Canada Spends Logo

Explore our Budget 2026 analysis

Grant: Discovery Launch Supplement

University of Ontario Institute of Technology

$12,500.00

Intrusion Detection and Forensic Analysis for IoT Systems in Connected and Automated Vehicles (CAVs)

FY 2024-25

Summary
The dawn of intelligent, interconnected, and autonomous vehicles heralds a profound transformation in the automotive sector, a shift rivaled only by the revolution ignited by Henry Ford's Model T in 1913. By harnessing a synergy of sensors, controllers, and advanced onboard technology, these Connected and Automated Vehicles (CAVs) can autonomously execute or aid in operations like steering, braking, and environmental monitoring. This technological merger offers heightened safety, optimized mobility, and reduced emissions. As autonomous electric vehicles transition into the mainstream, global automakers are swiftly refining their CAV strategies. At their foundation, CAVs depend on a spectrum of wired and wireless technologies that enable communication between their integral systems and the broader transportation landscape. This interconnectedness broadens potential attack surfaces, introducing distinct security vulnerabilities. Given the real-time system response requirements in CAVs (for instance, the expected reaction time of an anti-lock braking system), traditional cybersecurity methods may fall short. The emerging cybersecurity threats that CAVs face have life-threatening implications. A compromised vehicle under remote control, for instance, could be employed for intricate terrorist acts, potentially leading to substantial casualties. Therefore, there's an urgent necessity to devise new monitoring and defense mechanisms, especially considering the computational restrictions inherent to the embedded IoT devices in these vehicles. The long-term goal of this proposed research program is to propel forward the current state of intrusion detection research concerning CAVs. The program will primarily center on two application domains: (1) intrusion detection systems tailored for IoT devices within CAVs, and (2) forensic examination of incidents involving CAVs. Specific short-term objectives tackled in this program encompass: (a) the identification and counteraction of advanced cyber threats specific to CAVs, while accounting for computational limitations like response time and the restricted memory of in-vehicle computing nodes, and (b) the efficient collection and storage of massive real-time data for forensic scrutiny. As the industry progresses, churning out innovative products and immediate security remedies, our program is poised to emphasize foundational research, which is indispensable for ensuring a secure and effective integration of CAVs both in Canada and globally. This aligns seamlessly with Canada's National Cyber Security Strategy. Furthermore, this DG program promises to be a rich training ground for 11 HQP in the realms of cybersecurity and forensic analysis-a talent demographic highly coveted by Canada's transportation and manufacturing sector. This will firmly position Canada at the vanguard of this technological wave.
Program
Discovery Launch Supplement
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
DGECR-2024-00004
Name nom
Madani, Pooria
Department département
Faculty of Business and IT
Organization id
19222
Institution établissement
University of Ontario Institute of Technology
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2024
Award amount
12500
Program id
DGECR
Program name en
Discovery Launch Supplement
Program name fr
Supplément Tremplin vers la découverte
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1507
Committee name en
Computer Science
Committee name fr
Sciences informatiques
Area of application code
801
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Computer software
Area of application fr
Logiciel
Research subject code
3002
Research subject group en
Statistics and probability
Research subject group fr
Statistique et probabilité
Research subject en
Time series analysis
Research subject fr
Analyse des séries chronologiques
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Intrusion Detection and Forensic Analysis for IoT Systems in Connected and Automated Vehicles (CAVs)
Keywords
connected and automated vehicles; intrusion detection systems; internet of things; forensic analysis; cybersecurity
Application summary
The dawn of intelligent, interconnected, and autonomous vehicles heralds a profound transformation in the automotive sector, a shift rivaled only by the revolution ignited by Henry Ford's Model T in 1913. By harnessing a synergy of sensors, controllers, and advanced onboard technology, these Connected and Automated Vehicles (CAVs) can autonomously execute or aid in operations like steering, braking, and environmental monitoring. This technological merger offers heightened safety, optimized mobility, and reduced emissions. As autonomous electric vehicles transition into the mainstream, global automakers are swiftly refining their CAV strategies. At their foundation, CAVs depend on a spectrum of wired and wireless technologies that enable communication between their integral systems and the broader transportation landscape. This interconnectedness broadens potential attack surfaces, introducing distinct security vulnerabilities. Given the real-time system response requirements in CAVs (for instance, the expected reaction time of an anti-lock braking system), traditional cybersecurity methods may fall short. The emerging cybersecurity threats that CAVs face have life-threatening implications. A compromised vehicle under remote control, for instance, could be employed for intricate terrorist acts, potentially leading to substantial casualties. Therefore, there's an urgent necessity to devise new monitoring and defense mechanisms, especially considering the computational restrictions inherent to the embedded IoT devices in these vehicles. The long-term goal of this proposed research program is to propel forward the current state of intrusion detection research concerning CAVs. The program will primarily center on two application domains: (1) intrusion detection systems tailored for IoT devices within CAVs, and (2) forensic examination of incidents involving CAVs. Specific short-term objectives tackled in this program encompass: (a) the identification and counteraction of advanced cyber threats specific to CAVs, while accounting for computational limitations like response time and the restricted memory of in-vehicle computing nodes, and (b) the efficient collection and storage of massive real-time data for forensic scrutiny. As the industry progresses, churning out innovative products and immediate security remedies, our program is poised to emphasize foundational research, which is indispensable for ensuring a secure and effective integration of CAVs both in Canada and globally. This aligns seamlessly with Canada's National Cyber Security Strategy. Furthermore, this DG program promises to be a rich training ground for 11 HQP in the realms of cybersecurity and forensic analysis-a talent demographic highly coveted by Canada's transportation and manufacturing sector. This will firmly position Canada at the vanguard of this technological wave.