With the in-depth application of new technologies such as big data in education fields,the storage and sharing model of student education records data still faces many challenges in terms of privacy protection and eff...With the in-depth application of new technologies such as big data in education fields,the storage and sharing model of student education records data still faces many challenges in terms of privacy protection and efficient transmission.In this paper,we propose a data security storage and sharing scheme based on consortium blockchain,which is a credible search scheme without verification.In our scheme,the implementation of data security storage is using the blockchain and storage server together.In detail,the smart contract provides protection for data keywords,the storage server stores data after data masking,and the blockchain ensures the traceability of query transactions.The need for precise privacy data is achieved by constructing a dictionary.Cryptographic techniques such as AES and RSA are used for encrypted storage of data,keywords,and digital signatures.Security analysis and performance evaluation shows that the availability,high efficiency,and privacy-preserving can be achieved.Meanwhile,this scheme has better robustness compared to other educational records data sharing models.展开更多
无人机辅助联邦学习受限于地面用户计算能力与参与积极性。为此,文中提出博弈优化算法,构建多无人机-多用户协同的区块链联邦学习系统,引入区块链激励机制。采用DBSCAN(Density-Based Spatial Clustering of Applications with Noise)...无人机辅助联邦学习受限于地面用户计算能力与参与积极性。为此,文中提出博弈优化算法,构建多无人机-多用户协同的区块链联邦学习系统,引入区块链激励机制。采用DBSCAN(Density-Based Spatial Clustering of Applications with Noise)算法对用户分簇,无人机激励用户上传数据并本地训练,再由选举出的无人机聚合全局模型。构建Stackelberg博弈数据交易模型,无人机(领导者)制定奖励策略,用户(追随者)确定数据上传方案,分别设计双方效用函数(含奖励、能耗等因素)。通过模拟退火算法优化追随者发射功率,将领导者优化问题拆分为三个子问题,分别用粒子群、理论推导和黄金分割法求解最优无人机位置、CPU频率及奖励分配比,最终求得博弈均衡解。仿真验证,该算法可有效提升数据采集效率与联邦学习性能。展开更多
基金The research work was supported by the National Key Research and Development Plan in China(Grant No.2020YFB1005500)Key Project Plan of Blockchain in Ministry of Education of the People’s Republic of China(Grant No.2020KJ010802)Natural Science Foundation of Beijing Municipality(Grant No.M21034).
文摘With the in-depth application of new technologies such as big data in education fields,the storage and sharing model of student education records data still faces many challenges in terms of privacy protection and efficient transmission.In this paper,we propose a data security storage and sharing scheme based on consortium blockchain,which is a credible search scheme without verification.In our scheme,the implementation of data security storage is using the blockchain and storage server together.In detail,the smart contract provides protection for data keywords,the storage server stores data after data masking,and the blockchain ensures the traceability of query transactions.The need for precise privacy data is achieved by constructing a dictionary.Cryptographic techniques such as AES and RSA are used for encrypted storage of data,keywords,and digital signatures.Security analysis and performance evaluation shows that the availability,high efficiency,and privacy-preserving can be achieved.Meanwhile,this scheme has better robustness compared to other educational records data sharing models.
文摘无人机辅助联邦学习受限于地面用户计算能力与参与积极性。为此,文中提出博弈优化算法,构建多无人机-多用户协同的区块链联邦学习系统,引入区块链激励机制。采用DBSCAN(Density-Based Spatial Clustering of Applications with Noise)算法对用户分簇,无人机激励用户上传数据并本地训练,再由选举出的无人机聚合全局模型。构建Stackelberg博弈数据交易模型,无人机(领导者)制定奖励策略,用户(追随者)确定数据上传方案,分别设计双方效用函数(含奖励、能耗等因素)。通过模拟退火算法优化追随者发射功率,将领导者优化问题拆分为三个子问题,分别用粒子群、理论推导和黄金分割法求解最优无人机位置、CPU频率及奖励分配比,最终求得博弈均衡解。仿真验证,该算法可有效提升数据采集效率与联邦学习性能。
