A trusted execution environment(TEE)is a system-on-chip and CPU system with a wide security solution available on today’s Arm application(APP)processors,which dominate the smartphone market.Generally,mobile APPs crea...A trusted execution environment(TEE)is a system-on-chip and CPU system with a wide security solution available on today’s Arm application(APP)processors,which dominate the smartphone market.Generally,mobile APPs create a trusted application(TA)in the TEE to process sensitive information,such as payment or message encryption,which is transparent to the APPs running in the rich execution environments(REEs).In detail,the REE and TEE interact and eventually send back the results to the APP in the REE through the interface provided by the TA.Such an operation definitely increases the overhead of mobile APPs.In this paper,we first present a comprehensive analysis of the performance of open-source TEE encrypted text.We then propose a high energy-efficient task scheduling strategy(ETS-TEE).By leveraging the deep learning algorithm,our policy considers the complexity of TA tasks,which are dynamically scheduled between modeling on the local device and offloading to an edge server.We evaluate our approach on Raspberry Pi 3B as the local mobile device and Jetson TX2 as the edge server.The results show that compared with the default scheduling strategy on the local device,our approach achieves an average of 38.0%energy reduction and 1.6×speedup.This greatly reduces the performance loss caused by mobile devices in order to protect the safe execution of applications,so that the trusted execution environment has both security and high performance.展开更多
Nowadays,with the significant growth of the mobile market,security issues on the Android Operation System have also become an urgent matter.Trusted execution environment(TEE)technologies are considered an option for s...Nowadays,with the significant growth of the mobile market,security issues on the Android Operation System have also become an urgent matter.Trusted execution environment(TEE)technologies are considered an option for satisfying the inviolable property by taking advantage of hardware security.However,for Android,TEE technologies still contain restrictions and limitations.The first issue is that non-original equipment manufacturer developers have limited access to the functionality of hardware-based TEE.Another issue of hardware-based TEE is the cross-platform problem.Since every mobile device supports different TEE vendors,it becomes an obstacle for developers to migrate their trusted applications to other Android devices.A software-based TEE solution is a potential approach that allows developers to customize,package and deliver the product efficiently.Motivated by that idea,this paper introduces a VTEE model,a software-based TEE solution,on Android devices.This research contributes to the analysis of the feasibility of using a virtualized TEE on Android devices by considering two metrics:computing performance and security.The experiment shows that the VTEE model can host other software-based TEE services and deliver various cryptography TEE functions on theAndroid environment.The security evaluation shows that adding the VTEE model to the existing Android does not addmore security issues to the traditional design.Overall,this paper shows applicable solutions to adjust the balance between computing performance and security.展开更多
This research critically reviews the definition of confidential computing(CC)and the security comparison of CC with other related technologies by the Confidential Computing Consortium(CCC).We demonstrate that the defi...This research critically reviews the definition of confidential computing(CC)and the security comparison of CC with other related technologies by the Confidential Computing Consortium(CCC).We demonstrate that the definitions by CCC are ambiguous,incomplete and even conflicting.We also demonstrate that the security comparison of CC with other technologies is neither scientific nor fair.We highlight the issues in the definitions and comparisons and provide initial recommendations for fixing the issues.These recommendations are the first step towards more precise definitions and reliable comparisons in the future.展开更多
Trusted Execution Environment(TEE)is an important part of the security architecture of modern mobile devices,but its secure interaction process brings extra computing burden to mobile devices.This paper takes open por...Trusted Execution Environment(TEE)is an important part of the security architecture of modern mobile devices,but its secure interaction process brings extra computing burden to mobile devices.This paper takes open portable trusted execution environment(OP-TEE)as the research object and deploys it to Raspberry Pi 3B,designs and implements a benchmark for OP-TEE,and analyzes its program characteristics.Furthermore,the application execution time,energy consumption and energy-delay product(EDP)are taken as the optimization objectives,and the central processing unit(CPU)frequency scheduling strategy of mobile devices is dynamically adjusted according to the characteristics of different applications through the combined model.The experimental result shows that compared with the default strategy,the scheduling method proposed in this paper saves 21.18%on average with the Line Regression-Decision Tree scheduling model with the shortest delay as the optimization objective.The Decision Tree-Support Vector Regression(SVR)scheduling model,which takes the lowest energy consumption as the optimization goal,saves 22%energy on average.The Decision Tree-K-Nearest Neighbor(KNN)scheduling model with the lowest EDP as the optimization objective optimizes about 33.9%on average.展开更多
