Cybersecurity Risk Assessment in Connected Intelligent Systems for Designing Resilient Systems

Khattak, Zulqarnain; Qian, Sean; Lin, Gavin

i

Cybersecurity Risk Assessment in Connected Intelligent Systems for Designing Resilient Systems

2024-07-31
By Khattak, Zulqarnain ; Qian, Sean ; Lin, Gavin

File Language:

English

Details

Creators:

Khattak, Zulqarnain ; Qian, Sean ; Lin, Gavin
Corporate Creators:

Carnegie Mellon University ; Carnegie Mellon University. Traffic21 Institute. Safety21 University Transportation Center (UTC)
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
Subject/TRT Terms:
Resource Type:

Tech Report
Geographical Coverage:

Maryland;United States
Edition:

Final Report
Corporate Publisher:

Carnegie Mellon University. Traffic21 Institute. Safety21 University Transportation Center (UTC)
Abstract:

Transportation operation and management systems utilize wired and wireless communications for managing roadways and are at significant risk of cyberattacks. Furthermore, perfect protection from cyberattacks is not realistic. Thus, this research proposes to focus on analyzing the vulnerability of cooperative driving relying on infrastructure-based communication using real-field experimental data collected at the Aberdeen center in Maryland. Multiple cyberattacks and sensor anomalies were emulated using conditions from field experiments to test the consequences of different types of cyberattacks. Long short-term memory with Gaussian mixture (LAGMM) model were utilized to design efficient and effective anomaly detection method for accounting the temporal relations of trajectories, so that anomalous behavior can be detected in real-time and the severe consequences of cyberattack or sensor anomalies can be avoided. The research would help agencies in monitoring the cooperative driving environment for anomalous behavior.
Format:

PDF
Funding:

69A3552344811
Download URL:

https://rosap.ntl.bts.gov/view/dot/77498/dot_77498_DS1.pdf
File Type:

[PDF - 1.12 MB]
Collection(s):

University Transportation Centers
Main Document Checksum:

urn:sha-512:c4f76c7dc16de85368d75bb1686fe9e4aa155509a3f48137111bc00b3ae03da9d3e8abd69d84d68b6e6681bf285786148ead88402d2b341ceec466e5eecc4858

Cybersecurity Risk Assessment in Connected Intelligent Systems for Designing Resilient Systems [supporting dataset]

Dataset

This research is based on the premise that perfect protection from cyberattacks is not realistic. Thus, the proposed research focuses on analyzing the ...

Khattak, Zulqarnain

;

Qian, Sean

File Language:

English

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