| 1. |
- Filieri, Antonio, et al.
(författare)
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Software Engineering Meets Control Theory
- 2015
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Ingår i: 2015 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems. - Piscataway, NJ, USA : IEEE Press. - 9780769555676 ; , s. 71-82
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Konferensbidrag (refereegranskat)abstract
- The software engineering community has proposed numerous approaches for making software self-adaptive. These approaches take inspiration from machine learning and control theory, constructing software that monitors and modifies its own behavior to meet goals. Control theory, in particular, has received considerable attention as it represents a general methodology for creating adaptive systems. Control-theoretical software implementations, however, tend to be ad hoc. While such solutions often work in practice, it is difficult to understand and reason about the desired properties and behavior of the resulting adaptive software and its controller. This paper discusses a control design process for software systems which enables automatic analysis and synthesis of a controller that is guaranteed to have the desired properties and behavior. The paper documents the process and illustrates its use in an example that walks through all necessary steps for self-adaptive controller synthesis.
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| 2. |
- Gualandi, Gabriele, et al.
(författare)
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Optimization-based attack against control systems with CUSUM-based anomaly detection
- 2022
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Ingår i: 2022 30th Mediterranean Conference on Control and Automation, MED 2022. - : Institute of Electrical and Electronics Engineers Inc.. - 9781665406734 ; , s. 896-901
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Konferensbidrag (refereegranskat)abstract
- Security attacks on sensor data can deceive a control system and force the physical plant to reach an unwanted and potentially dangerous state. Therefore, attack detection mechanisms are employed in cyber-physical control systems to detect ongoing attacks, the most prominent one being a threshold-based anomaly detection method called CUSUM. Literature defines the maximum impact of stealth attacks as the maximum deviation in the plant's state that an undetectable attack can introduce, and formulates it as an optimization problem. This paper proposes an optimization-based attack with different saturation models, and it investigates how the attack duration significantly affects the impact of the attack on the state of the plant. We show that more dangerous attacks can be discovered when allowing saturation of the control system actuators. The proposed approach is compared with the geometric attack, showing how longer attack durations can lead to a greater impact of the attack while keeping the attack stealthy. © 2022 IEEE.
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| 3. |
- Hoffmann, Henry, et al.
(författare)
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Self-aware computing in the Angstrom processor
- 2012
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Ingår i: Proceedings of the 49th Annual Design Automation Conference. - New York, NY, USA : ACM. - 9781450311991 ; , s. 259-264
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Konferensbidrag (refereegranskat)abstract
- Addressing the challenges of extreme scale computing re- quires holistic design of new programming models and sys- tems that support those models. This paper discusses the Angstrom processor, which is designed to support a new Self-aware Computing (SEEC) model. In SEEC, applications explicitly state goals, while other systems components provide actions that the SEEC runtime system can use to meet those goals. Angstrom supports this model by ex- posing sensors and adaptations that traditionally would be managed independently by hardware. This exposure allows SEEC to coordinate hardware actions with actions specified by other parts of the system, and allows the SEEC runtime system to meet application goals while reducing costs (e.g., power consumption).
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