This paper presents a comprehensive survey on the development of Intel SGX(software guard extensions)processors and its applications.With the advent of SGX in 2013 and its subsequent development,the corresponding rese...This paper presents a comprehensive survey on the development of Intel SGX(software guard extensions)processors and its applications.With the advent of SGX in 2013 and its subsequent development,the corresponding research works are also increasing rapidly.In order to get a more comprehensive literature review related to SGX,we have made a systematic analysis of the related papers in this area.We first search through five large-scale paper retrieval libraries by keywords(i.e.,ACM Digital Library,IEEE/IET Electronic Library,SpringerLink,Web of Science,and Elsevier Science Direct).We read and analyze a total of 128 SGX-related papers.The first round of extensive study is conducted to classify them.The second round of intensive study is carried out to complete a comprehensive analysis of the paper from various aspects.We start with the working environment of SGX and make a conclusive summary of trusted execution environment(TEE).We then focus on the applications of SGX.We also review and study multifarious attack methods to SGX framework and some recent security improvements made on SGX.Finally,we summarize the advantages and disadvantages of SGX with some future research opportunities.We hope this review could help the existing and future research works on SGX and its application for both developers and users.展开更多
Machine learning advancements in healthcare have made data collected through smartphones and wearable devices a vital source of public health and medical insights.While wearable device data help to monitor,detect,and ...Machine learning advancements in healthcare have made data collected through smartphones and wearable devices a vital source of public health and medical insights.While wearable device data help to monitor,detect,and predict diseases and health conditions,some data owners hesitate to share such sensitive data with companies or researchers due to privacy concerns.Moreover,wearable devices have been recently available as commercial products;thus large,diverse,and representative datasets are not available to most researchers.In this article,the authors propose an open marketplace where wearable device users securely monetize their wearable device records by sharing data with consumers(e.g.,researchers)to make wearable device data more available to healthcare researchers.To secure the data transactions in a privacy-preserving manner,the authors use a decentralized approach using Blockchain and Non-Fungible Tokens(NFTs).To ensure data originality and integrity with secure validation,the marketplace uses Trusted Execution Environments(TEE)in wearable devices to verify the correctness of health data.The marketplace also allows researchers to train models using Federated Learning with a TEE-backed secure aggregation of data users may not be willing to share.To ensure user participation,we model incentive mechanisms for the Federated Learning-based and anonymized data-sharing approaches using NFTs.The authors also propose using payment channels and batching to reduce smart contact gas fees and optimize user profits.If widely adopted,it’s believed that TEE and Blockchain-based incentives will promote the ethical use of machine learning with validated wearable device data in healthcare and improve user participation due to incentives.展开更多
As a product of the combination of information and energy technology,the energy internet is enormous and complex,and the absence of security safeguards at any aspect of it can cause incalculable damage.Aiming at the p...As a product of the combination of information and energy technology,the energy internet is enormous and complex,and the absence of security safeguards at any aspect of it can cause incalculable damage.Aiming at the problems that Energy Internet terminals are difficult to be trusted and the integrity of massive terminals cannot be guaranteed,this paper designs and implements a set of comprehensive credibility measures and security protection schemes,isolates various malicious operations,and ensures that the system is always in a credible state.Specifically,we develop a secure TF card control program in the Android terminal application layer to realize the overall security scheme.Experimental results prove that this security protection scheme can effectively detect illegal application packages in energy Internet terminal devices,resist malicious programs,and protect key data from theft at the same time,achieving security protection in the“thing-to-thing”interconnection scenario of the Energy Internet.展开更多
