Demo Data from EDBT 2026 / reviewers in the wild / expert
Boseok Park
dblp:243/0155
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2019
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1 · 1 first-author
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% |
Topics — the 2 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 |
0.4 | 1 | 2019 | Intrusion Detection on IoT Services using Event Sampling and Correlation · MobiSys 2019 |
Network security › intrusion detection and prevention › intrusion detection › network intrusion detection
iot intrusion detection |
0.4 | 1 | 2019 | Intrusion Detection on IoT Services using Event Sampling and Correlation · MobiSys 2019 |
Methods — techniques the papers use, named apart from their topics
graph modeling · 0.4event correlation algorithm · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Intrusion Detection on IoT Services using Event Sampling and CorrelationabstractThe IoT services have different types of security frameworks. As a result, it is difficult for security manager or attack response systems to understand the alerts and take appropriate actions. In this paper, we describes the analysis of security methods in the area of IoT and describes a mechanism that analyzes logs generated by IoT devices attacks. We models an event network based on a graph of interconnected logs between network devices and IoT gateways. Moreover, suggests an algorithm that correlate logs into single meaningful messages. Boseok Park |
MobiSys | 1 |