The Experts below are selected from a list of 3525 Experts worldwide ranked by ideXlab platform
Ming Xian - One of the best experts on this subject based on the ideXlab platform.
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efficient privacy preserving frequent itemset query over semantically secure Encrypted cloud Database
World Wide Web, 2021Co-Authors: Ming Xian, Udaya ParampalliAbstract:In recent years, more users tend to use data mining as a service (DMaaS) provided by cloud service providers. However, while enjoying the convenient pay-per-use mode and powerful capacity of cloud computing, users are also threatened by the potential risk of privacy leakage. In this paper, we aim to efficiently perform privacy-preserving DMaaS, and focus on frequent itemset mining over Encrypted Database in outsourced cloud environment. Existing work apply different encryption methods to design various privacy-preserving mining solutions. Nevertheless, these approaches either cannot provide sufficient security requirements, or introduce heavy computation costs. Some of them also need users staying on-line to execute computations, which are not practical in real-world applications. In this paper, we propose a novel efficient privacy-preserving frequent itemset query (PPFIQ) scheme using two homomorphic encryptions and ciphertext packing technique. The proposed scheme protects transaction Database with semantic security, preserves mining privacy and resists frequency analysis attacks. Meanwhile, efficiency is guaranteed by inherent parallel computations for packed plaintexts and users could stay off-line during the mining process. We provide formal security analysis and evaluate the performance of our scheme with extensive experiments. The experiment results demonstrate that the proposed scheme can be efficiently implemented on large Databases.
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privacy preserving k nearest neighbor classification over Encrypted Database in outsourced cloud environments
World Wide Web, 2019Co-Authors: Wei Wu, Udaya Parampalli, Ming XianAbstract:To utilize the cost-saving advantages of the cloud computing paradigm, individuals and enterprises increasingly resort to outsource their Databases and data operations to cloud servers. However such solutions come with the risk of violating the privacy of users. To protect privacy, the outsourced Databases are usually Encrypted, making it difficult to run queries and other data mining tasks without decrypting the data first. Conventional encryption methods are either incapable of supporting such operations or computationally expensive to do so. In this paper, we aim to efficiently support computations over Encrypted cloud Databases, particularly focusing on privacy preserving k-nearest neighbor classification. The proposed scheme efficiently protects Database security, key confidentiality of the data owner, query privacy and data access patterns. We analyze the cost of our proposed scheme and evaluate the performance through extensive experiments using both synthetic and real Databases.
Udaya Parampalli - One of the best experts on this subject based on the ideXlab platform.
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efficient privacy preserving frequent itemset query over semantically secure Encrypted cloud Database
World Wide Web, 2021Co-Authors: Ming Xian, Udaya ParampalliAbstract:In recent years, more users tend to use data mining as a service (DMaaS) provided by cloud service providers. However, while enjoying the convenient pay-per-use mode and powerful capacity of cloud computing, users are also threatened by the potential risk of privacy leakage. In this paper, we aim to efficiently perform privacy-preserving DMaaS, and focus on frequent itemset mining over Encrypted Database in outsourced cloud environment. Existing work apply different encryption methods to design various privacy-preserving mining solutions. Nevertheless, these approaches either cannot provide sufficient security requirements, or introduce heavy computation costs. Some of them also need users staying on-line to execute computations, which are not practical in real-world applications. In this paper, we propose a novel efficient privacy-preserving frequent itemset query (PPFIQ) scheme using two homomorphic encryptions and ciphertext packing technique. The proposed scheme protects transaction Database with semantic security, preserves mining privacy and resists frequency analysis attacks. Meanwhile, efficiency is guaranteed by inherent parallel computations for packed plaintexts and users could stay off-line during the mining process. We provide formal security analysis and evaluate the performance of our scheme with extensive experiments. The experiment results demonstrate that the proposed scheme can be efficiently implemented on large Databases.
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privacy preserving k nearest neighbor classification over Encrypted Database in outsourced cloud environments
World Wide Web, 2019Co-Authors: Wei Wu, Udaya Parampalli, Ming XianAbstract:To utilize the cost-saving advantages of the cloud computing paradigm, individuals and enterprises increasingly resort to outsource their Databases and data operations to cloud servers. However such solutions come with the risk of violating the privacy of users. To protect privacy, the outsourced Databases are usually Encrypted, making it difficult to run queries and other data mining tasks without decrypting the data first. Conventional encryption methods are either incapable of supporting such operations or computationally expensive to do so. In this paper, we aim to efficiently support computations over Encrypted cloud Databases, particularly focusing on privacy preserving k-nearest neighbor classification. The proposed scheme efficiently protects Database security, key confidentiality of the data owner, query privacy and data access patterns. We analyze the cost of our proposed scheme and evaluate the performance through extensive experiments using both synthetic and real Databases.
Joseph K Liu - One of the best experts on this subject based on the ideXlab platform.
