Recently,vehicles have experienced a rise in networking and informatization,leading to increased security concerns.As the most widely used automotive bus network,the Controller Area Network(CAN)bus is vulnerable to at...Recently,vehicles have experienced a rise in networking and informatization,leading to increased security concerns.As the most widely used automotive bus network,the Controller Area Network(CAN)bus is vulnerable to attacks,as security was not considered in its original design.This paper proposes SIDuBzip2,a traffic anomaly detection method for the CAN bus based on the bzip2 compression algorithm.The proposed method utilizes the pseudo-periodic characteristics of CAN bus traffic,constructing time series of CAN IDs and calculating the similarity between adjacent time series to identify abnormal traffic.The method consists of three parts:the conversion of CAN ID values to characters,the calculation of similarity based on bzip2 compression,and the optimal solution of model parameters.The experimental results demonstrate that the proposed SIDuBzip2 method effectively detects various attacks,including Denial of Service,replay,basic injection,mixed injection,and suppression attacks.In addition,existing CAN bus traffic anomaly detection methods are compared with the proposed method in terms of performance and delay,demonstrating the feasibility of the proposed method.展开更多
Due to the rapid advancements in network technology,blockchain is being employed for distributed data storage.In the Internet of Things(IoT)scenario,different participants manage multiple blockchains located in differ...Due to the rapid advancements in network technology,blockchain is being employed for distributed data storage.In the Internet of Things(IoT)scenario,different participants manage multiple blockchains located in different trust domains,which has resulted in the extensive development of cross-domain authentication techniques.However,the emergence of many attackers equipped with quantum computers has the potential to launch quantum computing attacks against cross-domain authentication schemes based on traditional cryptography,posing a significant security threat.In response to the aforementioned challenges,our paper demonstrates a post-quantum cross-domain identity authentication scheme to negotiate the session key used in the cross-chain asset exchange process.Firstly,our paper designs the hiding and recovery process of user identity index based on lattice cryptography and introduces the identity-based signature from lattice to construct a post-quantum cross-domain authentication scheme.Secondly,our paper utilizes the hashed time-locked contract to achieves the cross-chain asset exchange of blockchain nodes in different trust domains.Furthermore,the security analysis reduces the security of the identity index and signature to Learning With Errors(LWE)and Short Integer Solution(SIS)assumption,respectively,indicating that our scheme has post-quantum security.Last but not least,through comparison analysis,we display that our scheme is efficient compared with the cross-domain authentication scheme based on traditional cryptography.展开更多
The grain surfaces(film surface and grain boundary)of polycrystalline perovskite films are vulnerable sites in solar cells since they pose a high defect density and initiate the degradation of perovskite absorber.Achi...The grain surfaces(film surface and grain boundary)of polycrystalline perovskite films are vulnerable sites in solar cells since they pose a high defect density and initiate the degradation of perovskite absorber.Achieving simultaneously defect passivation and grain protection from moisture is crucial for the viability of perovskite solar cells.Here,an in situ cross-linked grain encapsulation(CLGE)strategy that improves both device stability and defect passivation is reported.Cross-linkable semiconducting small molecules are mixed into the antisolvent to uniformly form a compact and conducting cross-linked layer over the grain surfaces.This cross-linked coating layer not only passivates trap states and facilitates hole extraction,but also enhances the device stability by preventing moisture diffusion.Using the CLGE strategy,a high power conversion efficiency(PCE)of 22.7%is obtained in 1.55-eV bandgap planar perovskite solar cells.The unencapsulated devices with CLGE exhibit significantly enhanced device stability again moisture and maintain>90%of their initial PCE after shelf storage under ambient condition for over10,000 h.展开更多
