Privacy-Preserving Substring Search on Multi-Source Encrypted Gene Data

Substring searching on gene sequence data is widely used for analyzing the association between a list of gene mutations and a specific disease. As substring search usually has a high computational cost, deploying it in the cloud has become a popular solution. Moreover, the cloud allows easier data s...
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Autor*in:	Shiyue Qin [verfasserIn] Fucai Zhou [verfasserIn] Zongye Zhang [verfasserIn] Zifeng Xu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Composite order bilinear map data privacy gene data substring search

Übergeordnetes Werk:	In: IEEE Access - IEEE, 2014, 8(2020), Seite 50472-50484
Übergeordnetes Werk:	volume:8 ; year:2020 ; pages:50472-50484

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1109/ACCESS.2020.2980375

Katalog-ID:	DOAJ007198469

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spelling	10.1109/ACCESS.2020.2980375 doi (DE-627)DOAJ007198469 (DE-599)DOAJ9a7b957b8f684ff29da413d737391e8d DE-627 ger DE-627 rakwb eng TK1-9971 Shiyue Qin verfasserin aut Privacy-Preserving Substring Search on Multi-Source Encrypted Gene Data 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Substring searching on gene sequence data is widely used for analyzing the association between a list of gene mutations and a specific disease. As substring search usually has a high computational cost, deploying it in the cloud has become a popular solution. Moreover, the cloud allows easier data sharing among medical organizations. Since the gene data contains private information, medical organizations usually outsource encrypted gene data to the cloud and selectively share with others. Most existing solutions for the privacy-preserving substring search problem are based on searchable encryption. However, they mainly focus on single-source gene data, not suitable for handling multi-source gene data because of some practical weaknesses. In this paper, we propose a cryptographic scheme that supports privacy-preserving substring search on multi-source encrypted gene data. The cloud can authorize queriers with access control and perform substring searches over the multi-source encrypted gene data for them. Despite the outsourced gene data is encrypted with different keys, but the authorized querier can issue a substring search only uses its own key. We adopt the composite order bilinear map as the primary underlying cryptographic primitive of our scheme. We mainly focus on protecting the privacy of the outsourced gene data and the substring queries, and we provide a security analysis under the honest-but-curious model. We also perform experiments on different datasets and analyze the experimental results in terms of computation cost and communication cost. The analyses show that our scheme is secure and efficient for substring search on multi-source encrypted gene data. Composite order bilinear map data privacy gene data substring search Electrical engineering. Electronics. Nuclear engineering Fucai Zhou verfasserin aut Zongye Zhang verfasserin aut Zifeng Xu verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 50472-50484 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:50472-50484 https://doi.org/10.1109/ACCESS.2020.2980375 kostenfrei https://doaj.org/article/9a7b957b8f684ff29da413d737391e8d kostenfrei https://ieeexplore.ieee.org/document/9034096/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 50472-50484
allfields_unstemmed	10.1109/ACCESS.2020.2980375 doi (DE-627)DOAJ007198469 (DE-599)DOAJ9a7b957b8f684ff29da413d737391e8d DE-627 ger DE-627 rakwb eng TK1-9971 Shiyue Qin verfasserin aut Privacy-Preserving Substring Search on Multi-Source Encrypted Gene Data 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Substring searching on gene sequence data is widely used for analyzing the association between a list of gene mutations and a specific disease. As substring search usually has a high computational cost, deploying it in the cloud has become a popular solution. Moreover, the cloud allows easier data sharing among medical organizations. Since the gene data contains private information, medical organizations usually outsource encrypted gene data to the cloud and selectively share with others. Most existing solutions for the privacy-preserving substring search problem are based on searchable encryption. However, they mainly focus on single-source gene data, not suitable for handling multi-source gene data because of some practical weaknesses. In this paper, we propose a cryptographic scheme that supports privacy-preserving substring search on multi-source encrypted gene data. The cloud can authorize queriers with access control and perform substring searches over the multi-source encrypted gene data for them. Despite the outsourced gene data is encrypted with different keys, but the authorized querier can issue a substring search only uses its own key. We adopt the composite order bilinear map as the primary underlying cryptographic primitive of our scheme. We mainly focus on protecting the privacy of the outsourced gene data and the substring queries, and we provide a security analysis under the honest-but-curious model. We also perform experiments on different datasets and analyze the experimental results in terms of computation cost and communication cost. The analyses show that our scheme is secure and efficient for substring search on multi-source encrypted gene data. Composite order bilinear map data privacy gene data substring search Electrical engineering. Electronics. Nuclear engineering Fucai Zhou verfasserin aut Zongye Zhang verfasserin aut Zifeng Xu verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 50472-50484 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:50472-50484 https://doi.org/10.1109/ACCESS.2020.2980375 kostenfrei https://doaj.org/article/9a7b957b8f684ff29da413d737391e8d kostenfrei https://ieeexplore.ieee.org/document/9034096/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 50472-50484
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callnumber-first	T - Technology
author	Shiyue Qin
spellingShingle	Shiyue Qin misc TK1-9971 misc Composite order bilinear map misc data privacy misc gene data misc substring search misc Electrical engineering. Electronics. Nuclear engineering Privacy-Preserving Substring Search on Multi-Source Encrypted Gene Data
