Ethnography: Step By Step

In the last years there has been an increasing interest in the security of process control and SCADA systems. Furthermore, recent computer attacks such as the Stuxnet worm, have shown there are parties with the motivation and resources to effectively attack control systems.While previous work has proposed new security mechanisms for control systems, few of them have explored new and fundamentally different research problems for securing control systems when compared to securing traditional information technology (IT) systems. In particular, the sophistication of new malware attacking control systems--malware including zero-days attacks, rootkits created for control systems, and software signed by trusted certificate authorities--has shown that it is very difficult to prevent and detect these attacks based solely on IT system information.In this paper we show how, by incorporating knowledge of the physical system under control, we are able to detect computer attacks that change the behavior of the targeted control system. By using knowledge of the physical system we are able to focus on the final objective of the attack, and not on the particular mechanisms of how vulnerabilities are exploited, and how the attack is hidden. We analyze the security and safety of our mechanisms by exploring the effects of stealthy attacks, and by ensuring that automatic attack-response mechanisms will not drive the system to an unsafe state.A secondary goal of this paper is to initiate the discussion between control and security practitioners--two areas that have had little interaction in the past. We believe that control engineers can leverage security engineering to design--based on a combination of their best practices--control algorithms that go beyond safety and fault tolerance, and include considerations to survive targeted attacks.

/pdf/attacks-against-process-control-systems-risk-assessment-6p1ukqbc92.pdf

Attacks against process control systems: risk assessment, detection, and response

http://core.ecu.edu/omgt/krosj/appart2.pdf

Models for production planning under uncertainty: A review ☆

A review of cyber security risk assessment methods for SCADA systems

Research in automating the process level of machining operations has been conducted, in both academia and industry, over the past few decades. This work is motivated by a strong belief that research in this area will provide increased productivity, improved part quality, reduced costs, and relaxed machine design constraints. The basis for this belief is twofold. First, machining process automation can be applied to both large batch production environments and small batch jobs. Second, process automation can autonomously tune machine parameters (feed, speed, depth of cut, etc.) on-line and off-line to substantially increase the machine tool's performance in terms of part tolerances and surface finish, operation cycle time, etc. Process automation holds the promise of bridging the gap between product design and process planning, while reaching beyond the capability of a human operator. The success of manufacturing process automation hinges primarily on the effectiveness of the process monitoring and control systems. This paper discusses the evolution of machining process monitoring and control technologies and conducts an in-depth review of the state-of-the-art of these technologies over the past decade. The research in each area is highlighted with experimental and simulation examples. Open architecture software platforms that provide the means to implement process monitoring and control systems are also reviewed. The impact, industrial realization, and future trends of machining process monitoring and control technologies are also discussed.

Machining Process Monitoring and Control: The State-of-the-Art

The growing dependence of critical infrastructures and industrial automation on interconnected physical and cyber-based control systems has resulted in a growing and previously unforeseen cyber security threat to supervisory control and data acquisition (SCADA) and distributed control systems (DCSs). It is critical that engineers and managers understand these issues and know how to locate the information they need. This paper provides a broad overview of cyber security and risk assessment for SCADA and DCS, introduces the main industry organizations and government groups working in this area, and gives a comprehensive review of the literature to date. Major concepts related to the risk assessment methods are introduced with references cited for more detail. Included are risk assessment methods such as HHM, IIM, and RFRM which have been applied successfully to SCADA systems with many interdependencies and have highlighted the need for quantifiable metrics. Presented in broad terms is probability risk analysis (PRA) which includes methods such as FTA, ETA, and FEMA. The paper concludes with a general discussion of two recent methods (one based on compromise graphs and one on augmented vulnerability trees) that quantitatively determine the probability of an attack, the impact of the attack, and the reduction in risk associated with a particular countermeasure.

https://informationsecurity.report/Resources/Whitepapers/20f1cd45-fc89-4387-9bb8-a9e0168cb9ab_erw.pdf

Cyber security risk assessment for SCADA and DCS networks

https://louisville.edu/psychology/decaro/lab/publications-2/copy_of_BelllingerDeCaroRalston2015.pdf/at_download/file

Mindfulness, anxiety, and high-stakes mathematics performance in the laboratory and classroom

Quantitatively assessing the vulnerability of critical information systems: A new method for evaluating security enhancements

A major challenge college students face is retaining the knowledge they acquire in their classes, especially in cumulative disciplines such as engineering, where ultimate success depends on long-term retention of foundational content. Cognitive psychologists have recently recommended various techniques educators might use to increase retention. One technique (spaced retrieval practice) involves extending opportunities to retrieve course content beyond a customarily short temporal window following initial learning. Confirming the technique’s utility requires demonstrating that it increases retention in real classroom settings, with commonly encountered educational content, and that gains endure into subsequent semesters. We manipulated spaced versus massed retrieval practice in a precalculus course for engineering students and followed a subset of students who proceeded into a calculus class the following semester. Spacing versus massing was manipulated within- and between-subjects. Within-subjects, students retained spaced content better than massed content in the precalculus course. Between-subjects, students for whom some retrieval practice was spaced, compared to those for whom all practice was massed, performed better on the final exam in the precalculus class and on exams in the calculus class. These findings suggest that spaced retrieval practice can have a meaningful, long-lasting impact on educational outcomes.

Spaced Retrieval Practice Increases College Students’ Short- and Long-Term Retention of Mathematics Knowledge

Principal component analysis (PCA) for process modeling and multivariate statistical techniques for monitoring, fault detection, and diagnosis are becoming more common in published research, but are still underutilized in practice. This paper summarizes an in-depth case study on a chemical process with 20 monitored process variables, one of which reflects product quality. Data from intervals of “good” operation times are used to determine a PCA model, and then data sets from intervals of “bad” operation times are compared to the model to detect the faulty variable and determine those variables responsible for the poor product quality. The analysis is performed using the PLS_Toolbox 2.01 with MATLAB. The methods used are reviewed summarily, and then results are shown based on typical application of the multivariate statistical techniques. An enhancement is made by using confidence limits on the residuals of each variable for fault detection rather than just confidence limits on an overall residual. Results show that the time required for fault detection is reduced. This approach was suggested in the literature, but its efficacy not demonstrated. Finally, ways to more effectively monitor processes and to more promptly detect and diagnose faults when they occur are identified.

Patricia A. Ralston

Papers

Cyber security risk assessment for SCADA and DCS networks

Mindfulness, anxiety, and high-stakes mathematics performance in the laboratory and classroom

Quantitatively assessing the vulnerability of critical information systems: A new method for evaluating security enhancements

Spaced Retrieval Practice Increases College Students’ Short- and Long-Term Retention of Mathematics Knowledge

Computer-based monitoring and fault diagnosis: a chemical process case study