With the development of information technology,the online retrieval of remote electronic data has become an important method for investigative agencies to collect evidence.In the current normative documents,the online...With the development of information technology,the online retrieval of remote electronic data has become an important method for investigative agencies to collect evidence.In the current normative documents,the online retrieval of electronic data is positioned as a new type of arbitrary investigative measure.However,study of its actual operation has found that the online retrieval of electronic data does not fully comply with the characteristics of arbitrary investigative measures.The root cause is its inaccurately defined nature due to analogy errors,an emphasis on the authenticity of electronic data at the cost of rights protection,insufficient effectiveness of normative documents to break through the boundaries of law,and superficial inconsistency found in the mechanical comparison with the nature of existing investigative measures causes.The nature of electronic data retrieved online should be defined according to different circumstances.The retrieval of electronic data disclosed on the Internet is an arbitrary investigative measure,and following procedural specifications should be sufficient.When investigators conceal their true identities and enter the cyberspace of the suspected crime through a registered account to extract dynamic electronic data for criminal activities,it is essentially a covert investigation in cyberspace,and they should follow the normative requirements for covert investigations.The retrieval of dynamic electronic data from private spaces is a technical investigative measure and should be implemented in accordance with the technical investigative procedures.Retrieval of remote“non-public electronic data involving privacy”is a mandatory investigative measure,and is essentially a search in the virtual space.Therefore,procedural specifications should be set in accordance with the standards of searching.展开更多
Security insurance is a paramount cloud services issue in the most recent decade. Therefore, Mapreduce which is a programming framework for preparing and creating huge data collections should be optimized and securely...Security insurance is a paramount cloud services issue in the most recent decade. Therefore, Mapreduce which is a programming framework for preparing and creating huge data collections should be optimized and securely implemented. But, conventional operations on ciphertexts were not relevant. So there is a foremost need to enable particular sorts of calculations to be done on encrypted data and additionally optimize data processing at the Map stage. Thereby schemes like (DGHV) and (Gen 10) are presented to address data privacy issue. However private encryption key (DGHV) or key’s parameters (Gen 10) are sent to untrusted cloud server which compromise the information security insurance. Therefore, in this paper we propose an optimized homomorphic scheme (Op_FHE_SHCR) which speed up ciphertext (Rc) retrieval and addresses metadata dynamics and authentication through our secure Anonymiser agent. Additionally for the efficiency of our proposed scheme regarding computation cost and security investigation, we utilize a scalar homomorphic approach instead of applying a blinding probabilistic and polynomial-time calculation which is computationally expensive. Doing as such, we apply an optimized ternary search tries (TST) algorithm in our metadata repository which utilizes Merkle hash tree structure to manage metadata authentication and dynamics.展开更多
