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Prowell, Stacy J

Publications and source records attributed to Prowell, Stacy J.

Tools, Techniques, and Methodologies: A Survey of Digital Forensics for SCADA Systems

Security aspects of SCADA environments and the systems within are increasingly a center of interest to researchers and security professionals. As the rise of sophisticated and nation-state malware targeting such systems flourishes, traditional digital forensics tools struggle to transfer the same capabilities to systems lacking typical volatile memory primitives, monitoring software, and the compatible operating-system primitives necessary for conducting forensic investigations. Even worse, SCADA systems are typically not designed and implemented with security in mind, nor were they purpose-built to monitor and record system data at the granularity associated with traditional IT systems. Rather, these systems are often built to control field devices and drive industrial processes. More succinctly, SCADA systems were not designed with a primary goal of interacting with the digital world. Consequently, forensics investigators well-versed in the world of digital forensics and incident response face an array of challenges that prevent them from conducting effective forensic investigation in environments with vast amounts of critical infrastructure. In order to bring SCADA systems within the reach of the armies of digital forensics professionals and tooling already available, both researchers and practitioners need a guide to the current state-of-the-art techniques, a road-map to the challenges lying on the path forward, and insight into the future directions R&D must move towards. To that end, this paper presents a survey into the literature on digital forensics applied to SCADA systems. We cover not only the challenges to applying digital forensics to SCADA like most other reviews, but also the range of proposed frameworks, methodologies, and actual implementations in literature.

Asmar Awad, Rima↗

Modeling inter-signal arrival times for accurate detection of CAN bus signal injection attacks

Modern vehicles rely on hundreds of on-board electronic control units (ECUs) communicating over in-vehicle networks. As external interfaces to the car control networks (such as the on-board diagnostic (OBD) port, auxiliary media ports, etc.) become common, and vehicle-to-vehicle / vehicle-to-infrastructure technology is in the near future, the attack surface for vehicles grows, exposing control networks to potentially life-critical attacks. This paper addresses the need for securing the CAN bus by detecting anomalous traffic patterns via unusual refresh rates of certain commands. While previous works have identified signal frequency as an important feature for CAN bus intrusion detection, this paper provides the first such algorithm with experiments on five attack scenarios. Our data-driven anomaly detection algorithm requires only five seconds of training time (on normal data) and achieves true positive / false discovery rates of 0.9998/0.00298, respectively (micro-averaged across the five experimental tests).

anomaly detection↗

Computing Legacy Software Behavior to Understand Functionality and Security Properties: An IBM/370 Demonstration

Organizations maintaining mainframe legacy software can benefit from code modernization and incorporation of security capabilities to address the current threat environment. Oak Ridge National Laboratory is developing the Hyperion system to compute the behavior of software as a means to gain understanding of software functionality and security properties. Computation of functionality is critical to revealing security attributes, which are in fact specialized functional behaviors of software. Oak Ridge is collaborating with MITRE Corporation to conduct a demonstration project to compute behavior of legacy IBM Assembly Language code for a federal agency. The ultimate goal is to understand functionality and security vulnerabilities as a basis for code modernization. This paper reports on the first phase, to define functional semantics for IBM Assembly instructions and conduct behavior computation experiments.

reverse engineering↗