EDBT 2026 Demo / reviewers in the wild / expert
Kandy Phan
dblp:334/3678
· 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.
| Network and information security
1 paper |
Cyber-physical and IoT security · 62% Systems and software security · 38% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cyber-physical and IoT security
industrial control system security |
0.7 | 1 | 2023 | Scaphy: Detecting Modern ICS Attacks by Correlating Behaviors in SCADA and PHYsical · SP 2023 |
Systems and software security › program analysis
dynamic analysis |
0.2 | 1 | 2023 | Scaphy: Detecting Modern ICS Attacks by Correlating Behaviors in SCADA and PHYsical · SP 2023 |
Systems and software security
program analysis |
0.2 | 1 | 2023 | Scaphy: Detecting Modern ICS Attacks by Correlating Behaviors in SCADA and PHYsical · SP 2023 |
Methods — techniques the papers use, named apart from their topics
physical process dependency and impact graph · 0.7API call behavior monitoring · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Scaphy: Detecting Modern ICS Attacks by Correlating Behaviors in SCADA and PHYsicalabstractModern Industrial Control Systems (ICS) attacks evade existing tools by using knowledge of ICS processes to blend their activities with benign Supervisory Control and Data Acquisition (SCADA) operation, causing physical world damages. We present Scaphy to detect ICS attacks in SCADA by leveraging the unique execution phases of SCADA to identify the limited set of legitimate behaviors to control the physical world in different phases, which differentiates from attacker’s activities. For example, it is typical for SCADA to setup ICS device objects during initialization, but anomalous during process-control. To extract unique behaviors of SCADA execution phases, Scaphy first leverages open ICS conventions to generate a novel physical process dependency and impact graph (PDIG) to identify disruptive physical states. Scaphy then uses PDIG to inform a physical process-aware dynamic analysis, whereby code paths of SCADA process-control execution is induced to reveal API call behaviors unique to legitimate process-control phases. Using this established behavior, Scaphy selectively monitors attacker’s physical world-targeted activities that violates legitimate process-control behaviors. We evaluated Scaphy at a U.S. national lab ICS testbed environment. Using diverse ICS deployment scenarios and attacks across 4 ICS industries, Scaphy achieved 95% accuracy & 3.5% false positives (FP), compared to 47.5% accuracy and 25% FP of existing work. We analyze Scaphy’s resilience to futuristic attacks where attacker knows our approach. Moses Ike, Kandy Phan, Keaton Sadoski, Romuald Valme, Wenke Lee |
SP | 2 |