The development of the Internet of Things(IoT)calls for a comprehensive in-formation security evaluation framework to quantitatively measure the safety score and risk(S&R)value of the network urgently.In this pape...The development of the Internet of Things(IoT)calls for a comprehensive in-formation security evaluation framework to quantitatively measure the safety score and risk(S&R)value of the network urgently.In this paper,we summarize the architecture and vulnerability in IoT and propose a comprehensive information security evaluation model based on multi-level decomposition feedback.The evaluation model provides an idea for information security evaluation of IoT and guides the security decision maker for dynamic protection.Firstly,we establish an overall evaluation indicator system that includes four primary indicators of threat information,asset,vulnerability,and management,respectively.It also includes eleven secondary indicators of system protection rate,attack detection rate,confidentiality,availability,controllability,identifiability,number of vulnerabilities,vulnerability hazard level,staff organization,enterprise grading and service continuity,respectively.Then,we build the core algorithm to enable the evaluation model,wherein a novel weighting technique is developed and a quantitative method is proposed to measure the S&R value.Moreover,in order to better supervise the performance of the proposed evaluation model,we present four novel indicators includes residual risk,continuous conformity of residual risk,head-to-tail consistency and decrease ratio,respectively.Simulation results show the advantages of the proposed model in the evaluation of information security for IoT.展开更多
With the development of the Internet of Things(Io T), people's lives have become increasingly convenient. It is desirable for smart home(SH) systems to integrate and leverage the enormous information available fro...With the development of the Internet of Things(Io T), people's lives have become increasingly convenient. It is desirable for smart home(SH) systems to integrate and leverage the enormous information available from IoT. Information can be analyzed to learn user intentions and automatically provide the appropriate services. However, existing service recommendation models typically do not consider the services that are unavailable in a user's living environment. In order to address this problem, we propose a series of semantic models for SH devices. These semantic models can be used to infer user intentions. Based on the models, we proposed a service recommendation probability model and an alternative-service recommending algorithm. The algorithm is devoted to providing appropriate alternative services when the desired service is unavailable. The algorithm has been implemented and achieves accuracy higher than traditional Hidden Markov Model(HMM). The maximum accuracy achieved is 68.3%.展开更多
With the skyrocketing development of technologies,there are many issues in information security quantitative evaluation(ISQE)of complex heterogeneous information systems(CHISs).The development of CHIS calls for an ISQ...With the skyrocketing development of technologies,there are many issues in information security quantitative evaluation(ISQE)of complex heterogeneous information systems(CHISs).The development of CHIS calls for an ISQE model based on security-critical components to improve the efficiency of system security evaluation urgently.In this paper,we summarize the implication of critical components in different filed and propose a recognition algorithm of security-critical components based on threat attack tree to support the ISQE process.The evaluation model establishes a framework for ISQE of CHISs that are updated iteratively.Firstly,with the support of asset identification and topology data,we sort the security importance of each asset based on the threat attack tree and obtain the security-critical components(set)of the CHIS.Then,we build the evaluation indicator tree of the evaluation target and propose an ISQE algorithm based on the coefficient of variation to calculate the security quality value of the CHIS.Moreover,we present a novel indicator measurement uncertainty aiming to better supervise the performance of the proposed model.Simulation results show the advantages of the proposed algorithm in the evaluation of CHISs.展开更多
Considering the privacy challenges of secure storage and controlled flow,there is an urgent need to realize a decentralized ecosystem of private blockchain for cyberspace.A collaboration dilemma arises when the partic...Considering the privacy challenges of secure storage and controlled flow,there is an urgent need to realize a decentralized ecosystem of private blockchain for cyberspace.A collaboration dilemma arises when the participants are self-interested and lack feedback of complete information.Traditional blockchains have similar faults,such as trustlessness,single-factor consensus,and heavily distributed ledger,preventing them from adapting to the heterogeneous and resource-constrained Internet of Things.In this paper,we develop the game-theoretic design of a two-sided rating with complete information feedback to stimulate collaborations for private blockchain.The design consists of an evolution strategy of the decision-making network and a computing power network for continuously verifiable proofs.We formulate the optimum rating and resource scheduling problems as two-stage iterative games between participants and leaders.We theoretically prove that the Stackelberg equilibrium exists and the group evolution is stable.Then,we propose a multi-stage evolution consensus with feedback on a block-accounting workload for metadata survival.To continuously validate a block,the metadata of the optimum rating,privacy,and proofs are extracted to store on a lightweight blockchain.Moreover,to increase resource utilization,surplus computing power is scheduled flexibly to enhance security by degrees.Finally,the evaluation results show the validity and efficiency of our model,thereby solving the collaboration dilemma in the private blockchain.展开更多