The 5G mobile Internet facilitates contents generation for online communities and platforms through human-to-human collaboration.Wikipedia,a well-known online community,uses wiki technology to build an encyclopedia th...The 5G mobile Internet facilitates contents generation for online communities and platforms through human-to-human collaboration.Wikipedia,a well-known online community,uses wiki technology to build an encyclopedia through collective intelligence and collaboration.Mainstream wiki systems adopt a centralized implementation,and while existing studies have optimized the efficiency of the wiki systems'centralized implementation,these systems still suffer from a lot of problems,for example,opacity and distrust.Over the years,blockchain has brought a flurry of fervour and decentralization to the system architecture,meanwhile giving users a sense of trust and participation.Thus,an innovative blockchain-enabled wiki framework called DecWiki is proposed to build one transparent,truthful,collaborative and autonomous encyclopedia.After several participatory design iterations,we present DecWiki's detailed architecture and its implementation in the form of a smart contract and use the interplanetary file system to complement the big data storage.Meanwhile,we use the trusted execution environment to secure sensitive information in the wireless scenario.Finally,the system overhead and the acceptance of the prototype are evaluated.Extensive experiments present its significant performance.展开更多
Decentralized cloud platforms have emerged as a promising paradigm to exploit the idle computing resources across the Internet to catch up with the ever-increasing cloud computing demands.As any user or enterprise can...Decentralized cloud platforms have emerged as a promising paradigm to exploit the idle computing resources across the Internet to catch up with the ever-increasing cloud computing demands.As any user or enterprise can be the cloud provider in the decentralized cloud,the performance assessment of the heterogeneous computing resources is of vital significance.However,with the consideration of the untrustworthiness of the participants and the lack of unified performance assessment metric,the performance monitoring reliability and the incentive for cloud providers to offer real and stable performance together constitute the computational performance assessment problem in the decentralized cloud.In this paper,we present a robust performance assessment solution RODE to solve this problem.RODE mainly consists of a performance monitoring mechanism and an assessment of the claimed performance(AoCP)mechanism.The performance monitoring mechanism first generates reliable and verifiable performance monitoring results for the workloads executed by untrusted cloud providers.Based on the performance monitoring results,the AoCP mechanism forms a unified performance assessment metric to incentivize cloud providers to offer performance as claimed.Via extensive experiments,we show RODE can accurately monitor the performance of cloud providers on the premise of reliability,and incentivize cloud providers to honestly present the performance information and maintain the performance stability.展开更多
Bitcoin transactions are pseudo-anonymous,which can be exploited to reveal a user’s private information.To eliminate this threat,this paper presents FairMixer,a highly secure and efficient Bitcoin mixing system using...Bitcoin transactions are pseudo-anonymous,which can be exploited to reveal a user’s private information.To eliminate this threat,this paper presents FairMixer,a highly secure and efficient Bitcoin mixing system using the trusted execution environments(TEEs).With the TEE’s confidentiality and integrity guarantees for code and data,FairMixer enables a correct and privacy-preserving mixing process.However,a TEE-based implementation cannot prevent the manipulation of inputs to the mixer,such as mixing request submissions and blockchain feeds.Against this background,FairMixer captures users’ mixing requests via Bitcoin transactions for deterring a malicious service provider from dropping benign participants.To constrain misbehavior during a mixing mission,a misconduct monitoring mechanism and a penalty mechanism are introduced.The proposed scheme is fully compatible with Bitcoin and forces mixes to be accountable.Finally,a prototype of FairMixer is provided using Intel Software Guard Extensions(SGX) and its performance is evaluated in the Bitcoin Testnet.FairMixer mixes 700 inputs in just 8.39 s,which outperforms most existing decentralized mixers.展开更多
A centralized trusted execution environment(TEE)has been extensively studied to provide secure and trusted computing.However,a TEE might become a throughput bottleneck if it is used to evaluate data quality when colle...A centralized trusted execution environment(TEE)has been extensively studied to provide secure and trusted computing.However,a TEE might become a throughput bottleneck if it is used to evaluate data quality when collecting large-scale data in a crowdsourcing system.It may also have security problems compromised by attackers.Here,we propose a scheme,named dTEE,for building a platform for providing distributed trusted computing by leveraging TEEs.The platform is used as an infrastructure of trusted computations for blockchain-based crowdsourcing systems,especially to securely evaluate data quality and manage remuneration:these operations are handled by a TEE group.First,dTEE uses a public blockchain with smart contracts to manage TEEs without reliance on any trusted third parties.Second,to update TEE registration information and rule out zombie TEEs,dTEE uses a reporting mechanism.To attract TEE owners to join in and provide service of trusted computations,it uses a fair monetary incentive mechanism.Third,to account for malicious attackers,we design a model with Byzantine fault tolerance,not limited to a crash-failure model.Finally,we conduct an extensive evaluation of our design on a local cluster.The results show that dTEE finishes evaluating 10,000 images within one minute and achieves about 65 tps throughput when evaluating Sudoku solution data with collective signatures both in a group of 120 TEEs.展开更多
基金supported by the National Natural Science Foundation of China (No.61902229)Fundamental Research Funds for the Central Universities (No.GK202103084).
