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Timothy Curry

dblp:236/5019 · DBLP profile ↗
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3ranked-venue papers
2as first author
2since 2021 · last 2023
0000-0002-5772-7468ORCID · corroborated

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

Security and privacy · 2 · 1 first-author · 1 since 2021Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Software engineering, systems software and programming languages · 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.

Computer networks
1 paper
Network management and operations · 50% Software-defined and programmable networks · 50%
Network and information security
1 paper
Network security · 100%

Topics — the 1 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Network management and operations › network configuration
network reconfiguration
0.712023
FASHION: Functional and Attack Graph Secured HybrId Optimization of Virtualized Networks · IEEE Trans. Dependable Secur. Comput. 2023

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

probabilistic attack graph · 1.3multicommodity flow · 1.3linear optimization · 1.3
YearPublicationVenuePosition
2023 FASHION: Functional and Attack Graph Secured HybrId Optimization of Virtualized Networks
abstract
Maintaining a resilient computer network is a delicate task with conflicting priorities. Flows should be served while controlling risk due to attackers. Upon publication of a vulnerability, administrators scramble to manually mitigate risk while waiting for a patch. We introduce$\textsc {Fashion}$: a linear optimizer that balances routing flows with the security risk posed by these flows.$\textsc {Fashion}$formalizes routing as a multi-commodity flow problem with side-constraints.$\textsc {Fashion}$formulates security using two approximations of risk in a probabilistic attack graph (Frigault et al. Network Security Metrics 2017).$\textsc {Fashion}$'s output is a set of software-defined networking rules consumable by Frenetic (Foster et al. ICFP 2011). We introduce a topology generation tool that creates data center network instances including flows and vulnerabilities.$\textsc {Fashion}$is executed on instances of up to 600 devices, thousands of flows, and million edge attack graphs. Solve time averages 30 minutes on the largest instances (seconds on the smallest instances). To ensure the security objective is accurate, the output solution is assessed using risk as defined by Frigault et al.$\textsc {Fashion}$allows enterprises to reconfigure their network in response to changes in functionality or security requirements.
Devon Callahan, Timothy Curry, Hazel Davidson, Heytem Zitoun, Benjamin Fuller 0001, Laurent D. Michel
IEEE Trans. Dependable Secur. Comput.2
2022 DUELMIPs: Optimizing SDN Functionality and Security
Timothy Curry, Gabriel De Pace, Benjamin Fuller 0001, Laurent D. Michel, Yan Lindsay Sun
CP1
2019 DOCSDN: Dynamic and Optimal Configuration of Software-Defined Networks
Timothy Curry, Devon Callahan, Benjamin Fuller 0001, Laurent D. Michel
ACISP1