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Xiaodong Lin
Researcher at University of Guelph
Publications - 337
Citations - 18654
Xiaodong Lin is an academic researcher from University of Guelph. The author has contributed to research in topics: Information privacy & Authentication. The author has an hindex of 61, co-authored 315 publications receiving 15199 citations. Previous affiliations of Xiaodong Lin include University of Ontario Institute of Technology & University of Waterloo.
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Ciphertext Policy Attribute Based Encryption with Efficient Revocation
TL;DR: This paper proposes the ciphertext policy attribute based encryption scheme with efficient revocation which can be proved secure in the standard model and proves the chosen plaintext security of the construction based on Decisional Bilinear Diffie-Hellman (DBDH) assumption in thestandard model.
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MuDA: Multifunctional data aggregation in privacy-preserving smart grid communications
TL;DR: This paper proposes a new multifunctional data aggregation scheme, named MuDA, for privacy-preserving smart grid communications, and demonstrates that MuDA preserves users’ data privacy with acceptable noise rate.
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Security in service-oriented vehicular networks
TL;DR: A novel fast vehicle-to-infrastructure authentication based on a vehicle mobility prediction scheme and an infrastructure-based short-time certificate management scheme are proposed to address two security challenges, minimizing vehicleto- infrastructure authentication latency and distributed public key revocation.
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Securing m-healthcare social networks: challenges, countermeasures and future directions
TL;DR: Following each kind of security and privacy challenge, a series of basic and sophisticated cyber attacks are defined and substantial and promising solutions are given to satisfy the uniqueSecurity and privacy requirements in m-healthcare social networks.
Proceedings ArticleDOI
STAP: A social-tier-assisted packet forwarding protocol for achieving receiver-location privacy preservation in VANETs
TL;DR: The proposed STAP protocol can protect the receiver's location privacy against an active global adversary, and achieve vehicle's conditional privacy preservation as well, and performance evaluation via extensive simulations demonstrates its efficiency in terms of high delivery ratio and low average delay.