文摘A trusted execution environment(TEE)is a system-on-chip and CPU system with a wide security solution available on today’s Arm application(APP)processors,which dominate the smartphone market.Generally,mobile APPs create a trusted application(TA)in the TEE to process sensitive information,such as payment or message encryption,which is transparent to the APPs running in the rich execution environments(REEs).In detail,the REE and TEE interact and eventually send back the results to the APP in the REE through the interface provided by the TA.Such an operation definitely increases the overhead of mobile APPs.In this paper,we first present a comprehensive analysis of the performance of open-source TEE encrypted text.We then propose a high energy-efficient task scheduling strategy(ETS-TEE).By leveraging the deep learning algorithm,our policy considers the complexity of TA tasks,which are dynamically scheduled between modeling on the local device and offloading to an edge server.We evaluate our approach on Raspberry Pi 3B as the local mobile device and Jetson TX2 as the edge server.The results show that compared with the default scheduling strategy on the local device,our approach achieves an average of 38.0%energy reduction and 1.6×speedup.This greatly reduces the performance loss caused by mobile devices in order to protect the safe execution of applications,so that the trusted execution environment has both security and high performance.
基金This work was partly supported by the Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea Government(MSIT),(No.2020-0-00952,Development of 5G edge security technology for ensuring 5G+service stability and availability,50%)the Institute of Information and Communications Technology Planning and Evaluation(IITP)grant funded by the MSIT(Ministry of Science and ICT),Korea(No.IITP-2022-2020-0-01602,ITRC(Information Technology Research Center)support program,50%).
文摘Nowadays,with the significant growth of the mobile market,security issues on the Android Operation System have also become an urgent matter.Trusted execution environment(TEE)technologies are considered an option for satisfying the inviolable property by taking advantage of hardware security.However,for Android,TEE technologies still contain restrictions and limitations.The first issue is that non-original equipment manufacturer developers have limited access to the functionality of hardware-based TEE.Another issue of hardware-based TEE is the cross-platform problem.Since every mobile device supports different TEE vendors,it becomes an obstacle for developers to migrate their trusted applications to other Android devices.A software-based TEE solution is a potential approach that allows developers to customize,package and deliver the product efficiently.Motivated by that idea,this paper introduces a VTEE model,a software-based TEE solution,on Android devices.This research contributes to the analysis of the feasibility of using a virtualized TEE on Android devices by considering two metrics:computing performance and security.The experiment shows that the VTEE model can host other software-based TEE services and deliver various cryptography TEE functions on theAndroid environment.The security evaluation shows that adding the VTEE model to the existing Android does not addmore security issues to the traditional design.Overall,this paper shows applicable solutions to adjust the balance between computing performance and security.
基金Funded by DFG Grants 389792660 as part of TRR 248—CPECand 390696704 as part of CeTI.
文摘This research critically reviews the definition of confidential computing(CC)and the security comparison of CC with other related technologies by the Confidential Computing Consortium(CCC).We demonstrate that the definitions by CCC are ambiguous,incomplete and even conflicting.We also demonstrate that the security comparison of CC with other technologies is neither scientific nor fair.We highlight the issues in the definitions and comparisons and provide initial recommendations for fixing the issues.These recommendations are the first step towards more precise definitions and reliable comparisons in the future.
基金funded by National Key Research and Development Program of China under Grant No.2019YFC1520904 from January 2020 to April 2023funded by Shaanxi Innovation Program under Grant 2023-CX-TD-04 January 2023 to December 2025.
文摘Trusted Execution Environment(TEE)is an important part of the security architecture of modern mobile devices,but its secure interaction process brings extra computing burden to mobile devices.This paper takes open portable trusted execution environment(OP-TEE)as the research object and deploys it to Raspberry Pi 3B,designs and implements a benchmark for OP-TEE,and analyzes its program characteristics.Furthermore,the application execution time,energy consumption and energy-delay product(EDP)are taken as the optimization objectives,and the central processing unit(CPU)frequency scheduling strategy of mobile devices is dynamically adjusted according to the characteristics of different applications through the combined model.The experimental result shows that compared with the default strategy,the scheduling method proposed in this paper saves 21.18%on average with the Line Regression-Decision Tree scheduling model with the shortest delay as the optimization objective.The Decision Tree-Support Vector Regression(SVR)scheduling model,which takes the lowest energy consumption as the optimization goal,saves 22%energy on average.The Decision Tree-K-Nearest Neighbor(KNN)scheduling model with the lowest EDP as the optimization objective optimizes about 33.9%on average.
