Demo Data from EDBT 2026 / reviewers in the wild / expert
Steve Geist
dblp:23/3947
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1999
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 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 |
Distributed systems · 50% Embedded and real-time systems · 50% | |
| Network and information security
1 paper |
Cyber-physical and IoT security · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Embedded and real-time systems › industrial control systems
distributed control systems |
0.0 | 1 | 1999 | Information Survivability Control Systems · ICSE 1999 |
Distributed systems
fault tolerance |
0.0 | 1 | 1999 | Information Survivability Control Systems · ICSE 1999 |
Cyber-physical and IoT security
critical infrastructure protection |
0.0 | 1 | 1999 | Information Survivability Control Systems · ICSE 1999 |
Methods — techniques the papers use, named apart from their topics
multiple model control · 0.0hierarchical adaptive control · 0.0discrete-state distributed control · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1999 | Information Survivability Control SystemsabstractWe address the dependence of critical infrastructures-including electric power, telecommunications, finance and transportation-on vulnerable information systems. Our approach is based on the notion of control systems. We envision hierarchical, adaptive, multiple model, discrete-state distributed control systems to monitor infrastructure information systems and respond to disruptions (e.g., security attacks) by changing operating modes and design configurations to minimize loss of utility. To explore and evaluate our approach, we have developed a toolkit for building distributed dynamic models of infrastructure information systems. We used this toolkit to build a model of a simple subset of the United States payment system and a control system for this model information system. Kevin J. Sullivan, John C. Knight, Steve Geist |
ICSE | 4 |