Water resources are an indispensable and valuable resource for human survival and development.Water quality predicting plays an important role in the protection and development of water resources.It is difficult to pr...Water resources are an indispensable and valuable resource for human survival and development.Water quality predicting plays an important role in the protection and development of water resources.It is difficult to predictwater quality due to its random and trend changes.Therefore,amethod of predicting water quality which combines Auto Regressive Integrated Moving Average(ARIMA)and clusteringmodelwas proposed in this paper.By taking thewater qualitymonitoring data of a certain river basin as a sample,thewater quality Total Phosphorus(TP)index was selected as the prediction object.Firstly,the sample data was cleaned,stationary analyzed,and white noise analyzed.Secondly,the appropriate parameters were selected according to the Bayesian Information Criterion(BIC)principle,and the trend component characteristics were obtained by using ARIMA to conduct water quality predicting.Thirdly,the relationship between the precipitation and the TP index in themonitoring water field was analyzed by the K-means clusteringmethod,and the random incremental characteristics of precipitation on water quality changes were calculated.Finally,by combining with the trend component characteristics and the random incremental characteristics,the water quality prediction results were calculated.Compared with the ARIMA water quality prediction method,experiments showed that the proposed method has higher accuracy,and its Mean Absolute Error(MAE),Mean Square Error(MSE),and Mean Absolute Percentage Error(MAPE)were respectively reduced by 44.6%,56.8%,and 45.8%.展开更多
At present,water pollution has become an important factor affecting and restricting national and regional economic development.Total phosphorus is one of the main sources of water pollution and eutrophication,so the p...At present,water pollution has become an important factor affecting and restricting national and regional economic development.Total phosphorus is one of the main sources of water pollution and eutrophication,so the prediction of total phosphorus in water quality has good research significance.This paper selects the total phosphorus and turbidity data for analysis by crawling the data of the water quality monitoring platform.By constructing the attribute object mapping relationship,the correlation between the two indicators was analyzed and used to predict the future data.Firstly,the monthly mean and daily mean concentrations of total phosphorus and turbidity outliers were calculated after cleaning,and the correlation between them was analyzed.Secondly,the correlation coefficients of different times and frequencies were used to predict the values for the next five days,and the data trend was predicted by python visualization.Finally,the real value was compared with the predicted value data,and the results showed that the correlation between total phosphorus and turbidity was useful in predicting the water quality.展开更多
文摘Recently,vehicles have experienced a rise in networking and informatization,leading to increased security concerns.As the most widely used automotive bus network,the Controller Area Network(CAN)bus is vulnerable to attacks,as security was not considered in its original design.This paper proposes SIDuBzip2,a traffic anomaly detection method for the CAN bus based on the bzip2 compression algorithm.The proposed method utilizes the pseudo-periodic characteristics of CAN bus traffic,constructing time series of CAN IDs and calculating the similarity between adjacent time series to identify abnormal traffic.The method consists of three parts:the conversion of CAN ID values to characters,the calculation of similarity based on bzip2 compression,and the optimal solution of model parameters.The experimental results demonstrate that the proposed SIDuBzip2 method effectively detects various attacks,including Denial of Service,replay,basic injection,mixed injection,and suppression attacks.In addition,existing CAN bus traffic anomaly detection methods are compared with the proposed method in terms of performance and delay,demonstrating the feasibility of the proposed method.
基金This work was supported by the Defense Industrial Technology Development Program(Grant No.JCKY2021208B036).
文摘Due to the rapid advancements in network technology,blockchain is being employed for distributed data storage.In the Internet of Things(IoT)scenario,different participants manage multiple blockchains located in different trust domains,which has resulted in the extensive development of cross-domain authentication techniques.However,the emergence of many attackers equipped with quantum computers has the potential to launch quantum computing attacks against cross-domain authentication schemes based on traditional cryptography,posing a significant security threat.In response to the aforementioned challenges,our paper demonstrates a post-quantum cross-domain identity authentication scheme to negotiate the session key used in the cross-chain asset exchange process.Firstly,our paper designs the hiding and recovery process of user identity index based on lattice cryptography and introduces the identity-based signature from lattice to construct a post-quantum cross-domain authentication scheme.Secondly,our paper utilizes the hashed time-locked contract to achieves the cross-chain asset exchange of blockchain nodes in different trust domains.Furthermore,the security analysis reduces the security of the identity index and signature to Learning With Errors(LWE)and Short Integer Solution(SIS)assumption,respectively,indicating that our scheme has post-quantum security.Last but not least,through comparison analysis,we display that our scheme is efficient compared with the cross-domain authentication scheme based on traditional cryptography.