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topic_title	TK1-9971 Privacy-Preserving Substring Search on Multi-Source Encrypted Gene Data Composite order bilinear map data privacy gene data substring search
topic	misc TK1-9971 misc Composite order bilinear map misc data privacy misc gene data misc substring search misc Electrical engineering. Electronics. Nuclear engineering
topic_unstemmed	misc TK1-9971 misc Composite order bilinear map misc data privacy misc gene data misc substring search misc Electrical engineering. Electronics. Nuclear engineering
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title	Privacy-Preserving Substring Search on Multi-Source Encrypted Gene Data
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title_full	Privacy-Preserving Substring Search on Multi-Source Encrypted Gene Data
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title_sort	privacy-preserving substring search on multi-source encrypted gene data
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title_auth	Privacy-Preserving Substring Search on Multi-Source Encrypted Gene Data
abstract	Substring searching on gene sequence data is widely used for analyzing the association between a list of gene mutations and a specific disease. As substring search usually has a high computational cost, deploying it in the cloud has become a popular solution. Moreover, the cloud allows easier data sharing among medical organizations. Since the gene data contains private information, medical organizations usually outsource encrypted gene data to the cloud and selectively share with others. Most existing solutions for the privacy-preserving substring search problem are based on searchable encryption. However, they mainly focus on single-source gene data, not suitable for handling multi-source gene data because of some practical weaknesses. In this paper, we propose a cryptographic scheme that supports privacy-preserving substring search on multi-source encrypted gene data. The cloud can authorize queriers with access control and perform substring searches over the multi-source encrypted gene data for them. Despite the outsourced gene data is encrypted with different keys, but the authorized querier can issue a substring search only uses its own key. We adopt the composite order bilinear map as the primary underlying cryptographic primitive of our scheme. We mainly focus on protecting the privacy of the outsourced gene data and the substring queries, and we provide a security analysis under the honest-but-curious model. We also perform experiments on different datasets and analyze the experimental results in terms of computation cost and communication cost. The analyses show that our scheme is secure and efficient for substring search on multi-source encrypted gene data.
abstractGer	Substring searching on gene sequence data is widely used for analyzing the association between a list of gene mutations and a specific disease. As substring search usually has a high computational cost, deploying it in the cloud has become a popular solution. Moreover, the cloud allows easier data sharing among medical organizations. Since the gene data contains private information, medical organizations usually outsource encrypted gene data to the cloud and selectively share with others. Most existing solutions for the privacy-preserving substring search problem are based on searchable encryption. However, they mainly focus on single-source gene data, not suitable for handling multi-source gene data because of some practical weaknesses. In this paper, we propose a cryptographic scheme that supports privacy-preserving substring search on multi-source encrypted gene data. The cloud can authorize queriers with access control and perform substring searches over the multi-source encrypted gene data for them. Despite the outsourced gene data is encrypted with different keys, but the authorized querier can issue a substring search only uses its own key. We adopt the composite order bilinear map as the primary underlying cryptographic primitive of our scheme. We mainly focus on protecting the privacy of the outsourced gene data and the substring queries, and we provide a security analysis under the honest-but-curious model. We also perform experiments on different datasets and analyze the experimental results in terms of computation cost and communication cost. The analyses show that our scheme is secure and efficient for substring search on multi-source encrypted gene data.
abstract_unstemmed	Substring searching on gene sequence data is widely used for analyzing the association between a list of gene mutations and a specific disease. As substring search usually has a high computational cost, deploying it in the cloud has become a popular solution. Moreover, the cloud allows easier data sharing among medical organizations. Since the gene data contains private information, medical organizations usually outsource encrypted gene data to the cloud and selectively share with others. Most existing solutions for the privacy-preserving substring search problem are based on searchable encryption. However, they mainly focus on single-source gene data, not suitable for handling multi-source gene data because of some practical weaknesses. In this paper, we propose a cryptographic scheme that supports privacy-preserving substring search on multi-source encrypted gene data. The cloud can authorize queriers with access control and perform substring searches over the multi-source encrypted gene data for them. Despite the outsourced gene data is encrypted with different keys, but the authorized querier can issue a substring search only uses its own key. We adopt the composite order bilinear map as the primary underlying cryptographic primitive of our scheme. We mainly focus on protecting the privacy of the outsourced gene data and the substring queries, and we provide a security analysis under the honest-but-curious model. We also perform experiments on different datasets and analyze the experimental results in terms of computation cost and communication cost. The analyses show that our scheme is secure and efficient for substring search on multi-source encrypted gene data.
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title_short	Privacy-Preserving Substring Search on Multi-Source Encrypted Gene Data
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