Abstract
Two trends are transforming transportation systems. First, the increasing complexity of cyber-physical technological advances, such as connected and autonomous mobility, which seamlessly integrate computation, communication, sensing, and control, holds great promise for societal and economic benefits. Second, these tightly coupled cyber-physical interdependencies can be self-defeating as they can pose new exposures to accelerating disruptions in cyber space (i.e., cyber-attacks), raising concerns about the safety, security, and privacy of the transportation system users. In view of these two overlapping trends, bolstering the cyber-physical resilience of transportation systems is crucial.
At its core, achieving cyber-physical resilience entails addressing its two distinguishing characteristics: 1) double-edged cyber-physical couplings, and 2) non-stationary uncertainties of cyber disruptions. The double-edged cyber-physical couplings require explicit investigation of both the bright and dark sides of these couplings, as well as their interactions through multi-agent modeling. For instance, computation (e.g., machine learning) can open doors to both cyber-attack and cyber-defense in autonomous mobility systems, while communication (e.g., connected/networked vehicles and infrastructure) can propagate cyber disruptions despite increasing network redundancy. The second distinguishing feature of cyber-physical resilience is that cyber-physical disruptions lead to non-stationary uncertainties, where adversaries can adapt cyber-attacks to cyber-defense mechanisms over time. This renders the classical resilience methods ineffective as they largely rely on the past experience of similar disruptions to tackle future ones assuming the associated uncertainties are stationary.
Addressing the above two inherent features of cyber-physical resilience requires transcending the conventional and siloed literature on cyber-physical systems and resilience. Current research on cyber-physical systems focuses on leveraging the inner workings of cyber-physical couplings to enhance engineered systems. Yet the inverse problem of tackling external forces (disruptions) exploiting the same couplings to damage these systems is underexplored. To address, this proposed project aims to survey the current research on transportation cyber-physical resilience, find research gaps, and suggest directions for future research. Through comprehensive and systematic investigation of this research area of national priority, this proposed project will lay the foundation for a series of future projects by the PI on the cyber-physical resilience of connected and autonomous transportation systems.
Description
Timeline
Strategic Description / RD&T
Page 17 of the USDOT’s RD&T Plan: Table 3: “Data-Driven System Safety”
Deployment Plan
Expected Outcomes/Impacts
The expected outcome of this research project is the capability enhancement in enhancing transportation safety through bolstering the cyber resilience of connected and autonomous transportation systems.
The anticipated impacts of this research project are 1) societal and economic impacts of bolstering cyber resilience in next generation transportation systems; and 2) enlargement of the pool of trained transportation professionals at the nexus of transportation safety and cyber resilience.
Expected Outputs
The anticipated output of this research project includes a survey paper (for publication in a peer-reviewed journal) on transportation cyber resilience.
TRID
The security and resilience of cyber-physical systems have garnered attentions only in recent years due to the growing frequency and complexity of cyber-attacks caused in part by the increasing digitalization of critical infrastructure systems (e.g., transportation). Despite its rising popularity and national priority, the field is still at its infancy and can significantly benefit from timely and comprehensive reviews of the state-of-the-art. While offering valuable insights, the small number of existing review studies on this topic, which mainly appear in the transportation science and computer science communities, do not comprehensively cover some of the urgent and emerging issues arising in this area. Examples of underexplored aspect of cyber-physical resilience include, but are not limited to, 1) a lifecycle approach (i.e., pre-disruption prevention and post-disruption response and recovery) by focusing on the corresponding lifecycle-based concept of cyber resilience rather than the pre-disruption notion of cybersecurity, 2) a theoretical approach to not only bolster resilience through advanced computation, but also provide theoretical guarantees for the worst-case system performance under certain cyber-attacks, and 3) a system-of-systems approach to prevent cascading failures in interdependent infrastructure systems.
Individuals Involved
| Email |
Name |
Affiliation |
Role |
Position |
| h.noruzoliaee@utrgv.edu |
Noruzoliaee, Mohamadhossein |
University of Texas Rio Grande Valley |
PI |
Faculty - Untenured, Tenure Track |
Budget
Amount of UTC Funds Awarded
$
Total Project Budget (from all funding sources)
$59367.00
Documents
Match Sources
No match sources!
Partners
| Name |
Type |
| University of Texas - Rio Grande Valley |
Deployment & Equity Partner Deployment & Equity Partner |