基金financially supported by the National Key R&D Program of China(2018YFB1500102,2018YFB2200101)the National Natural Science Foundation of China(61974063,61921005)+3 种基金Natural Science Foundation of Jiangsu Province(BK20190315)the Fundamental Research Funds for the Central Universities(14380168)the Thousand Talent Program for Young Outstanding Scientists in ChinaProgram for Innovative Talents and Entrepreneur in Jiangsu。
文摘The grain surfaces(film surface and grain boundary)of polycrystalline perovskite films are vulnerable sites in solar cells since they pose a high defect density and initiate the degradation of perovskite absorber.Achieving simultaneously defect passivation and grain protection from moisture is crucial for the viability of perovskite solar cells.Here,an in situ cross-linked grain encapsulation(CLGE)strategy that improves both device stability and defect passivation is reported.Cross-linkable semiconducting small molecules are mixed into the antisolvent to uniformly form a compact and conducting cross-linked layer over the grain surfaces.This cross-linked coating layer not only passivates trap states and facilitates hole extraction,but also enhances the device stability by preventing moisture diffusion.Using the CLGE strategy,a high power conversion efficiency(PCE)of 22.7%is obtained in 1.55-eV bandgap planar perovskite solar cells.The unencapsulated devices with CLGE exhibit significantly enhanced device stability again moisture and maintain>90%of their initial PCE after shelf storage under ambient condition for over10,000 h.
基金funded by the National Natural Science Foundation of China(No.51775185),Natural Science Foundation of Hunan Province(2022JJ90013)Scientific Research Fund of Hunan Province Education Department(18C0003)+1 种基金Research project on teaching reform in colleges and universities of Hunan Province Education Department(20190147)Hunan Normal University University-Industry Cooperation.This work is implemented at the 2011 Collaborative Innovation Center for Development and Utilization of Finance and Economics Big Data Property,Universities of Hunan Province,Open project,Grant Number 20181901CRP04.
文摘Water resources are an indispensable and valuable resource for human survival and development.Water quality predicting plays an important role in the protection and development of water resources.It is difficult to predictwater quality due to its random and trend changes.Therefore,amethod of predicting water quality which combines Auto Regressive Integrated Moving Average(ARIMA)and clusteringmodelwas proposed in this paper.By taking thewater qualitymonitoring data of a certain river basin as a sample,thewater quality Total Phosphorus(TP)index was selected as the prediction object.Firstly,the sample data was cleaned,stationary analyzed,and white noise analyzed.Secondly,the appropriate parameters were selected according to the Bayesian Information Criterion(BIC)principle,and the trend component characteristics were obtained by using ARIMA to conduct water quality predicting.Thirdly,the relationship between the precipitation and the TP index in themonitoring water field was analyzed by the K-means clusteringmethod,and the random incremental characteristics of precipitation on water quality changes were calculated.Finally,by combining with the trend component characteristics and the random incremental characteristics,the water quality prediction results were calculated.Compared with the ARIMA water quality prediction method,experiments showed that the proposed method has higher accuracy,and its Mean Absolute Error(MAE),Mean Square Error(MSE),and Mean Absolute Percentage Error(MAPE)were respectively reduced by 44.6%,56.8%,and 45.8%.
基金the National Natural Science Foundation of China(No.51775185)Natural Science Foundation of Hunan Province(No.2022JJ90013)+1 种基金Intelligent Environmental Monitoring Technology Hunan Provincial Joint Training Base for Graduate Students in the Integration of Industry and Education,and Hunan Normal University University-Industry Cooperation.the 2011 Collaborative Innovation Center for Development and Utilization of Finance and Economics Big Data Property,Universities of Hunan Province,Open Project,Grant Number 20181901CRP04.
文摘At present,water pollution has become an important factor affecting and restricting national and regional economic development.Total phosphorus is one of the main sources of water pollution and eutrophication,so the prediction of total phosphorus in water quality has good research significance.This paper selects the total phosphorus and turbidity data for analysis by crawling the data of the water quality monitoring platform.By constructing the attribute object mapping relationship,the correlation between the two indicators was analyzed and used to predict the future data.Firstly,the monthly mean and daily mean concentrations of total phosphorus and turbidity outliers were calculated after cleaning,and the correlation between them was analyzed.Secondly,the correlation coefficients of different times and frequencies were used to predict the values for the next five days,and the data trend was predicted by python visualization.Finally,the real value was compared with the predicted value data,and the results showed that the correlation between total phosphorus and turbidity was useful in predicting the water quality.
