Cross-Layer Resilience and Security for Autonomous Transportation Networks - College of Engineering - Purdue University

Project Description

The security of autonomous vehicle (AV) stacks is critical, yet current paradigms predominantly focus on the individual vehicle, neglecting systemic vulnerabilities in interconnected transportation networks. Adversarial actions against a small subset of AVs can trigger cascading failures, creating large-scale disruptions that existing security mechanisms cannot address.

This project will develop a novel, cross-layer framework for cyber-resilience that bridges vehicle-level systems security with network-level traffic theory. By combining formal methods and program analysis with complex network modeling, we will create high-fidelity models of AV-driven transportation ecosystems under cyber-attack. The research will produce new AI-driven algorithms for the concurrent detection of, and response to, threats at both the individual AV and the collective network levels. This integrated approach will enable coordinated defensive strategies, moving beyond isolated vehicle-centric responses. The project's goal is to establish verifiable guarantees for the safe and resilient operation of future autonomous mobility systems, a critical step for their public acceptance and deployment.

Start Date

January or May 2026

Postdoc Qualifications

Background in Security and Privacy
Background in Autonomous Transportation
Background in AI methods

Co-advisors

Satish V. Ukkusuri (Civil Engineering/Computer Science)

Z. Berkay Celik (Computer Science)

Bibliography