2026-08-06 ジョージア工科大学
＜関連情報＞
- https://news.research.gatech.edu/2026/08/06/water-systems-face-cyberattacks-georgia-tech-research-points-solutions
- https://dl.acm.org/doi/10.1145/3658644.3690195
猟犬を解き放て！アクティブネットワークデータを用いた現場展開型PLCの自動推論と経験的セキュリティ評価 Release the Hounds! Automated Inference and Empirical Security Evaluation of Field-Deployed PLCs Using Active Network Data
Ryan Pickren,Animesh Chotaray,Frank Li,Saman Zonouz,Raheem Beyah
CCS ’24: Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security Published: 09 December 2024
DOI:https://doi.org/10.1145/3658644.3690195
Abstract
Surveying field-deployed Industrial Control System (ICS) equipment has numerous security applications, including attack-surface management and measuring the adoption of vulnerability patches. However, discovering real-world devices using massive Internet-scale scan datasets is tedious and error-prone. We introduce PLCHound, a novel ICS asset discovery solution designed to automatically reveal elusive ICS devices hiding in network data collected by Internet-scale scanners such as Censys or Shodan. Our solution systematically uncovers indirect evidence of controllers using subtle network-based indicators and temporally-resistant signatures that are often overlooked in prior work. We present PLCHound‘s architecture, experimentally verify its accuracy, and explore the security advantages of enhanced device discovery. We also use PLCHound to perform the largest comprehensive examination of the publicly-reachable population of ICS devices by popular vendors. Our results reveal that the industry-accepted estimations and latest published papers undercount the true number of public devices by up to 37x. We also find that 95.88% of devices expose protocols that cause them to be remotely vulnerable to recent critical CVEs.
