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Reima Ishii

dblp:289/9670 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2026
0009-0007-7109-2220ORCID · reported

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

Systems, architecture and hardware · 1 · 1 first-author · 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.

Network and information security
1 paper
Systems and software security · 88% Network security · 12%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Cloud and datacenter computing · 100%

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

TopicWeightPapersLastEvidence papers
Systems and software security › vulnerability discovery › fuzzing
hypervisor fuzzing
1.012026
NecoFuzz: Effective Fuzzing of Nested Virtualization via Fuzz-Harness Virtual Machines · EuroSys 2026
Systems and software security
vulnerability discovery
1.012026
NecoFuzz: Effective Fuzzing of Nested Virtualization via Fuzz-Harness Virtual Machines · EuroSys 2026
Cloud and datacenter computing › virtualization
nested virtualization
1.012026
NecoFuzz: Effective Fuzzing of Nested Virtualization via Fuzz-Harness Virtual Machines · EuroSys 2026
Cloud and datacenter computing
virtualization
1.012026
NecoFuzz: Effective Fuzzing of Nested Virtualization via Fuzz-Harness Virtual Machines · EuroSys 2026
Network security › attack modeling
attack surface
0.312026
NecoFuzz: Effective Fuzzing of Nested Virtualization via Fuzz-Harness Virtual Machines · EuroSys 2026
Systems and software security
operating system security
0.312026
NecoFuzz: Effective Fuzzing of Nested Virtualization via Fuzz-Harness Virtual Machines · EuroSys 2026

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

fuzzing · 2.0fuzz-harness virtual machines · 2.0
YearPublicationVenuePosition
2026 NecoFuzz: Effective Fuzzing of Nested Virtualization via Fuzz-Harness Virtual Machines
abstract
Nested virtualization is now widely supported by major cloud vendors, allowing users to leverage virtualization-based technologies in the cloud. However, supporting nested virtualization significantly increases host hypervisor complexity and introduces a new attack surface in cloud platforms. While many prior studies have explored hypervisor fuzzing, none has explicitly addressed nested virtualization due to the challenge of generating effective virtual machine (VM) instances with a vast state space as fuzzing inputs.
Reima Ishii, Takaaki Fukai, Takahiro Shinagawa
EuroSys1