Yves Bieri

dblp:237/0696 · DBLP profile ↗
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2ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · none

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

Computer networks · 1Security and privacy · 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.

Network and information security
1 paper
Network security · 100%
Computer networks
2 papers
Software-defined and programmable networks · 62% Network management and operations · 38%
Software engineering, system software, and programming languages
1 paper
Program analysis · 100%

Topics — the 2 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Software-defined and programmable networks
network function
0.412019
Alembic: Automated Model Inference for Stateful Network Functions · NSDI 2019
Network management and operations › configuration verification
firewall verification
0.212024
Pryde: A Modular Generalizable Workflow for Uncovering Evasion Attacks Against Stateful Firewall Deployments · SP 2024

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

model-guided workflow · 1.5black-box fuzzing · 1.5model inference · 0.8
YearPublicationVenuePosition
2024 Pryde: A Modular Generalizable Workflow for Uncovering Evasion Attacks Against Stateful Firewall Deployments
abstract
Stateful firewalls (SFW) play a critical role in securing our network infrastructure. Incorrect implementation of the intended stateful semantics can lead to evasion opportunities, even if firewall rules are configured correctly. Uncovering these opportunities is challenging due to the (1) black-box and proprietary nature of firewalls; (2) diversity of deployments; and (3) complex stateful semantics. To tackle these challenges, we present Pryde. Pryde uses a modular model-guided workflow that generalizes across black-box firewall implementations and deployment-specific settings to generate evasion attacks. Pryde infers a behavioral model of the stateful firewall in the presence of potentially non-TCP-compliant packet sequences. It uses this model in conjunction with attacker capabilities and victim behavior to synthesize custom evasion attacks. Using Pryde, we identify more than 6,000 unique attacks against 4 popular firewalls and 4 host networking stacks, many of which cannot be uncovered by prior work on censorship circumvention and black-box fuzzing.
Soo-Jin Moon, Milind Srivastava, Yves Bieri, Ruben Martins, Vyas Sekar
SP3
2019 Alembic: Automated Model Inference for Stateful Network Functions
Soo-Jin Moon, Jeffrey Helt, Yves Bieri, Sujata Banerjee, Vyas Sekar, Wenfei Wu, Mihalis Yannakakis, Ying Zhang 0022
NSDI4