In the context of the diversity of smart terminals,the unity of the root of trust becomes complicated,which not only affects the efficiency of trust propagation,but also poses a challenge to the security of the whole ...In the context of the diversity of smart terminals,the unity of the root of trust becomes complicated,which not only affects the efficiency of trust propagation,but also poses a challenge to the security of the whole system.In particular,the solidification of the root of trust in non-volatile memory(NVM)restricts the system’s dynamic updating capability,which is an obvious disadvantage in a rapidly changing security environment.To address this issue,this study proposes a novel approach to generate root security parameters using static random access memory(SRAM)physical unclonable functions(PUFs).SRAM PUFs,as a security primitive,show great potential in lightweight security solutions due to their inherent physical properties,low cost and scalability.However,the stability of SRAM PUFs in harsh environments is a key issue.These environmental conditions include extreme temperatures,high humidity,and strong electromagnetic radiation,all of which can affect the performance of SRAM PUFs.In order to ensure the stability of root safety parameters under these conditions,this study proposes an integrated approach that covers not only the acquisition of entropy sources,but also the implementation of algorithms and configuration management.In addition,this study develops a series of reliability-enhancing algorithms,including adaptive parameter selection,data preprocessing,auxiliary data generation,and error correction,which are essential for improving the performance of SRAM PUFs in harsh environments.Based on these techniques,this study establishes six types of secure parameter generation mechanisms,which not only improve the security of the system,but also enhance its adaptability in variable environments.Through a series of experiments,we verify the effectiveness of the proposed method.Under 10 different environmental conditions,our method is able to achieve full recovery of security data with an error rate of less than 25%,which proves the robustness and reliability of our method.These results not only provide strong evidence for the stability of SRAM PUFs in practical applications,but also provide a new direction for future research in the field of smart terminal security.展开更多
River runoff is affected by many factors, including long-term effects such as climate change that alter rainfall-runoff relationships, and short-term effects related to human intervention(e.g., dam construction, land-...River runoff is affected by many factors, including long-term effects such as climate change that alter rainfall-runoff relationships, and short-term effects related to human intervention(e.g., dam construction, land-use and land-cover change(LUCC)). Discharge from the Yellow River system has been modified in numerous ways over the past century, not only as a result of increased demands for water from agriculture and industry, but also due to hydrological disturbance from LUCC, climate change and the construction of dams. The combined effect of these disturbances may have led to water shortages. Considering that there has been little change in long-term precipitation, dramatic decreases in water discharge may be attributed mainly to human activities, such as water usage, water transportation and dam construction. LUCC may also affect water availability, but the relative contribution of LUCC to changing discharge is unclear. In this study, the impact of LUCC on natural discharge(not including anthropogenic usage) is quantified using an attribution approach based on satellite land cover and discharge data. A retention parameter is used to relate LUCC to changes in discharge. We find that LUCC is the primary factor, and more dominant than climate change, in driving the reduction in discharge during 1956–2012, especially from the mid-1980 s to the end-1990 s. The ratio of each land class to total basin area changed significantly over the study period. Forestland and cropland increased by about 0.58% and 1.41%, respectively, and unused land decreased by 1.16%. Together, these variations resulted in changes in the retention parameter, and runoff generation showed a significant decrease after the mid-1980 s. Our findings highlight the importance of LUCC to runoff generation at the basin scale, and improve our understanding of the influence of LUCC on basin-scale hydrology.展开更多
基金supported by National key Research and Development Program“Security Protection Technology for Critical Information Infrastructure of Distribution Network”(2022YFB3105100).
文摘In the context of the diversity of smart terminals,the unity of the root of trust becomes complicated,which not only affects the efficiency of trust propagation,but also poses a challenge to the security of the whole system.In particular,the solidification of the root of trust in non-volatile memory(NVM)restricts the system’s dynamic updating capability,which is an obvious disadvantage in a rapidly changing security environment.To address this issue,this study proposes a novel approach to generate root security parameters using static random access memory(SRAM)physical unclonable functions(PUFs).SRAM PUFs,as a security primitive,show great potential in lightweight security solutions due to their inherent physical properties,low cost and scalability.However,the stability of SRAM PUFs in harsh environments is a key issue.These environmental conditions include extreme temperatures,high humidity,and strong electromagnetic radiation,all of which can affect the performance of SRAM PUFs.In order to ensure the stability of root safety parameters under these conditions,this study proposes an integrated approach that covers not only the acquisition of entropy sources,but also the implementation of algorithms and configuration management.In addition,this study develops a series of reliability-enhancing algorithms,including adaptive parameter selection,data preprocessing,auxiliary data generation,and error correction,which are essential for improving the performance of SRAM PUFs in harsh environments.Based on these techniques,this study establishes six types of secure parameter generation mechanisms,which not only improve the security of the system,but also enhance its adaptability in variable environments.Through a series of experiments,we verify the effectiveness of the proposed method.Under 10 different environmental conditions,our method is able to achieve full recovery of security data with an error rate of less than 25%,which proves the robustness and reliability of our method.These results not only provide strong evidence for the stability of SRAM PUFs in practical applications,but also provide a new direction for future research in the field of smart terminal security.
基金Under the auspices of Key Program of Chinese Academy of Sciences(No.KJZD-EW-TZ-G10)National Key Research and Development Program of China(No.2016YFA0602704)Breeding Project of Institute of Geographic Sciences and Natural Resources Research,CAS(No.TSYJS04)
文摘River runoff is affected by many factors, including long-term effects such as climate change that alter rainfall-runoff relationships, and short-term effects related to human intervention(e.g., dam construction, land-use and land-cover change(LUCC)). Discharge from the Yellow River system has been modified in numerous ways over the past century, not only as a result of increased demands for water from agriculture and industry, but also due to hydrological disturbance from LUCC, climate change and the construction of dams. The combined effect of these disturbances may have led to water shortages. Considering that there has been little change in long-term precipitation, dramatic decreases in water discharge may be attributed mainly to human activities, such as water usage, water transportation and dam construction. LUCC may also affect water availability, but the relative contribution of LUCC to changing discharge is unclear. In this study, the impact of LUCC on natural discharge(not including anthropogenic usage) is quantified using an attribution approach based on satellite land cover and discharge data. A retention parameter is used to relate LUCC to changes in discharge. We find that LUCC is the primary factor, and more dominant than climate change, in driving the reduction in discharge during 1956–2012, especially from the mid-1980 s to the end-1990 s. The ratio of each land class to total basin area changed significantly over the study period. Forestland and cropland increased by about 0.58% and 1.41%, respectively, and unused land decreased by 1.16%. Together, these variations resulted in changes in the retention parameter, and runoff generation showed a significant decrease after the mid-1980 s. Our findings highlight the importance of LUCC to runoff generation at the basin scale, and improve our understanding of the influence of LUCC on basin-scale hydrology.