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building a dynamic searchable Encrypted medical Database for multi client
Information Sciences, 2020Co-Authors: Joseph K Liu, Cong Zuo, Peng ZhangAbstract:Abstract E-medical record is an emerging health information exchange model based on cloud computing. As cloud computing allows companies and individuals to outsource their data and computation, the medical data is always stored at a third party such as cloud, which brings a variety of risks, such as data leakage to the untrusted cloud server, unauthorized access or modification operations. To assure the confidentiality of the data, the data owner needs to encrypt the sensitive data before uploading to the third party. Yet, issues like Encrypted data search, flexible access and control on sensitive data have also remained the most significant challenges. In this paper, we investigate a novel searchable Encrypted e-medical framework for multi-client which provides both confidentiality and searchability. Different from previous privacy protecting works in secure data outsourcing, we focus on providing a fine-grained access control Encrypted data search scheme including clients and data. Our scheme also enables secure data update of the Encrypted Database by leveraging a secure dynamic searchable encryption. Furthermore, we implement the proposed scheme based on some existed cryptography library, and conduct several experiments on a selected dataset to evaluate its performance. The results demonstrate that our scheme provides a balance between security and efficiency.
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an Encrypted Database with enforced access control and blockchain validation
International Conference on Information Security and Cryptology, 2018Co-Authors: Zhimei Sui, Shangqi Lai, Cong Zuo, Xingliang Yuan, Joseph K Liu, Haifeng QianAbstract:Data privacy and integrity is top of mind for modern data applications. To tackle with the above issue, we propose an Encrypted Database system with access control capabilities and blockchain validation in this paper. Compared to the existing Encrypted Database system, our design proposes a proxy-free architecture, which avoids the need for a trusted proxy for access control. In order to protect the integrity of user data, our system leverages the blockchain technology to realize a tampering protection mechanism. The mechanism ensures that modification logging is compulsory and public-available but hardened. Users can validate and easily detect the tampered data. Finally, we implement a prototype system and conduct evaluations on each component of the proposed system.
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forward secure searchable encryption using key based blocks chain technique
International Conference on Algorithms and Architectures for Parallel Processing, 2018Co-Authors: Yanyu Huang, Joseph K Liu, Zheli Liu, Yu Wei, Donghoon LeeAbstract:Searchable Symmetric Encryption (SSE) has been widely applied in the Encrypted Database for exact queries or even range queries in practice. In spite of it has excellent efficiency and complete functionality, it always suffers from information leakages. Some recent attacks point out that forward privacy is the vital security goal. However, there are only several schemes achieving this security. In this paper, we propose a new flexible forward secure SSE scheme referred to as “FFSSE”, which has the best performance in literature, such as fast search operation, fast token generation and O(1) update complexity. It also supports both add and delete operations in the unique instance. Technically, we exploit a novel “key-based blocks chain” technique based on symmetric cryptographic primitive, which can be deployed in arbitrary index tree structures or key-value structures directly to guarantee forward privacy.
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towards efficient verifiable conjunctive keyword search for large Encrypted Database
European Symposium on Research in Computer Security, 2018Co-Authors: Jianfeng Wang, Joseph K Liu, Xiaofeng Chen, Shifeng Sun, Zhi Hui ZhanAbstract:Searchable Symmetric Encryption (SSE) enables a client to securely outsource large Encrypted Database to a server while supporting efficient keyword search. Most of the existing works are designed against the honest-but-curious server. That is, the server will be curious but execute the protocol in an honest manner. Recently, some researchers presented various verifiable SSE schemes that can resist to the malicious server, where the server may not honestly perform all the query operations. However, they either only considered single-keyword search or cannot handle very large Database. To address this challenge, we propose a new verifiable conjunctive keyword search scheme by leveraging accumulator. Our proposed scheme can not only ensure verifiability of search result even if an empty set is returned but also support efficient conjunctive keyword search with sublinear overhead. Besides, the verification cost of our construction is independent of the size of search result. In addition, we introduce a sample check method for verifying the completeness of search result with a high probability, which can significantly reduce the computation cost on the client side. Security and efficiency evaluation demonstrate that the proposed scheme not only can achieve high security goals but also has a comparable performance.
Tsuyoshi Takagi - One of the best experts on this subject based on the ideXlab platform.
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efficient outsourcing of secure k nearest neighbour query over Encrypted Database
Computers & Security, 2017Co-Authors: Kirill Morozov, Yanjiang Yang, Jianying Zhou, Tsuyoshi TakagiAbstract:Abstract Cloud computing allows a cloud user to outsource her data and the related computation to a cloud service provider to save storage and computational cost. This convenient service has brought a shift from the traditional client–server model to Database as a Service (DBaaS). Although DBaaS relieves the clients from the data management burdens, a significant concern about the data privacy remains. In this work, we focus on outsourcing secure k-nearest neighbour (k-NN) query, and provide the first sublinear solution (with preprocessing) with computational complexity O ( k lg n ( lg 2 n + lg 3 k ) ) . Our construction uses the data structure called kd-tree to achieve the sublinear query complexity. In order to protect data access patterns, garbled circuits are used to simulate Oblivious RAM (ORAM) for accessing data in the kd-tree. Compared with the existing solutions, our scheme imposes only constant overhead on both the data owner and the querying client.