基金supported in part by the National Key Research and Development Program of China under Grant No.2020AAA-0108502the National Natural Science Foundation of China under Grant Nos.61972244,U19A2060,and 61925206the HighTech Support Program from Shanghai Committee of Science and Technology under Grant No.19511121100.
文摘ion and secure enclave migration on heterogeneous security architectures.
基金supported by Fund of Shaanxi Science and Technology Research and Development Plan Project(2015GY073)Shaanxi Key Research and Development Program(2019GY-057).
文摘This paper presents a comprehensive survey on the development of Intel SGX(software guard extensions)processors and its applications.With the advent of SGX in 2013 and its subsequent development,the corresponding research works are also increasing rapidly.In order to get a more comprehensive literature review related to SGX,we have made a systematic analysis of the related papers in this area.We first search through five large-scale paper retrieval libraries by keywords(i.e.,ACM Digital Library,IEEE/IET Electronic Library,SpringerLink,Web of Science,and Elsevier Science Direct).We read and analyze a total of 128 SGX-related papers.The first round of extensive study is conducted to classify them.The second round of intensive study is carried out to complete a comprehensive analysis of the paper from various aspects.We start with the working environment of SGX and make a conclusive summary of trusted execution environment(TEE).We then focus on the applications of SGX.We also review and study multifarious attack methods to SGX framework and some recent security improvements made on SGX.Finally,we summarize the advantages and disadvantages of SGX with some future research opportunities.We hope this review could help the existing and future research works on SGX and its application for both developers and users.
文摘Machine learning advancements in healthcare have made data collected through smartphones and wearable devices a vital source of public health and medical insights.While wearable device data help to monitor,detect,and predict diseases and health conditions,some data owners hesitate to share such sensitive data with companies or researchers due to privacy concerns.Moreover,wearable devices have been recently available as commercial products;thus large,diverse,and representative datasets are not available to most researchers.In this article,the authors propose an open marketplace where wearable device users securely monetize their wearable device records by sharing data with consumers(e.g.,researchers)to make wearable device data more available to healthcare researchers.To secure the data transactions in a privacy-preserving manner,the authors use a decentralized approach using Blockchain and Non-Fungible Tokens(NFTs).To ensure data originality and integrity with secure validation,the marketplace uses Trusted Execution Environments(TEE)in wearable devices to verify the correctness of health data.The marketplace also allows researchers to train models using Federated Learning with a TEE-backed secure aggregation of data users may not be willing to share.To ensure user participation,we model incentive mechanisms for the Federated Learning-based and anonymized data-sharing approaches using NFTs.The authors also propose using payment channels and batching to reduce smart contact gas fees and optimize user profits.If widely adopted,it’s believed that TEE and Blockchain-based incentives will promote the ethical use of machine learning with validated wearable device data in healthcare and improve user participation due to incentives.
基金Supported by the State Grid Corporation of China Science and Technology Project Funding
文摘As a product of the combination of information and energy technology,the energy internet is enormous and complex,and the absence of security safeguards at any aspect of it can cause incalculable damage.Aiming at the problems that Energy Internet terminals are difficult to be trusted and the integrity of massive terminals cannot be guaranteed,this paper designs and implements a set of comprehensive credibility measures and security protection schemes,isolates various malicious operations,and ensures that the system is always in a credible state.Specifically,we develop a secure TF card control program in the Android terminal application layer to realize the overall security scheme.Experimental results prove that this security protection scheme can effectively detect illegal application packages in energy Internet terminal devices,resist malicious programs,and protect key data from theft at the same time,achieving security protection in the“thing-to-thing”interconnection scenario of the Energy Internet.
基金supported by the National Natural Science Foundation of China(NSFC)under Grant No.61932007.
