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ShuangHe Peng

dblp:235/1527 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · unresolved

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

Security and privacy · 1

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
Cloud and datacenter computing · 60% Embedded and real-time systems · 20% Energy-efficient computing · 20%
Network and information security
1 paper
Hardware security and side channels · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cloud and datacenter computing
cloud security
0.412020
CPU Elasticity to Mitigate Cross-VM Runtime Monitoring · IEEE Trans. Dependable Secur. Comput. 2020
Energy-efficient computing › power management › speed scaling
CPU frequency scaling
0.412020
CPU Elasticity to Mitigate Cross-VM Runtime Monitoring · IEEE Trans. Dependable Secur. Comput. 2020
Cloud and datacenter computing › cloud security
cross-VM side-channel attack
0.412020
CPU Elasticity to Mitigate Cross-VM Runtime Monitoring · IEEE Trans. Dependable Secur. Comput. 2020
Cloud and datacenter computing
resource management
0.412020
CPU Elasticity to Mitigate Cross-VM Runtime Monitoring · IEEE Trans. Dependable Secur. Comput. 2020
Embedded and real-time systems
runtime monitoring
0.412020
CPU Elasticity to Mitigate Cross-VM Runtime Monitoring · IEEE Trans. Dependable Secur. Comput. 2020
Hardware security and side channels › side-channel attack
cache side-channel attacks
0.112020
CPU Elasticity to Mitigate Cross-VM Runtime Monitoring · IEEE Trans. Dependable Secur. Comput. 2020

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

schedule quantum randomization · 0.9frequency scaling · 0.9
YearPublicationVenuePosition
2020 CPU Elasticity to Mitigate Cross-VM Runtime Monitoring
abstract
In this paper, We present a new technique that offers lightweight, general, and elastic protection against Crum (Cross-VM runtime monitoring) attacks. Our protection, called Crease (CPU Resource Elasticity as a Service), enables a VM (called principal) to purchase a higher clock rate from the cloud, through lowering the frequency of a malicious VM (called peer), to support its security-critical operations within a short period. During that period, the weakened peer becomes unable to catch up with the pace of the strengthened principal, therefore losing the capability to effectively collect its sensitive information. In the meantime, our approach can also make up for the performance impact on the peer through refunding schedule credits or service credits, in line with the service level agreement of today's cloud. At the center of our design is the novel application of on-demand frequency scaling and schedule quantum randomization, together with a situation-awareness mechanism that dynamically assesses the security risk posed by the peer. We analyzed the security guarantee of our design, implemented a prototype and evaluated it on a well-known Crum attack (an LLC side-channel attack) and various workloads. Our study shows that Crease is effective at protecting the principal, with only a small impact on the peer's operations.
Zeyu Mi, Haibo Chen 0001, Yinqian Zhang, ShuangHe Peng, XiaoFeng Wang 0001, Michael K. Reiter
IEEE Trans. Dependable Secur. Comput.4