Visible to the public CPS: Breakthrough: Collaborative Research: Track and Fallback: Intrusion Detection to Counteract Carjack Hacks with Fail-Operational FeedbackConflict Detection Enabled

Project Details
Lead PI:Gedare Bloom
Performance Period:10/01/16 - 09/30/19
Institution(s):Howard University
Sponsor(s):National Science Foundation
Award Number:1646317
105 Reads. Placed 463 out of 803 NSF CPS Projects based on total reads on all related artifacts.
Abstract: The security of every vehicle on the road is necessary to ensure the safety of every person on or near roadways, whether a motorist, bicyclist, or pedestrian. Features such as infotainment, telematics, and driver assistance greatly increase the complexity of vehicles: top-of-the-line cars contain over 200 computers and 100 million lines of software code. With rising complexity comes rising costs to ensure safety and security. This project investigates novel methods to improve vehicular security by detecting malicious cyber attacks against a moving automobile and responding to those attacks in a manner that ensures the safety of humans in close proximity to the vehicle. The objective of this project is to protect in-vehicle networks from remote cyber attacks. The method of protection is a distributed in-vehicle network intrusion detection system (IDS) using information flow tracking and sensor data provenance in the cyber domain with novel approaches to address the physical uncertainty and time constraints of an automotive control system. When an intrusion is detected, the IDS triggers a fail-operational mode change to provide graceful degradation of service and initiate recovery without compromising human safety. Specific research aims of this project are to explore the design space of fail-operational IDS for automotive in-vehicle networks, to evaluate security and resiliency of an automobile using a fail-operational IDS, and to generalize fundamentals of a fail-operational IDS to other cyber-physical systems.