The computational complexity of privacy information retrieval protocols is often linearly related to database size.When the database size is large,the efficiency of privacy information retrieval protocols is relativel...The computational complexity of privacy information retrieval protocols is often linearly related to database size.When the database size is large,the efficiency of privacy information retrieval protocols is relatively low.This paper designs an effective privacy information retrieval model based on hybrid fully homomorphic encryption.The assignment method is cleverly used to replace a large number of homomorphic encryption operations.At the same time,the multiplicative homomorphic encryption scheme is first used to deal with the large-scale serialization in the search,and then the fully homomorphic encryption scheme is used to deal with the remaining simple operations.The depth of operations supported by the fully homomorphic scheme no longer depends on the size of the database,but only needs to support the single homomorphic encryption scheme to decrypt the circuit depth.Based on this hybrid homomorphic encryption retrieval model,the efficiency of homomorphic privacy information retrieval model can be greatly improved.展开更多
在定位请求服务中,如何保护用户的位置隐私和位置服务提供商(Localization service provider,LSP)的数据隐私是关系到WiFi指纹定位应用的一个具有挑战性的问题。基于密文域的K-近邻(K-nearest neighbors,KNN)检索,本文提出了一种适用于...在定位请求服务中,如何保护用户的位置隐私和位置服务提供商(Localization service provider,LSP)的数据隐私是关系到WiFi指纹定位应用的一个具有挑战性的问题。基于密文域的K-近邻(K-nearest neighbors,KNN)检索,本文提出了一种适用于三方的定位隐私保护算法,能有效提升对LSP指纹信息隐私的保护强度并降低计算开销。服务器和用户分别完成对指纹信息和定位请求的加密,而第三方则基于加密指纹库和加密定位请求,在隐私状态下完成对用户的位置估计。所提算法把各参考点的位置信息随机嵌入指纹,可避免恶意用户获取各参考点的具体位置;进一步利用布隆滤波器在隐藏接入点信息的情况下,第三方可完成参考点的在线匹配,实现对用户隐私状态下的粗定位,可与定位算法结合降低计算开销。在公共数据集和实验室数据集中,对两种算法的安全、开销和定位性能进行了全面的评估。与同类加密算法比较,在不降低定位精度的情况下,进一步增强了对数据隐私的保护。展开更多
位置隐私和查询内容隐私是LBS兴趣点(point of interest,简称POI)查询服务中需要保护的两个重要内容,同时,在路网连续查询过程中,位置频繁变化会给LBS服务器带来巨大的查询处理负担,如何在保护用户隐私的同时,高效地获取精确查询结果,...位置隐私和查询内容隐私是LBS兴趣点(point of interest,简称POI)查询服务中需要保护的两个重要内容,同时,在路网连续查询过程中,位置频繁变化会给LBS服务器带来巨大的查询处理负担,如何在保护用户隐私的同时,高效地获取精确查询结果,是目前研究的难题.以私有信息检索中除用户自身外其他实体均不可信的思想为基本假设,基于Paillier密码系统的同态特性,提出了无需用户提供真实位置及查询内容的K近邻兴趣点查询方法,实现了对用户位置、查询内容隐私的保护及兴趣点的精确检索;同时,以路网顶点为生成元组织兴趣点分布信息,进一步解决了高强度密码方案在路网连续查询中因用户位置变化频繁导致的实用效率低的问题,减少了用户的查询次数,并能确保查询结果的准确性.最后从准确性、安全性及查询效率方面对本方法进行了分析,并通过仿真实验验证了理论分析结果的正确性.展开更多
基金the phased research result of the Supreme People’s Procuratorate’s procuratorial theory research program“Research on the Governance Problems of the Crime of Aiding Information Network Criminal Activities”(Project Approval Number GJ2023D28)。
文摘With the development of information technology,the online retrieval of remote electronic data has become an important method for investigative agencies to collect evidence.In the current normative documents,the online retrieval of electronic data is positioned as a new type of arbitrary investigative measure.However,study of its actual operation has found that the online retrieval of electronic data does not fully comply with the characteristics of arbitrary investigative measures.The root cause is its inaccurately defined nature due to analogy errors,an emphasis on the authenticity of electronic data at the cost of rights protection,insufficient effectiveness of normative documents to break through the boundaries of law,and superficial inconsistency found in the mechanical comparison with the nature of existing investigative measures causes.The nature of electronic data retrieved online should be defined according to different circumstances.The retrieval of electronic data disclosed on the Internet is an arbitrary investigative measure,and following procedural specifications should be sufficient.When investigators conceal their true identities and enter the cyberspace of the suspected crime through a registered account to extract dynamic electronic data for criminal activities,it is essentially a covert investigation in cyberspace,and they should follow the normative requirements for covert investigations.The retrieval of dynamic electronic data from private spaces is a technical investigative measure and should be implemented in accordance with the technical investigative procedures.Retrieval of remote“non-public electronic data involving privacy”is a mandatory investigative measure,and is essentially a search in the virtual space.Therefore,procedural specifications should be set in accordance with the standards of searching.