Quantum networks provide opportunities and challenges across a range of intellectual and technical frontiers,including quantum computation,communication,and others.Unlike traditional communication networks,quantum net...Quantum networks provide opportunities and challenges across a range of intellectual and technical frontiers,including quantum computation,communication,and others.Unlike traditional communication networks,quantum networks utilize quantum bits rather than classical bits to store and transmit information.Quantum key distribution(QKD)relying on the principles of quantum mechanics is a key component in quantum networks and enables two parties to produce a shared random secret key,thereby ensuring the security of data transmission.In this work,we propose a cost-effective quantum downstream access network structure in which each user can get their corresponding key information through terminal distribution.Based on this structure,we demonstrate the first four-end-users quantum downstream access network in continuous variable QKD with a local local oscillator.In contrast to point-to-point continuous variable QKD,the network architecture reevaluates the security of each user and accounts for it accordingly,and each user has a lower tolerance for excess noise as the overall network expands with more users.Hence,the feasibility of the experiment is based on the analysis of the theoretical model,noise analysis,and multiple techniques such as the particle filter and adaptive equalization algorithm used to suppress excess noise.The results show that each user can get a low level of excess noise and can achieve secret key rates of 546 kbps,535 kbps,522.5 kbps,and 512.5 kbps under a transmission distance of 10 km,respectively,with the finite-size block of 1×10~8.This not only verifies the good performance but also provides the foundation for the future multi-user quantum downstream access networks.展开更多
基金This work was supported in part by National Key R&D Program of China under Grant 2019YFB2102400in part by the BUPT Excellent Ph.D.Students Foundation under Grant CX2019117.
文摘The development of the Internet of Things(IoT)calls for a comprehensive in-formation security evaluation framework to quantitatively measure the safety score and risk(S&R)value of the network urgently.In this paper,we summarize the architecture and vulnerability in IoT and propose a comprehensive information security evaluation model based on multi-level decomposition feedback.The evaluation model provides an idea for information security evaluation of IoT and guides the security decision maker for dynamic protection.Firstly,we establish an overall evaluation indicator system that includes four primary indicators of threat information,asset,vulnerability,and management,respectively.It also includes eleven secondary indicators of system protection rate,attack detection rate,confidentiality,availability,controllability,identifiability,number of vulnerabilities,vulnerability hazard level,staff organization,enterprise grading and service continuity,respectively.Then,we build the core algorithm to enable the evaluation model,wherein a novel weighting technique is developed and a quantitative method is proposed to measure the S&R value.Moreover,in order to better supervise the performance of the proposed evaluation model,we present four novel indicators includes residual risk,continuous conformity of residual risk,head-to-tail consistency and decrease ratio,respectively.Simulation results show the advantages of the proposed model in the evaluation of information security for IoT.
基金supported by the National Key Research and Development Program(No.2016YFB0800302)
文摘With the development of the Internet of Things(Io T), people's lives have become increasingly convenient. It is desirable for smart home(SH) systems to integrate and leverage the enormous information available from IoT. Information can be analyzed to learn user intentions and automatically provide the appropriate services. However, existing service recommendation models typically do not consider the services that are unavailable in a user's living environment. In order to address this problem, we propose a series of semantic models for SH devices. These semantic models can be used to infer user intentions. Based on the models, we proposed a service recommendation probability model and an alternative-service recommending algorithm. The algorithm is devoted to providing appropriate alternative services when the desired service is unavailable. The algorithm has been implemented and achieves accuracy higher than traditional Hidden Markov Model(HMM). The maximum accuracy achieved is 68.3%.