文摘The 5G mobile Internet facilitates contents generation for online communities and platforms through human-to-human collaboration.Wikipedia,a well-known online community,uses wiki technology to build an encyclopedia through collective intelligence and collaboration.Mainstream wiki systems adopt a centralized implementation,and while existing studies have optimized the efficiency of the wiki systems'centralized implementation,these systems still suffer from a lot of problems,for example,opacity and distrust.Over the years,blockchain has brought a flurry of fervour and decentralization to the system architecture,meanwhile giving users a sense of trust and participation.Thus,an innovative blockchain-enabled wiki framework called DecWiki is proposed to build one transparent,truthful,collaborative and autonomous encyclopedia.After several participatory design iterations,we present DecWiki's detailed architecture and its implementation in the form of a smart contract and use the interplanetary file system to complement the big data storage.Meanwhile,we use the trusted execution environment to secure sensitive information in the wireless scenario.Finally,the system overhead and the acceptance of the prototype are evaluated.Extensive experiments present its significant performance.
基金This work is supported by the National Natural Science Foundation of China under Grant Nos.61832006 and 61872240。
文摘Decentralized cloud platforms have emerged as a promising paradigm to exploit the idle computing resources across the Internet to catch up with the ever-increasing cloud computing demands.As any user or enterprise can be the cloud provider in the decentralized cloud,the performance assessment of the heterogeneous computing resources is of vital significance.However,with the consideration of the untrustworthiness of the participants and the lack of unified performance assessment metric,the performance monitoring reliability and the incentive for cloud providers to offer real and stable performance together constitute the computational performance assessment problem in the decentralized cloud.In this paper,we present a robust performance assessment solution RODE to solve this problem.RODE mainly consists of a performance monitoring mechanism and an assessment of the claimed performance(AoCP)mechanism.The performance monitoring mechanism first generates reliable and verifiable performance monitoring results for the workloads executed by untrusted cloud providers.Based on the performance monitoring results,the AoCP mechanism forms a unified performance assessment metric to incentivize cloud providers to offer performance as claimed.Via extensive experiments,we show RODE can accurately monitor the performance of cloud providers on the premise of reliability,and incentivize cloud providers to honestly present the performance information and maintain the performance stability.
基金Supported by the National Key Research&Development Program of China (No.2018YFB0904503)。
文摘Bitcoin transactions are pseudo-anonymous,which can be exploited to reveal a user’s private information.To eliminate this threat,this paper presents FairMixer,a highly secure and efficient Bitcoin mixing system using the trusted execution environments(TEEs).With the TEE’s confidentiality and integrity guarantees for code and data,FairMixer enables a correct and privacy-preserving mixing process.However,a TEE-based implementation cannot prevent the manipulation of inputs to the mixer,such as mixing request submissions and blockchain feeds.Against this background,FairMixer captures users’ mixing requests via Bitcoin transactions for deterring a malicious service provider from dropping benign participants.To constrain misbehavior during a mixing mission,a misconduct monitoring mechanism and a penalty mechanism are introduced.The proposed scheme is fully compatible with Bitcoin and forces mixes to be accountable.Finally,a prototype of FairMixer is provided using Intel Software Guard Extensions(SGX) and its performance is evaluated in the Bitcoin Testnet.FairMixer mixes 700 inputs in just 8.39 s,which outperforms most existing decentralized mixers.
基金This work was supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(No.NRF-2019R1A2C1090713).
文摘A centralized trusted execution environment(TEE)has been extensively studied to provide secure and trusted computing.However,a TEE might become a throughput bottleneck if it is used to evaluate data quality when collecting large-scale data in a crowdsourcing system.It may also have security problems compromised by attackers.Here,we propose a scheme,named dTEE,for building a platform for providing distributed trusted computing by leveraging TEEs.The platform is used as an infrastructure of trusted computations for blockchain-based crowdsourcing systems,especially to securely evaluate data quality and manage remuneration:these operations are handled by a TEE group.First,dTEE uses a public blockchain with smart contracts to manage TEEs without reliance on any trusted third parties.Second,to update TEE registration information and rule out zombie TEEs,dTEE uses a reporting mechanism.To attract TEE owners to join in and provide service of trusted computations,it uses a fair monetary incentive mechanism.Third,to account for malicious attackers,we design a model with Byzantine fault tolerance,not limited to a crash-failure model.Finally,we conduct an extensive evaluation of our design on a local cluster.The results show that dTEE finishes evaluating 10,000 images within one minute and achieves about 65 tps throughput when evaluating Sudoku solution data with collective signatures both in a group of 120 TEEs.
