Attribute-based encryption with keyword search(ABEKS)is a novel cryptographic paradigm that can be used to implementfine-grained access control and retrieve ciphertexts without disclosing the sensitive information.It i...Attribute-based encryption with keyword search(ABEKS)is a novel cryptographic paradigm that can be used to implementfine-grained access control and retrieve ciphertexts without disclosing the sensitive information.It is a perfect combination of attribute-based encryption(ABE)and public key encryption with keyword search(PEKS).Nevertheless,most of the existing ABEKS schemes have limited search capabilities and only support single or simple conjunctive keyword search.Due to the weak search capability and inaccurate search results,it is difficult to apply these schemes to practical applications.In this paper,an effi-cient expressive ABEKS(EABEKS)scheme supporting unbounded keyword uni-verse over prime-order groups is designed,which supplies the expressive keyword search function supporting the logical connectives of“AND”and“OR”.The proposed scheme not only leads to low computation and communica-tion costs,but also supports unbounded keyword universe.In the standard model,the scheme is proven to be secure under the chosen keyword attack and the cho-sen plaintext attack.The comparison analysis and experimental results show that it has better performance than the existing EABEKS schemes in the storage,com-putation and communication costs.展开更多
对“内涝”和“风险评估”进行关键词检索,以1991—2023年中国知网(CNKI)中文数据库、Web of Science(WOS)核心数据库共2783篇城市内涝风险评估相关文献为基础,采用词频分析、共被引分析、聚类分析等文献计量方法,借助R语言的Bibliomet...对“内涝”和“风险评估”进行关键词检索,以1991—2023年中国知网(CNKI)中文数据库、Web of Science(WOS)核心数据库共2783篇城市内涝风险评估相关文献为基础,采用词频分析、共被引分析、聚类分析等文献计量方法,借助R语言的Bibliometrix包实现数据统计与图谱绘制。结果表明,以内涝风险评估为主题的国内外相关研究近10年呈快速增长趋势,虽然中文文献出现晚于英文文献,但英文文献中,国内研究机构发文量最多;对应国内城市暴雨洪涝灾害发生数量排全球首位,体现出国内城市暴雨内涝灾害影响严重,并已逐渐成为众多学者关注的研究热点;地理信息系统(GIS)是内涝风险评估研究中常用的技术手段,机器学习和遥感技术广泛应用于国际研究,值得国内相关研究学习和借鉴;英文研究热点集中在灾损曲线、脆弱性指标体系和多准则的内涝综合风险分析,而中文研究目前聚焦在基于水文和水力学模型的内涝灾害危险性识别,未来在逐步完善的海绵城市和内涝防治工程建设研究基础上,面向气候变化和韧性城市规划建设的内涝综合风险评估可能会成为新的研究热点。展开更多
基金supported in part by the National Natural Science Foundation of China under Grant No.61772009the Natural Science Foundation of Jiangsu Province under Grant No.BK20181304.
文摘Attribute-based encryption with keyword search(ABEKS)is a novel cryptographic paradigm that can be used to implementfine-grained access control and retrieve ciphertexts without disclosing the sensitive information.It is a perfect combination of attribute-based encryption(ABE)and public key encryption with keyword search(PEKS).Nevertheless,most of the existing ABEKS schemes have limited search capabilities and only support single or simple conjunctive keyword search.Due to the weak search capability and inaccurate search results,it is difficult to apply these schemes to practical applications.In this paper,an effi-cient expressive ABEKS(EABEKS)scheme supporting unbounded keyword uni-verse over prime-order groups is designed,which supplies the expressive keyword search function supporting the logical connectives of“AND”and“OR”.The proposed scheme not only leads to low computation and communica-tion costs,but also supports unbounded keyword universe.In the standard model,the scheme is proven to be secure under the chosen keyword attack and the cho-sen plaintext attack.The comparison analysis and experimental results show that it has better performance than the existing EABEKS schemes in the storage,com-putation and communication costs.
文摘对“内涝”和“风险评估”进行关键词检索,以1991—2023年中国知网(CNKI)中文数据库、Web of Science(WOS)核心数据库共2783篇城市内涝风险评估相关文献为基础,采用词频分析、共被引分析、聚类分析等文献计量方法,借助R语言的Bibliometrix包实现数据统计与图谱绘制。结果表明,以内涝风险评估为主题的国内外相关研究近10年呈快速增长趋势,虽然中文文献出现晚于英文文献,但英文文献中,国内研究机构发文量最多;对应国内城市暴雨洪涝灾害发生数量排全球首位,体现出国内城市暴雨内涝灾害影响严重,并已逐渐成为众多学者关注的研究热点;地理信息系统(GIS)是内涝风险评估研究中常用的技术手段,机器学习和遥感技术广泛应用于国际研究,值得国内相关研究学习和借鉴;英文研究热点集中在灾损曲线、脆弱性指标体系和多准则的内涝综合风险分析,而中文研究目前聚焦在基于水文和水力学模型的内涝灾害危险性识别,未来在逐步完善的海绵城市和内涝防治工程建设研究基础上,面向气候变化和韧性城市规划建设的内涝综合风险评估可能会成为新的研究热点。
