TY - GEN
T1 - Enabling efficient and fine-grained DNA similarity search with access control over encrypted cloud data
AU - Li, Hongwei
AU - Xu, Guowen
AU - Tang, Qiang
AU - Lin, Xiaodong
AU - Shen, Xuemin Sherman
N1 - Funding Information:
Acknowledgment. This work is supported by the National Key R&D Program of China under Grants 2017YFB0802300 and 2017YFB0802000, the National Natural Science Foundation of China under Grants 61772121, 61728102, and 61472065, the Fundamental Research Funds for Chinese Central Universities under Grant ZYGX2015J056.
Publisher Copyright:
© 2018, Springer International Publishing AG, part of Springer Nature.
PY - 2018
Y1 - 2018
N2 - DNA similarity search has proven to be an essential demand in human genomic researches. Since DNA sequences contain many sensitive personal information, the acquisition and dissemination of DNA data have been tightly controlled and restricted by authorities. Although the problem of private DNA similarity query has been an active research issue, the latest research findings are still inadequate in terms of security, functionality and efficiency. In this paper, we propose an Efficient DNA Similarity Search scheme (EDSS) which can achieve fine-grained query and data access control over encrypted cloud data. Our original contributions are fourfold. First, we creatively put forward a private edit distance approximation algorithm to realize the efficient and high accurate DNA similarity query. Second, we classify the whole DNA sequences and design a multiple genes search strategy to achieve complicated logic query such as mixed “AND” and “NO” operations on genes. Third, the proposed scheme can also efficiently support data access control by employing a novel polynomial based design. Finally, security analysis and extensive experiments demonstrate the high security and efficiency of EDSS compared with existing schemes.
AB - DNA similarity search has proven to be an essential demand in human genomic researches. Since DNA sequences contain many sensitive personal information, the acquisition and dissemination of DNA data have been tightly controlled and restricted by authorities. Although the problem of private DNA similarity query has been an active research issue, the latest research findings are still inadequate in terms of security, functionality and efficiency. In this paper, we propose an Efficient DNA Similarity Search scheme (EDSS) which can achieve fine-grained query and data access control over encrypted cloud data. Our original contributions are fourfold. First, we creatively put forward a private edit distance approximation algorithm to realize the efficient and high accurate DNA similarity query. Second, we classify the whole DNA sequences and design a multiple genes search strategy to achieve complicated logic query such as mixed “AND” and “NO” operations on genes. Third, the proposed scheme can also efficiently support data access control by employing a novel polynomial based design. Finally, security analysis and extensive experiments demonstrate the high security and efficiency of EDSS compared with existing schemes.
KW - Access control
KW - Cloud computing
KW - DNA similarity search
KW - Fine-grained query
KW - Privacy-preserving
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U2 - 10.1007/978-3-319-94268-1_20
DO - 10.1007/978-3-319-94268-1_20
M3 - Conference contribution
AN - SCOPUS:85049018345
SN - 9783319942674
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 236
EP - 248
BT - Wireless Algorithms, Systems, and Applications - 13th International Conference, WASA 2018, Proceedings
A2 - Cheng, Wei
A2 - Li, Wei
A2 - Chellappan, Sriram
PB - Springer Verlag
T2 - 13th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2018
Y2 - 20 June 2018 through 22 June 2018
ER -