Demo Data from EDBT 2026 / reviewers in the wild / expert
Hazel Davidson
dblp:352/2359
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Security 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.
| 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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Network management and operations › network configuration
network reconfiguration |
0.7 | 1 | 2023 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | FASHION: Functional and Attack Graph Secured HybrId Optimization of Virtualized NetworksabstractMaintaining 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. | 3 |