Demo Data from EDBT 2026 / reviewers in the wild / expert
Kai Nürnberger
dblp:332/2882
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—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.
| Network and information security
1 paper |
Cyber-physical and IoT security · 56% Network security · 44% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Network security › intrusion detection and prevention
intrusion detection |
0.6 | 1 | 2022 | Poster: INSIDE - Enhancing Network Intrusion Detection in Power Grids with Automated Facility Monitoring · CCS 2022 |
Cyber-physical and IoT security › smart grid security
power grid security |
0.6 | 1 | 2022 | Poster: INSIDE - Enhancing Network Intrusion Detection in Power Grids with Automated Facility Monitoring · CCS 2022 |
Cyber-physical and IoT security
critical infrastructure protection |
0.2 | 1 | 2022 | Poster: INSIDE - Enhancing Network Intrusion Detection in Power Grids with Automated Facility Monitoring · CCS 2022 |
Methods — techniques the papers use, named apart from their topics
network anomaly detection · 0.6automated facility monitoring · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Poster: INSIDE - Enhancing Network Intrusion Detection in Power Grids with Automated Facility MonitoringabstractAdvances in digitalization and networking of power grids have increased the risks of cyberattacks against such critical infrastructures, where the attacks often originate from within the power grid's network. Adequate detection must hence consider both physical access violations and network anomalies to identify the attack's origin. Therefore, we propose INSIDE, combining network intrusion detection with automated facility monitoring to swiftly detect cyberattacks on power grids based on unauthorized access. Besides providing an initial design for INSIDE, we discuss potential use cases illustrating the benefits of such a comprehensive methodology. Martin Serror, Lennart Bader, Martin Henze, Arne Schwarze, Kai Nürnberger |
CCS | 5 |