Hui Zhao

Dr. Hui Zhao

orcid

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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3 February 2020 in IEEE Systems Journal
Verified
Journal Article
Open access
YJYu’e Jiang
Yu’e Jiang
Liangmin WangLiangmin Wang
Liangmin Wang
HZHui Zhao
Hui Zhao
HCHsiao-Hwa Chen
Hsiao-Hwa Chen
A device-to-device (D2D) communication link is vulnerable because it is relatively easy to be compromised by adversaries due to the fact that D2D terminals are power limited nodes. This article proposes a covert communication scheme that allows D2D communication links to transmit covert signals (e.g., privacy sensitive data) to ensure a low probability of detection. We allocate transmit powers of cellular and D2D noncovert signals following a fading D2D channel to add the uncertainty in adversary’s background noises. With the help of base station, cooperative power domain nonorthogonal multiple access and successive interference cancellation are used to decode covert signal. Depending on whether a D2D transmitter has the knowledge of adversary’s detection threshold, we derive minimum error probability to measure the covertness performance. Furthermore, we evaluate covert throughput, which is defined as a maximum average transmission rate of covert signal, subject to a given covertness performance.

21 November 2024 in Mathematics
Verified
Journal Article
Open access
PDF file
HZHui Zhao
Hui Zhao
XSXiangmei Song
Xiangmei Song
The Onion Router (Tor), as the most widely used anonymous network, is vulnerable to traffic correlation attacks by powerful passive adversaries, such as Autonomous Systems (AS). AS-level adversaries increase their chances of executing correlation attacks by manipulating the underlying routing, thereby compromising anonymity. Furthermore, these underlying routing detours in the Tor client’s routing inference introduce extra latency. To address this challenge, we propose Toward Resisting AS-level Adversary Correlation Attacks Optimal Anonymous Routing (TOAR). TOAR is a two-stage routing mechanism based on Bayesian optimization within Software Defined Networks (SDN), comprising route search and route forwarding. Specifically, it searches for routes that conform to established policies, avoiding AS that could connect traffic between clients and destinations while maintaining anonymity in the selection of routes that minimize communication costs. To evaluate the anonymity of TOAR, as well as the effectiveness of route searching and the performance of route forwarding, we conduct a detailed analysis and extensive experiments. The analysis and experimental results show that the probability of routing being compromised by correlation attacks is significantly reduced. Compared to classical enumeration-based methods, the success rate of route searching increased by close to 2.5 times, and the forwarding throughput reached 70% of that of the packet transmission. The results show that TOAR effectively improves anonymity while maintaining communication quality, minimizing anonymity loss from AS-level adversaries and reducing high latency from routing detours.