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                            Funding & Awards
 Cybersecurity and Safety Challenges in Autonomous Vehicles: Threats Identification and Countermeasures Development
Note:
              This awardee has received supplemental funding. This award detail page includes information about both the original award and supplemental awards.
Award Information
Awardee
              PURDUE UNIVERSITY
Award #
              2017-R2-CX-0001
Funding Category
              Competitive Discretionary
Location
                    WEST LAFAYETTE, IN
Congressional District
              4
Status
              Closed
Funding First Awarded
              2017
Total funding (to date)
              $147,131
Original Solicitation
              NIJ FY17 Graduate Research Fellowship Program in Science, Technology, Engineering and Mathematics
Description of original award (Fiscal Year 2017, $50,000)
Today's autonomous cars, otherwise known as driverless vehicles or self-driving cars, enable the deployment of safety technologies, such as collision warning, automatic emergency braking, and Vehicle-to-Vehicle technologies.
In the near future, these systems in all vehicles will help to achieve zero fatalities, zero injuries, and zero accidents. However, behind the potential of these innovations, there is new challenge on autonomous cars that still need to address: cybersecurity.
Most of autonomous vehicles use wireless signals to exchange information between vehicles about their location, direction, and speed. This collected information can be used to provide safety technologies.
Simultaneously, common communications networks enable autonomous cars to receive and transmit a great deal of information between sensors, actuators, and the electronic control units, provide access for attackers. From this point of view, cybersecurity is considered as new threats to public safety. Thus, the units that governs safety should be protected from malicious attacks, unauthorized access, or dubious activities which could interfere with public safety.
Unfortunately, while previous research efforts have largely considered attack models and detection methodologies of cybersecurity risks, very limited research efforts are known with respect to defense and mitigation technologies and the practical security issues in autonomous vehicles today. A typical automotive electronic control system mainly relies on the followings: sensors; actuators; communication networks; control algorithm. To examine the potential safety concerns associated with electronic sensors and prevent relevant crimes, there are three specific goals in this research: (1) to identify a mathematical model for autonomous vehicles, attacks, and observers; to analyze vulnerabilities of cyberattack via communication networks; to design observers to detect and identify attacks; (2) to develop countermeasures and defense strategies to maintain safety-critical systems (steering, braking, throttle, and power) functional under attacks; (3) to conduct experiments using autonomous robots to demonstrate the reliability and feasibility of the overall proposed study in a practical manner.
In order to achieve these goals, an approach from modern control engineering will be considered to design a robust filter or estimator that generates residuals which are insensitive to noise and uncertainties. Furthermore, three strategies (hybrid mode, multiple sensor fusion, isolation) will be proposed to mitigate the potential harmful consequences due to cyberattacks. Finally, two different types of simulation (SILS, HILS) and field tests will be performed. The proposed technology will impact on the automotive industry; vehicular study in academia; policymakers; criminal justice practitioner.
ca/ncf
Supplemental Award 1 (Fiscal Year 2018, $50,000)
Today's autonomous cars, otherwise known as driverless vehicles or self-driving cars, enable the deployment of safety technologies, such as collision warning, automatic emergency braking, and Vehicle-to-Vehicle technologies.
In the near future, these systems in all vehicles will help to achieve zero fatalities, zero injuries, and zero accidents. However, behind the potential of these innovations, there is new challenge on autonomous cars that still need to address: cybersecurity.
Most of autonomous vehicles use wireless signals to exchange information between vehicles about their location, direction, and speed. This collected information can be used to provide safety technologies.
Simultaneously, common communications networks enable autonomous cars to receive and transmit a great deal of information between sensors, actuators, and the electronic control units, provide access for attackers. From this point of view, cybersecurity is considered as new threats to public safety. Thus, the units that governs safety should be protected from malicious attacks, unauthorized access, or dubious activities which could interfere with public safety.
Unfortunately, while previous research efforts have largely considered attack models and detection methodologies of cybersecurity risks, very limited research efforts are known with respect to defense and mitigation technologies and the practical security issues in autonomous vehicles today. A typical automotive electronic control system mainly relies on the followings: sensors; actuators; communication networks; control algorithm. To examine the potential safety concerns associated with electronic sensors and prevent relevant crimes, there are three specific goals in this research: (1) to identify a mathematical model for autonomous vehicles, attacks, and observers; to analyze vulnerabilities of cyberattack via communication networks; to design observers to detect and identify attacks; (2) to develop countermeasures and defense strategies to maintain safety-critical systems (steering, braking, throttle, and power) functional under attacks; (3) to conduct experiments using autonomous robots to demonstrate the reliability and feasibility of the overall proposed study in a practical manner.
In order to achieve these goals, an approach from modern control engineering will be considered to design a robust filter or estimator that generates residuals which are insensitive to noise and uncertainties. Furthermore, three strategies (hybrid mode, multiple sensor fusion, isolation) will be proposed to mitigate the potential harmful consequences due to cyberattacks. Finally, two different types of simulation (SILS, HILS) and field tests will be performed. The proposed technology will impact on the automotive industry; vehicular study in academia; policymakers; criminal justice practitioner.
ca/ncf
    Supplemental Award 2 (Fiscal Year 2019, $47,131)
Today's autonomous cars, otherwise known as driverless vehicles or self-driving cars, enable the deployment of safety technologies, such as collision warning, automatic emergency braking, and Vehicle-to-Vehicle technologies.
In the near future, these systems in all vehicles will help to achieve zero fatalities, zero injuries, and zero accidents. However, behind the potential of these innovations, there is new challenge on autonomous cars that still need to address: cybersecurity.
Most of autonomous vehicles use wireless signals to exchange information between vehicles about their location, direction, and speed. This collected information can be used to provide safety technologies.
Simultaneously, common communications networks enable autonomous cars to receive and transmit a great deal of information between sensors, actuators, and the electronic control units, provide access for attackers. From this point of view, cybersecurity is considered as new threats to public safety. Thus, the units that governs safety should be protected from malicious attacks, unauthorized access, or dubious activities which could interfere with public safety.
Unfortunately, while previous research efforts have largely considered attack models and detection methodologies of cybersecurity risks, very limited research efforts are known with respect to defense and mitigation technologies and the practical security issues in autonomous vehicles today. A typical automotive electronic control system mainly relies on the followings: sensors; actuators; communication networks; control algorithm. To examine the potential safety concerns associated with electronic sensors and prevent relevant crimes, there are three specific goals in this research: (1) to identify a mathematical model for autonomous vehicles, attacks, and observers; to analyze vulnerabilities of cyberattack via communication networks; to design observers to detect and identify attacks; (2) to develop countermeasures and defense strategies to maintain safety-critical systems (steering, braking, throttle, and power) functional under attacks; (3) to conduct experiments using autonomous robots to demonstrate the reliability and feasibility of the overall proposed study in a practical manner.
In order to achieve these goals, an approach from modern control engineering will be considered to design a robust filter or estimator that generates residuals which are insensitive to noise and uncertainties. Furthermore, three strategies (hybrid mode, multiple sensor fusion, isolation) will be proposed to mitigate the potential harmful consequences due to cyberattacks. Finally, two different types of simulation (SILS, HILS) and field tests will be performed. The proposed technology will impact on the automotive industry; vehicular study in academia; policymakers; criminal justice practitioner.
ca/ncf


  
Grant-Funded Publications
        
                      Secure Multi-Robot Systems: Threat Identification and Countermeasure Development

  
Date Created: September 19, 2017
    
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