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2018-06-11
Tacliad, Francisco, Nguyen, Thuy D., Gondree, Mark.  2017.  DoS Exploitation of Allen-Bradley's Legacy Protocol Through Fuzz Testing. Proceedings of the 3rd Annual Industrial Control System Security Workshop. :24–31.
EtherNet/IP is a TCP/IP-based industrial protocol commonly used in industrial control systems (ICS). TCP/IP connectivity to the outside world has enabled ICS operators to implement more agile practices, but it also has exposed these cyber-physical systems to cyber attacks. Using a custom Scapy-based fuzzer to test for implementation flaws in the EtherNet/IP software of commercial programmable logic controllers (PLC), we uncover a previously unreported denial-of-service (DoS) vulnerability in the Ethernet/IP implementation of the Rockwell Automation/Allen-Bradley MicroLogix 1100 PLC that, if exploited, can cause the PLC to fault. ICS-CERT recently announces this vulnerability in the security advisory ICSA-17-138-03. This paper describes this vulnerability, the development of an EtherNet/IP fuzzer, and an approach to remotely monitor for faults generated when fuzzing.
2017-05-16
Ghaeini, Hamid Reza, Tippenhauer, Nils Ole.  2016.  HAMIDS: Hierarchical Monitoring Intrusion Detection System for Industrial Control Systems. Proceedings of the 2Nd ACM Workshop on Cyber-Physical Systems Security and Privacy. :103–111.

In this paper, we propose a hierarchical monitoring intrusion detection system (HAMIDS) for industrial control systems (ICS). The HAMIDS framework detects the anomalies in both level 0 and level 1 of an industrial control plant. In addition, the framework aggregates the cyber-physical process data in one point for further analysis as part of the intrusion detection process. The novelty of this framework is its ability to detect anomalies that have a distributed impact on the cyber-physical process. The performance of the proposed framework evaluated as part of SWaT security showdown (S3) in which six international teams were invited to test the framework in a real industrial control system. The proposed framework outperformed other proposed academic IDS in term of detection of ICS threats during the S3 event, which was held from July 25-29, 2016 at Singapore University of Technology and Design.