文摘Security insurance is a paramount cloud services issue in the most recent decade. Therefore, Mapreduce which is a programming framework for preparing and creating huge data collections should be optimized and securely implemented. But, conventional operations on ciphertexts were not relevant. So there is a foremost need to enable particular sorts of calculations to be done on encrypted data and additionally optimize data processing at the Map stage. Thereby schemes like (DGHV) and (Gen 10) are presented to address data privacy issue. However private encryption key (DGHV) or key’s parameters (Gen 10) are sent to untrusted cloud server which compromise the information security insurance. Therefore, in this paper we propose an optimized homomorphic scheme (Op_FHE_SHCR) which speed up ciphertext (Rc) retrieval and addresses metadata dynamics and authentication through our secure Anonymiser agent. Additionally for the efficiency of our proposed scheme regarding computation cost and security investigation, we utilize a scalar homomorphic approach instead of applying a blinding probabilistic and polynomial-time calculation which is computationally expensive. Doing as such, we apply an optimized ternary search tries (TST) algorithm in our metadata repository which utilizes Merkle hash tree structure to manage metadata authentication and dynamics.
基金sponsored in part by the National Natural Science Foundation of China[Grant-Nos.61902428,6210071026,62202493].
文摘The computational complexity of privacy information retrieval protocols is often linearly related to database size.When the database size is large,the efficiency of privacy information retrieval protocols is relatively low.This paper designs an effective privacy information retrieval model based on hybrid fully homomorphic encryption.The assignment method is cleverly used to replace a large number of homomorphic encryption operations.At the same time,the multiplicative homomorphic encryption scheme is first used to deal with the large-scale serialization in the search,and then the fully homomorphic encryption scheme is used to deal with the remaining simple operations.The depth of operations supported by the fully homomorphic scheme no longer depends on the size of the database,but only needs to support the single homomorphic encryption scheme to decrypt the circuit depth.Based on this hybrid homomorphic encryption retrieval model,the efficiency of homomorphic privacy information retrieval model can be greatly improved.
文摘在定位请求服务中,如何保护用户的位置隐私和位置服务提供商(Localization service provider,LSP)的数据隐私是关系到WiFi指纹定位应用的一个具有挑战性的问题。基于密文域的K-近邻(K-nearest neighbors,KNN)检索,本文提出了一种适用于三方的定位隐私保护算法,能有效提升对LSP指纹信息隐私的保护强度并降低计算开销。服务器和用户分别完成对指纹信息和定位请求的加密,而第三方则基于加密指纹库和加密定位请求,在隐私状态下完成对用户的位置估计。所提算法把各参考点的位置信息随机嵌入指纹,可避免恶意用户获取各参考点的具体位置;进一步利用布隆滤波器在隐藏接入点信息的情况下,第三方可完成参考点的在线匹配,实现对用户隐私状态下的粗定位,可与定位算法结合降低计算开销。在公共数据集和实验室数据集中,对两种算法的安全、开销和定位性能进行了全面的评估。与同类加密算法比较,在不降低定位精度的情况下,进一步增强了对数据隐私的保护。
文摘位置隐私和查询内容隐私是LBS兴趣点(point of interest,简称POI)查询服务中需要保护的两个重要内容,同时,在路网连续查询过程中,位置频繁变化会给LBS服务器带来巨大的查询处理负担,如何在保护用户隐私的同时,高效地获取精确查询结果,是目前研究的难题.以私有信息检索中除用户自身外其他实体均不可信的思想为基本假设,基于Paillier密码系统的同态特性,提出了无需用户提供真实位置及查询内容的K近邻兴趣点查询方法,实现了对用户位置、查询内容隐私的保护及兴趣点的精确检索;同时,以路网顶点为生成元组织兴趣点分布信息,进一步解决了高强度密码方案在路网连续查询中因用户位置变化频繁导致的实用效率低的问题,减少了用户的查询次数,并能确保查询结果的准确性.最后从准确性、安全性及查询效率方面对本方法进行了分析,并通过仿真实验验证了理论分析结果的正确性.
