Z
Ziqiao Zhou
Researcher at University of North Carolina at Chapel Hill
Publications - 15
Citations - 220
Ziqiao Zhou is an academic researcher from University of North Carolina at Chapel Hill. The author has contributed to research in topics: Memory management & Wireless sensor network. The author has an hindex of 6, co-authored 11 publications receiving 185 citations. Previous affiliations of Ziqiao Zhou include Shanghai Jiao Tong University & Microsoft.
Papers
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Proceedings ArticleDOI
A Software Approach to Defeating Side Channels in Last-Level Caches
TL;DR: Cache as mentioned in this paper is a software approach to mitigate access-driven side-channel attacks that leverage last-level caches (LLCs) shared across cores to leak information between security domains (e.g., tenants in a cloud).
Proceedings ArticleDOI
Fingerprint-free tracking with dynamic enhanced field division
TL;DR: The paper presents a fingerprint-free localizing and tracking algorithm, called Enhanced Field Division (EFD), which is used to dynamically divide the field into areas with unique signatures and tracks the target, without any finger-prints.
Proceedings ArticleDOI
EEP2P: An energy-efficient and economy-efficient P2P network protocol
TL;DR: This work presents a framework combining the Time-Of-Use (TOU) pricing model and P2P protocols in smart grid area, and shows that the protocol is both economically efficient and energy efficient for transferring files of various sizes on different systems such as Personal Computers (PCs) and mobile devices.
Journal ArticleDOI
A three-dimensional wireless indoor localization system
TL;DR: A 3-dimensional on-demand indoor localization system (3D-ODIL), which can be fingerprint-free and deployed rapidly in a multistorey building, which consists of two phases, vertical localization and horizontal localization.
Proceedings ArticleDOI
Static Evaluation of Noninterference Using Approximate Model Counting
TL;DR: A static analysis method to measure interference in software by assessing the extent to which different secret inputs are consistent with different attacker-controlled inputs and attacker-observable outputs, which can be measured using a technique called model counting.