Enhancing Autonomous Vehicle Security
A comprehensive research project focused on developing innovative security solutions for autonomous vehicles.
Research Components
Our research focuses on four key components to enhance the security of autonomous vehicles.
Smart Key System
Wickramaarachchi J.C.
Developing a smart key system using an Android app to replace traditional vehicle key fobs, enhancing security and convenience.
Secure V2V/V2I Communications
Al balushi O.T.M.G
Implementing lightweight ECC for secure Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications, protecting against network attacks.
PUF-based Authentication
Jayasinghe K.A.C.T
Utilizing Physical Unclonable Functions (PUFs) to create a robust challenge-response mechanism, enhancing authentication and guarding against side-channel attacks.
GPS Spoofing Detection
Wanigasekara W.M.I.W
A machine learning-based anomaly detection system to identify and counter GPS spoofing, ensuring reliable navigation for autonomous vehicles.
Research Domain
Our research focuses on four key components to enhance the security of autonomous vehicles.
Smart Key System
Wickramaarachchi J.C.
Developing a smart key system using an Android app to replace traditional vehicle key fobs, enhancing security and convenience.
- Android application replacing traditional key fobs
- Enhanced encryption for secure communication
- Role-Based Access Control (RBAC)
- Multi-Factor Authentication (MFA)
Secure V2V/V2I Communications
Al balushi O.T.M.G
Implementing lightweight ECC for secure Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications, protecting against network attacks.
- Lightweight ECC-based authentication
- Black-hole attack mitigation
- Trust-based security mechanism
- Performance evaluation metrics
PUF-based Authentication
Jayasinghe K.A.C.T
Utilizing Physical Unclonable Functions (PUFs) to create a robust challenge-response mechanism, enhancing authentication and guarding against side-channel attacks.
- Challenge-response mechanism
- FPGA implementation
- Hardware-based security
- Protection against cloning attempts
GPS Spoofing Detection
Wanigasekara W.M.I.W
A machine learning-based anomaly detection system to identify and counter GPS spoofing, ensuring reliable navigation for autonomous vehicles.
- Machine learning anomaly detection
- Real-time GPS data analysis
- IoT-based rover implementation
- Mobile app integration for alerts
Project Milestones
Key assessments and deliverables throughout our research project.
Topic Assessment Form (TAF)
Topic Review
May 13, 2024
Presentation of the research topic its sub-components with objectives.
Project Proposal
Initial project scope and objectives.
July 05, 2024
Presentation of the research proposal outlining the project scope, objectives, and methodology.
Marks: 06%
Progress Presentation 1
First progress review
Dec 04, 2024
Presentation of initial research findings, literature review, and preliminary implementation.
Marks: 15%
Progress Presentation 2
Second progress review
June 30, 2025
Presentation of advanced implementation, testing results, and refined methodology.
Marks: 18%
Final Assessment & Viva
Final project evaluation
July 10, 2025
Final presentation and viva of the complete project, demonstration of all components, and comprehensive documentation.
Marks: 20%
Project Documents
Access all project documentation and deliverables.
TAF Document
Initial project definition
Formal document outlining the project scope, objectives, and stakeholders.
Proposal Document
Research proposal
Comprehensive proposal detailing research questions, methodology, and expected outcomes.
Check List Documents
Project verification
Quality assurance checklists for each phase of the research project.
Smart Key System
Component 1 Documentation
Technical documentation for the Smart Key System component.
V2V/V2I Security
Component 2 Documentation
Technical documentation for the V2V/V2I Security component.
PUF Authentication
Component 3 Documentation
Technical documentation for the PUF Authentication component.
GPS Spoofing Detection
Component 4 Documentation
Technical documentation for the GPS Spoofing Detection component.
Final Document
Complete research paper
Comprehensive final document integrating all research components.
Presentations
Access slides from our project presentations.
Proposal Presentation
March 15, 2025
Initial presentation outlining the research proposal and methodology.
Progress Presentation 1
April 20, 2025
First progress review presentation with initial findings and implementation.
Progress Presentation 2
May 25, 2025
Second progress review presentation with advanced implementation and testing results.
Final Presentation
June 30, 2025
Final project presentation with comprehensive results and findings.
About Us
Meet our research team working on enhancing autonomous vehicle security.
Contact Us
Get in touch with our research team.
alert@nexlock.live
Research Team
24-25J-140 - Faculty of Computing, SLIIT
Project Timeline
March 2025 - July 2025
Send us a message
Securing the Future of Autonomous Mobility
Our research aims to address critical security challenges in autonomous vehicles, ensuring a safer and more secure future for transportation.