rate for ability trustworthiness measurement,the fuzzy comprehensive evaluation advanced-model considering effect of multiple short boards for basic standard trustworthiness,and the identity trustworthiness measurement method based on the code homology detecting tools.Finally,it provides a case study to verify that the solution is applicable and effective.
文摘The integration of machine learning(ML)into geohazard assessment has successfully instigated a paradigm shift,leading to the production of models that possess a level of predictive accuracy previously considered unattainable.However,the black-box nature of these systems presents a significant barrier,hindering their operational adoption,regulatory approval,and full scientific validation.This paper provides a systematic review and synthesis of the emerging field of explainable artificial intelligence(XAI)as applied to geohazard science(GeoXAI),a domain that aims to resolve the long-standing trade-off between model performance and interpretability.A rigorous synthesis of 87 foundational studies is used to map the intellectual and methodological contours of this rapidly expanding field.The analysis reveals that current research efforts are concentrated predominantly on landslide and flood assessment.Methodologically,tree-based ensembles and deep learning models dominate the literature,with SHapley Additive exPlanations(SHAP)frequently adopted as the principal post-hoc explanation technique.More importantly,the review further documents how the role of XAI has shifted:rather than being used solely as a tool for interpreting models after training,it is increasingly integrated into the modeling cycle itself.Recent applications include its use in feature selection,adaptive sampling strategies,and model evaluation.The evidence also shows that GeoXAI extends beyond producing feature rankings.It reveals nonlinear thresholds and interaction effects that generate deeper mechanistic insights into hazard processes and mechanisms.Nevertheless,several key challenges remain unresolved within the field.These persistent issues are especially pronounced when considering the crucial necessity for interpretation stability,the demanding scholarly task of reliably distinguishing correlation from causation,and the development of appropriate methods for the treatment of complex spatio-temporal dynamics.
基金co-funded by the European Union under the REFRESH-Research Excellence For REgion Sustainability and High-tech Industries project number CZ.10.03.01/00/22_003/0000048 via the Operational Programme Just Transitionsupported by the Ministry of Education,Youth and Sports of the Czech Republic conducted by VSB-Technical University of Ostrava,Czechia,under Grants SP2025/021 and SP2025/039。
文摘Practical applications of smart cities and the Internet of Things(IoT)have multiplied,posing many difficulties in network performance,dependability,and security.Concerns of accessibility,reliability,sustainability,and security too have arisen correspondingly because of the decentralized character of the smart city and IoT systems.Fog computing offers a foundation for various applications,including cognitive support,health and social services,intelligent transportation systems,and pervasive computing and communications.Fog computing can help enhance these apps'productivity and lower the end-to-end delay experienced by such time-sensitive applications.In this research,we propose a reliable and secure service delivery strategy at the network edge for smart cities.To improve the availability and dependability,along with the security of smart city applications,the approach employs a combined method uniting distributed fog servers in addition to mist servers with the help of an intrusion detection system.Simulation findings suggest a reduction of 40.3%in the delay incurred by each service request for highly dense areas and 60.6%for moderately dense environments.Furthermore,the system has low false-negative rates and high detection and accuracy rates,decreasing service requests 2%.