基金supported in part by the National Key R&D Program of China under Grant 2019YFB2102400,2016YFF0204001in part by the BUPT Excellent Ph.D.Students Foundation under Grant CX2019117.
文摘With the skyrocketing development of technologies,there are many issues in information security quantitative evaluation(ISQE)of complex heterogeneous information systems(CHISs).The development of CHIS calls for an ISQE model based on security-critical components to improve the efficiency of system security evaluation urgently.In this paper,we summarize the implication of critical components in different filed and propose a recognition algorithm of security-critical components based on threat attack tree to support the ISQE process.The evaluation model establishes a framework for ISQE of CHISs that are updated iteratively.Firstly,with the support of asset identification and topology data,we sort the security importance of each asset based on the threat attack tree and obtain the security-critical components(set)of the CHIS.Then,we build the evaluation indicator tree of the evaluation target and propose an ISQE algorithm based on the coefficient of variation to calculate the security quality value of the CHIS.Moreover,we present a novel indicator measurement uncertainty aiming to better supervise the performance of the proposed model.Simulation results show the advantages of the proposed algorithm in the evaluation of CHISs.
基金supported by the National Key R&D Program of China under Grant No.2021YFB3101904 and the fund under Grant No.2021JCJQQT075。
文摘Considering the privacy challenges of secure storage and controlled flow,there is an urgent need to realize a decentralized ecosystem of private blockchain for cyberspace.A collaboration dilemma arises when the participants are self-interested and lack feedback of complete information.Traditional blockchains have similar faults,such as trustlessness,single-factor consensus,and heavily distributed ledger,preventing them from adapting to the heterogeneous and resource-constrained Internet of Things.In this paper,we develop the game-theoretic design of a two-sided rating with complete information feedback to stimulate collaborations for private blockchain.The design consists of an evolution strategy of the decision-making network and a computing power network for continuously verifiable proofs.We formulate the optimum rating and resource scheduling problems as two-stage iterative games between participants and leaders.We theoretically prove that the Stackelberg equilibrium exists and the group evolution is stable.Then,we propose a multi-stage evolution consensus with feedback on a block-accounting workload for metadata survival.To continuously validate a block,the metadata of the optimum rating,privacy,and proofs are extracted to store on a lightweight blockchain.Moreover,to increase resource utilization,surplus computing power is scheduled flexibly to enhance security by degrees.Finally,the evaluation results show the validity and efficiency of our model,thereby solving the collaboration dilemma in the private blockchain.
基金National Natural Science Foundation of China(62371060,62001041,62201012)State Key Laboratory of Information Photonics and Optical Communications(IPOC2022ZT09).
文摘Quantum networks provide opportunities and challenges across a range of intellectual and technical frontiers,including quantum computation,communication,and others.Unlike traditional communication networks,quantum networks utilize quantum bits rather than classical bits to store and transmit information.Quantum key distribution(QKD)relying on the principles of quantum mechanics is a key component in quantum networks and enables two parties to produce a shared random secret key,thereby ensuring the security of data transmission.In this work,we propose a cost-effective quantum downstream access network structure in which each user can get their corresponding key information through terminal distribution.Based on this structure,we demonstrate the first four-end-users quantum downstream access network in continuous variable QKD with a local local oscillator.In contrast to point-to-point continuous variable QKD,the network architecture reevaluates the security of each user and accounts for it accordingly,and each user has a lower tolerance for excess noise as the overall network expands with more users.Hence,the feasibility of the experiment is based on the analysis of the theoretical model,noise analysis,and multiple techniques such as the particle filter and adaptive equalization algorithm used to suppress excess noise.The results show that each user can get a low level of excess noise and can achieve secret key rates of 546 kbps,535 kbps,522.5 kbps,and 512.5 kbps under a transmission distance of 10 km,respectively,with the finite-size block of 1×10~8.This not only verifies the good performance but also provides the foundation for the future multi-user quantum downstream access networks.