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secure and controllable k nn query over Encrypted cloud data with key confidentiality
Journal of Parallel and Distributed Computing, 2016Co-Authors: Zhiqiu Huang, Youwen Zhu, Tsuyoshi TakagiAbstract:Abstract To enjoy the advantages of cloud service while preserving security and privacy, huge data are increasingly outsourced to cloud in Encrypted form. Unfortunately, most conventional encryption schemes cannot smoothly support Encrypted data analysis and processing. As a significant topic, several schemes have been recently proposed to securely compute k -nearest neighbors ( k -NN) on Encrypted data being outsourced to cloud server (CS). However, most existing k -NN search methods assume query users (QUs) are fully-trusted and know the key of data owner (DO) to encrypt/decrypt outsourced Database. It is not realistic in many situations. In this paper, we propose a new secure k -NN query scheme on Encrypted cloud data. Our approach simultaneously achieves: (1) data privacy against CS: the Encrypted Database can resist potential attacks of CS, (2) key confidentiality against QUs: to avoid the problems caused by key-sharing, QUs cannot learn DO’s key, (3) query privacy against CS and DO: the privacy of query points is preserved as well, (4) query controllability: QUs cannot launch a feasible k -NN query for any new point without approval of DO. We provide theoretical guarantees for security and privacy properties, and show the efficiency of our scheme through extensive experiments.
Donghoon Lee - One of the best experts on this subject based on the ideXlab platform.
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forward secure searchable encryption using key based blocks chain technique
International Conference on Algorithms and Architectures for Parallel Processing, 2018Co-Authors: Yanyu Huang, Joseph K Liu, Zheli Liu, Yu Wei, Donghoon LeeAbstract:Searchable Symmetric Encryption (SSE) has been widely applied in the Encrypted Database for exact queries or even range queries in practice. In spite of it has excellent efficiency and complete functionality, it always suffers from information leakages. Some recent attacks point out that forward privacy is the vital security goal. However, there are only several schemes achieving this security. In this paper, we propose a new flexible forward secure SSE scheme referred to as “FFSSE”, which has the best performance in literature, such as fast search operation, fast token generation and O(1) update complexity. It also supports both add and delete operations in the unique instance. Technically, we exploit a novel “key-based blocks chain” technique based on symmetric cryptographic primitive, which can be deployed in arbitrary index tree structures or key-value structures directly to guarantee forward privacy.
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an efficient keyword searching technique over Encrypted data on smartphone Database
Information Security and Cryptology, 2014Co-Authors: Jongseok Kim, Won Suk Choi, Jinhyung Park, Donghoon LeeAbstract:ABSTRACT We are using our smartphone for our business as well as ours li ves. Thus, user’s privacy data and a company secret are stored at smartphone. By the way, the saved data on smartphone Database can be exposed to a malicous attacker when a malicous app is installed in the smartphone or a user lose his/her smartphone because all data are stored as form of plaintext in the Database. To prevent this disclosure of personal information, we need a Database encryption method. However, if a Database is Encrypted, it causes of declining the performance. For example, when we search specific data in condition with Encrypted Database, we should decrypt all data stored in the da tabase or search sequentially the data we want with accompanying overhead[1].In this paper, we propose an efficient and searchable encryptio n method using variable length bloom filter under limited resource circumstances(e.g., a smartphone). We compare with exi sting searchable symmetric encryption. Also, we implemented the proposed method in android smartphone and evaluated the per formance the proposed method. As a result through the implementation, We can confirm that our method has over a 50% i mprovement in the search speed compared to the simple search method about Encrypted Database and has over a 70% space saving compared to the method of fixed length bloom filter with the same false positive rate.Keywords: Searchable Encryption, Bloom filter, Smartphone
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comprehensive study on security and privacy requirements for retrieval system over Encrypted Database
Information Security and Cryptology, 2012Co-Authors: Hyuna Park, Donghoon Lee, Taikyeong ChungAbstract:Although most proposed security schemes have scrutinized their own security models for protecting different types of threats and attacks, this naturally causes a problem as follows-- if a security analysis tool would fit a certain scheme, it may not be proper to other schemes. In order to address this problem, this paper analyzes how security requirements of each paper could be different by comparing with two schemes: Agrawal et al.'s scheme OPES (Order Preserving Encryption Scheme) and Zdonik et al.'s FCE (Fast Comparison Encryption). Zdonik et al. have formally disproved the security of Agrawal et al.'s scheme OPES. Thereafter, some scholars have wondered whether the OPES can guarantee its applicability in a real world for its insecurity or not. However, the analysis by Zdonik et al. does not have valid objectivity because they used the security model INFO-CPA-DB for their scheme FCE to analyze Agrawal et al.'s scheme OPES, in spite of the differences between two schemes. In order to analyze any scheme correctly and apply it to a real world properly, the analysis tool should be comprehensively standardized. We re-analyze Zdonik et al.'s analysis for OPES and then propose general formalizations of security and privacy for all of the Encrypted retrieval systems. Finally, we recommend the minimum level of security requirements under our formal definitions. Additional considerations should be also supplemented in accordance with the conditions of each system.