Q
Qin Liu
Researcher at Hunan University
Publications - 104
Citations - 3579
Qin Liu is an academic researcher from Hunan University. The author has contributed to research in topics: Encryption & Cloud computing. The author has an hindex of 28, co-authored 98 publications receiving 3016 citations. Previous affiliations of Qin Liu include Beijing University of Posts and Telecommunications & Huazhong University of Science and Technology.
Papers
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Proceedings ArticleDOI
Hierarchical attribute-based encryption for fine-grained access control in cloud storage services
Guojun Wang,Qin Liu,Jie Wu +2 more
TL;DR: This paper proposes a scheme to help enterprises to efficiently share confidential data on cloud servers by first combining the HIBE system and the ciphertext-policy attribute-based encryption (CP-ABE) system, and then making a performance-expressivity tradeoff.
Journal ArticleDOI
Hierarchical attribute-based encryption and scalable user revocation for sharing data in cloud servers
TL;DR: This paper proposes a hierarchical attribute- based encryption scheme (HABE) by combining a hierarchical identity-based encryption (HIBE) system and a ciphertext-policy attribute-based encrypted system (CP-ABE), and proposes a scalable revocation scheme by applying proxy re-encryption (PRE) and lazy re-Encryption (LRE) to the HABE scheme, so as to efficiently revoke access rights from users.
Journal ArticleDOI
Time-based proxy re-encryption scheme for secure data sharing in a cloud environment
Qin Liu,Guojun Wang,Jie Wu +2 more
TL;DR: A time-based proxy re-encryption (TimePRE) scheme to allow a user's access right to expire automatically after a predetermined period of time, so that the data owner can be offline in the process of user revocations.
Journal ArticleDOI
Collaborative trajectory privacy preserving scheme in location-based services
TL;DR: The main idea of the scheme is to obfuscate the actual trajectory of a user by issuing fake queries to confuse the LBS adversary, in which trajectory privacy is guaranteed by caching-aware collaboration between users, without the need for any fully trusted entities.
Journal ArticleDOI
Preserving Privacy with Probabilistic Indistinguishability in Weighted Social Networks
TL;DR: A key privacy property, probabilistic indistinguishability, is defined, and a heuristic indistinguishable group anonymization (HIGA) scheme to anonymize a weighted social graph with such a property is proposed.