Demo Data from VLDB 2026 / reviewers in the wild / expert
YunKai Song
dblp:428/3836
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0007-5750-1366ORCID · reported
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.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Energy systems and smart grids · 100% |
Topics — the 1 heaviest of 1, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Energy systems and smart grids
power grid security |
1.0 | 1 | 2026 | CCPA via Load Redistribution: Sequential Strategies and Vulnerability Analysis in Power Systems · IEEE Trans. Inf. Forensics Secur. 2026 |
Methods — techniques the papers use, named apart from their topics
mixed integer linear programming · 1.0bi-level optimization · 1.0benders decomposition · 1.0KKT reformulation · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | CCPA via Load Redistribution: Sequential Strategies and Vulnerability Analysis in Power SystemsabstractCoordinated cyber-physical attacks (CCPAs) pose a critical threat to the secure operation of smart power grids. While existing studies often assume simultaneous or sequence-agnostic attack strategies, this paper proposes a sequence-aware CCPA framework that explicitly models the temporal coupling between cyber manipulation and physical sabotage. We enhance the classical load redistribution attack (LRA) by addressing four key limitations: detectability due to infeasible power flows, violation of power balance, omission of post-attack system response, and insensitivity to attack sequencing. Specifically, we formulate two distinct bilevel attack models, namely Cyber-to-Physical (C→P) and Physical-to-Cyber (P→C), and solve them via an exact KKT-based Mixed-Integer Linear Programming (MILP) reformulation and a scalable Benders decomposition (BD) framework. Experiments on IEEE 14-, 57-, and 118-bus systems demonstrate that C→P attacks induce significantly more line overloads than P→C, validating the heightened risk of cyber-initiated cascades. Moreover, our BD approach accurately identifies spatial vulnerability hotspots with high fidelity, even when the physical attack budget is extended fromRp= 1 toRp= 2, confirming the framework’s scalability and practical relevance. The results provide actionable insights for adaptive grid protection against sophisticated, sequential threats. Huihui Huang, YunKai Song, Ruilong Deng, Yangyang Geng |
IEEE Trans. Inf. Forensics Secur. | 2 |