Resilient Control Systems

With its rich set of conceptual, analytical and algorithmic tools, game theory has emerged as providing a versatile and effective framework for addressing issues of resilience, reliability and security (R2S) in networked (control) systems. This keynote will introduce the key elements of this modeling paradigm, and discuss various game-theoretic as well as control-theoretic solution concepts of direct relevance to NR2S. It will cover efficiency of these solutions within a non-cooperative mode of decision-making, and their sensitivity to imprecision in modeling. Further, the role of incentive mechanisms in mitigating or totally eliminating the adverse effects of inefficiency and sensitivity will be discussed. The talk will conclude with some specific examples of security games within the context of cyber-physical systems, with one setting involving multi-vehicle coordination in the presence of one or multiple mobile adversaries attempting to disrupt the communication, and thereby break connectivity, among the vehicles. and of communication networks; control over heterogeneous networks; formation in adversarial environments; estimation and control with limited sensing and transmission; security; and cyber-physical systems. Abstract This presentation will highlight the complexity of the definitions and quantifications of the multidimen-sional vulnerability and resilience of and the risk to cyber-physical infrastructures as systems of systems; and building on the following premises: (1) Cyber-physical infrastructures as system of systems, must be studied, modeled, their effective operation measured with appropriate data collection, and be subjected to a regular process of risk assessment, management, and communication; (2) The above systemic process cannot be achieved without reliance on the centrality of the states of a system and the time frame; (3) The vulnerability and resilience of cyber-physical infrastructure systems of systems are manifestations of their states; (4) The shared and unshared state variables play prominent harmonizing roles among the interdependent subsystems of the cyber-physical infrastructures; (5) The significance of risk of low probability and extreme consequences to the cyber-physical infrastructures ought to be recognized and acted upon; (6) Unantici-pated, undetected, misunderstood or ignored emergent forced changes, whether they originate from within or from outside a system, are likely to affect a multitude of states of that system with potentially adverse consequences. Therefore, it is imperative to be able--through scenario structuring, modeling and risk analysis--to envision, discover, and track emergent forced changes; (7) The vulnerability and resilience of the electric-pow-er grid to cyber and physical emergent forced changes must be studied, modeled, and managed as systems of systems; (8) Prudent risk management calls for a continuous process of measuring the performance of a system, assessing whether observed changes are suf-ficiently significant, developing metrics with which to measure performance, and designing a data-collection mechanism—all are requisites for effective risk modeling, assessment, management, and communication. Abstract Cyber Vision 2025 (CV25) is the Air Force wide cyber-space S&T vision that articulates a path forward in the near-, mid-, and far-term to provide the assured cyber advantage. CV25 forecasts future threats, identifies principled mitigations of vulnerabilities, and indicates opportunities to assure, empower, and sustain resilience of core Air Force missions. It considered both traditional information technology and networks as well as cyber systems embedded in air, space, C2 and ISR mission systems. CV25 was formulated by the Office of the Chief Scientist, in partnership with air staff, MAJCOMs, and key stakeholders. Experts from across government, industry, national laboratories, FFRDCs, and academia helped review and refine the vision. In addition to articulating where the Air Force should lead, follow, or watch in S&T, CV25 also addressed DOTMLPF considerations, especially cyber accessions, training and education, cyber acquisition, and cyber test and evaluation. Abstract Cyber-physical systems are engineered systems that require tight conjoining of and coordination between the computational (discrete) and the physical (continuous). Cyber-physical systems are rapidly penetrating every aspect of our lives, with potential impact on sectors critical to U.S. security and competitiveness, including aerospace, automotive, chemical production, civil infrastructure, energy, finance, healthcare, manufacturing, materials, and transportation. Cybertrust means making computing systems reliable, secure, privacy-preserving, and usable. This talk will look at cyber-physical systems from the lens of Abstract The origins of present data mining (DA) and machine learning (ML) are in the good old System Identification. Many control algorithms depend heavily on deriving models from system data. What is new today? First, the concept of data is changed and data have departed from engineering processes records to all possible data collections including images, sounds, and digital records of all kinds. Next, the amount of data has exploded and collections of millions of records are normal today. Massive data challenges our beliefs about the relations between the data and knowledge. The keynote will present some novel techniques to handle massive datasets. Some basic similarities and differences between neural networks and support vector machines (SVMs) will be presented. More will be said about basic algorithms for SVMs, because they are possibly the most feasible tools for handling massive datasets. Novelty detection by SVMs will be introduced as the possible way to increase the resilience of control systems. Abstract The Department of Energy Cyber Sciences Laboratory (DOE CSL) brings together the scientific research excellence, technical assets, innovation capacity, and intellectual strengths of the DOE/NNSA research community in a focused effort to address the one of the Nation’s greatest national security challenges: the growing cyber threat. The DOE and NNSA CIOs, and the DOE Director of Intelligence have established the DOE CSL to provide a process in support of a coordinated cyber security research agenda. DOE CSL will focus on the protection of NNSA nuclear weapons information, the national electric grid and the DOE/NNSA information enterprise. Attend this luncheon keynote to hear Bob Osborn, Associate Administrator of Information Management and Chief Information Officer of the NNSA, speak about this exciting initiative and An experimental approach to finding deceptive tactics for computer system defense has been developed. This approach tries a variety of tactics against live Internet traffic and observes the responses. These experiments are easiest to do on a honeypot, a computer system designed solely as an attack target. We report on three kinds of experiments with deceptive honeypots: one with packet modifications on packets provided by at-tackers using Snort Inline, one on scripted responses to attacks using Honeyd, and one on a fake Web site. Evidence of responses to deceptions in the form of increased session lengths, and the disappearance of at-tackers was found . Some benefit was obtained by varying the deceptions over time. These results are encour-aging for developing more comprehensive automated deception strategies for defending computer systems, and providing a new experimentation methodology for systematically developing deception plans. An architecture and supporting methods are presented for the implementation of a resilient condition assessment monitoring system that can adaptively accommo-date both cyber and physical anomalies to a monitored system under observation. In particular, the architecture includes three layers: information, assessment, and sensor selection. The information layer estimates probability distributions of process variables based on sensor measurements and assessments of the quality of sensor data. Based on these estimates, the assessment layer then employs probabilistic reasoning methods to assess the plant health. The sensor selection layer selects sensors so that assessments of the plant condition can be made within desired time periods. This paper presents multi-agent based control of networked linear time invariant systems in a noisy environment. The control protocol is based on output information received from other subsystems through the communication channel, which imparts noise to the sensor data. We show that the sum of the mean square state errors between various subsystems converges to a small bound for the multi-agent system. It is apparent that a higher controller gain tends to make the networked system arrive at a consensus faster, while at the same time has the detrimental effect of enlarging the radius of consensus. Resilience of consensus is demonstrated in that the controller maintains collective stability in the event of communication or subsystem failures. This paper presents a novel data quality model as part of a monitoring system that degrades gracefully under attacks on its sensors. The attacker is assumed to manipu-late the sensor data’s variance or mean, with the aim of projecting a false state of the plant. Each sensor’s data is assigned a level of trust, termed data quality, as part of assessing the states of the process variables. For the variance-based attacker, it is established that the concept of data quality is not, in fact, necessary to obtain the best possible assessment. For the mean-based attacker, it is recognized that statistical means are not sufficient to dis-cern data quality. To combat this problem, the so-called method of probing signals is proposed. The efficacy of this method is illustrated by numerical experiments cat-egorized into two parts. The first deals with ind