Quantitative Measurement of Cyber Resilience: Modeling and Experimentation

Cyber resilience is the ability of a system to resist and recover from a cyber attack, thereby restoring the system's functionality. Effective design and development of a cyber resilient system requires experimental methods and tools for quantitative measuring of cyber resilience. This paper describes an experimental method and test bed for obtaining resilience-relevant data as a system (in our case -- a truck) traverses its route, in repeatable, systematic experiments. We model a truck equipped with an autonomous cyber-defense system and which also includes inherent physical resilience features. When attacked by malware, this ensemble of cyber-physical features (i.e., "bonware") strives to resist and recover from the performance degradation caused by the malware's attack. We propose parsimonious mathematical models to aid in quantifying systems' resilience to cyber attacks. Using the models, we identify quantitative characteristics obtainable from experimental data, and show that these characteristics can serve as useful quantitative measures of cyber resilience.Comment: arXiv admin note: text overlap with arXiv:2302.04413, arXiv:2302.0794

Anticipatory Intelligence Resilience Modeling Evaluation of ASPIRE Research Center

The analysis of threats and vulnerabilities in a system is essential in developing resilience strategies to strengthen the system’s ability to adapt and succeed. This report delivers a threat analysis of ASPIRE, a research organization centered on engineering solutions for promoting electric vehicle (EV) adoption. ASPIRE, which is an international network of university research partners and comprised primarily of engineering teams, is focused on developing technology that can be used by industry or governmental partners. The threat of low public buy-in for ASPIRE technology is one of the most significant concerns facing the system. Low adoption rates or public resistance against the company could lessen ASPIRE’s operational success and funding potential. The ASPIRE system has strengths that improve its resilience, as well as vulnerabilities that put the system at greater risk of failing because of this threat. Existing community partnerships strengthen ASPIRE’s resistance to the threat of low public buy-in, but the company could benefit by increasing outreach to key stakeholders. The enthusiasm of ASPIRE employees about the company’s mission helps the company succeed in the face of risks. Additionally, ASPIRE’s varied research focuses allow it to retain its core purpose if one project fails. However, ASPIRE’s ability for threat recovery is potentially lowered because of reliance on public funding; proving worth to funders is challenging if ASPIRE projects fail to achieve public support. The conclusion of this threat analysis is a set of recommendations to improve the system’s resilience potential. These recommendations include the implementation of training and project reporting so that every ASPIRE engineer includes an evaluation of public buy-in potential in their research process. Another recommendation is to increase marketing efforts to improve external perceptions of ASPIRE and address key concerns like product safety and usefulness. The final suggestion is to increase partnerships with industry members and community stakeholders. This builds ASPIRE’s recovery potential by positioning the organization in an advantageous place for future funding

Resilience Modeling of Surface Transportation System in Mixed Traffic Environment

Large-scale natural disasters challenge the resilience of surface transportation system. The objective of this research was to develop a resilience model of surface transportation system in mixed-traffic environment considering varying Connected and Automated Vehicle (CAV) penetration scenarios. As deployment of CAVs are expected to improve traffic operations, a resilience model was developed in this research to evaluate the resilience performance of a transportation system with several CAV penetration levels (0%, 25%, 50%, 75% and 100%) for a given budget and recovery time. The proposed resilience quantification model was applied on a roadway network considering several disaster scenarios. The network capacity in terms of trips at any phase of disaster was compared to the pre-disaster trips to determine the system resilience. The capacity variation and the travel time variation was also estimated. The analysis showed that the resilience phenomenon of the transportation system improved with CAVs in respect of travel time and capacity improvement. The rate of improvement in link travel time for varied CAV penetration was almost identical for different disaster scenarios. For each disaster scenario, the individual link travel time reduced significantly with increased CAV penetration. However, higher penetration of CAVs (i.e., 50% or more), increased the recovery budget requirement. For example, the recovery budget needed for medium and large-scale disasters were 50% and 90% higher respectively compared to the recovery budget needed for a small-scale disaster. These higher costs were primarily needed for repair and replacement of intelligent infrastructure required for CAV

Chapter 5- Lessons from Anticipatory Intelligence: Resilient Pedagogy in the Face of Future Disruptions

The COVID-19 pandemic has disrupted universities across the globe in unprecedented ways, requiring many teaching faculty to reexamine and transform approaches to pedagogy. As higher-education institutions have grappled with various methods of hybrid and remote delivery in an effort to best preserve student instruction through the pandemic, most have fervently looked ahead for a more satisfying “new normal.” Yet this moment of unease and transformation is one of critical opportunity for universities and their teaching faculty. Educators are seeing in vivid form how an unexpected “threat”—in this case, a global health challenge—can profoundly disrupt pedagogy, and the immense adaptive innovation necessary to preserve universities’ most important functions through a sustained period of difficulty. Equally important are lessons concerning the varying degrees of success experienced between institutions based on different levels of proactive planning and the quality of resilience-building strategies

MICROGRID RESILIENCE ANALYSIS SOFTWARE DEVELOPMENT

Military installation microgrids need to be resilient to a variety of potential disruptions (storms, attacks, et cetera). Various metrics for assessing microgrid resilience have been described in literature, and multiple tools for simulating microgrid performance have been constructed; however, it is often left to system owners and maintainers to bring these efforts together to identify and realize effective, efficient improvement strategies. Military microgrid stakeholders have expressed a desire for an integrated, unified platform that provides these multiple capabilities in a coordinated fashion. In support of these endeavors, analysis methods developed by NPS and NAVFAC Expeditionary Warfare Center researchers for measuring microgrid resilience have been integrated into an existing web-based microgrid power flow simulation and distributed energy resource rightsizing software tool. This was achieved by the development of additional functions and methods within the existing software platform code base, and expansion of the application programming interface (API). These API additions enabled access to the new calculation and analysis capabilities, as well as increased control over power flow simulation parameters. These analytical and functional contributions were validated through a design of experiments, including comparison to independently generated data, and factorial analysis.Outstanding ThesisCivilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyApproved for public release. Distribution is unlimited

Objectives and Metrics in Decision Support for Urban Resilience

A holistic framework for the representation of systems resilience in the context of decision support on societal developments at urban, national and global scales is presented with emphasis on the identification of objectives and corresponding metrics of systems resilience performances in the context of technical, social and environmental systems. The proposed framework facilitates for inclusion of specific policies and stakeholder interests that might be relevant as boundary conditions for the ranking of decision alternatives. The application of the proposed framework and metrics is illustrated through a principal example considering an interconnected system comprised by the subsystems infrastructure, governance and environment. It is shown how decision alternatives for the management of urban systems can be related to societal welfare and capacity to cope with disturbances in the long run and thereby facilitating a systems resilience optimization