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Zheliang Xu

dblp:409/6937 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0009-3013-197XORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Processor architecture and microarchitecture · 100%
Network and information security
1 paper
Hardware security and side channels · 62% Systems and software security · 38%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Hardware security and side channels
microarchitectural side channel
0.912025
Oxpecker: Leaking Secrets via Fetch Target Queue · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2025
Processor architecture and microarchitecture
front-end
0.912025
Oxpecker: Leaking Secrets via Fetch Target Queue · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2025
Processor architecture and microarchitecture
instruction fetch
0.912025
Oxpecker: Leaking Secrets via Fetch Target Queue · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2025
Systems and software security
exploitation
0.312025
Oxpecker: Leaking Secrets via Fetch Target Queue · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2025
Systems and software security › code randomization
kernel address space layout randomization
0.312025
Oxpecker: Leaking Secrets via Fetch Target Queue · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2025

Methods — techniques the papers use, named apart from their topics

side-channel analysis · 1.7microarchitectural reverse engineering · 1.7
YearPublicationVenuePosition
2025 Oxpecker: Leaking Secrets via Fetch Target Queue
abstract
Modern processors integrate carefully designed micro-architectural components within the front-end to optimize performance. These components include instruction cache, micro-operation cache, and instruction prefetcher. Through experimentation, we observed that the rate of instruction generation in the fetch unit markedly exceeds the execution rate in the decode unit. However, existing frameworks of processors fail to explain this phenomenon. Consequently, we empirically validate the presence of an optimization feature, referred to as the Fetch Target Queue (FTQ), within the Intel processor. To the best of our knowledge, our study represents the first empirical validation of FTQ across various Intel processors and provides a comprehensive characterization of unrecorded FTQ micro-structural details on Intel processors. Our analysis uncovers overlooked insights that front-end rollbacks caused by the incorrectly ordered instructions or mismatched instruction lengths stored in FTQ introduce specific execution latencies. Based on these observations, we introduce the Oxpecker attack, consisting of two attack primitives, which leverages the FTQ to construct novel side-channel attacks. We construct two distinct exploitation scenarios for each attack primitive to demonstrate the Oxpecker attack’s capability to leak secret control flow information and break Kernel Address Space Layout Randomization.
Shan Li 0008, Zheliang Xu, Haihua Shen, Huawei Li 0001
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.2