Description

This curriculum spans the technical and organizational rigor of a multi-phase automotive cybersecurity integration program, matching the depth of work required to secure automated driving systems across threat modeling, secure development, safety interdependencies, and supply chain governance.

Module 1: Threat Modeling and Risk Assessment for Automated Driving Systems

Conducting STRIDE-based threat modeling on vehicle-to-everything (V2X) communication interfaces to identify spoofing and tampering risks in real-time traffic data exchange.
Selecting attack trees versus attack graphs for modeling multi-step adversarial paths across perception, planning, and control subsystems.
Integrating ISO/SAE 21434 risk assessment outcomes with AUTOSAR secure software architecture constraints during system decomposition.
Assigning CVSS scores to identified vulnerabilities in over-the-air (OTA) update components under real-world exploitability conditions.
Defining asset criticality levels for LiDAR point cloud data versus camera metadata based on functional safety (ISO 26262) ASIL ratings.
Documenting threat scenario assumptions for sensor spoofing attacks (e.g., adversarial laser pulses on LiDAR) in compliance with TARA reporting requirements.

Module 2: Secure Communication Architectures in Vehicle Networks

Implementing TLS 1.3 with mutual authentication for secure V2I (vehicle-to-infrastructure) handshakes in urban mobility corridors.
Configuring CAN FD message authentication using HMAC-SHA256 with key rotation intervals constrained by ECU processing limits.
Deploying secure gateways to enforce message filtering and rate limiting between domain controllers (ADAS, infotainment, chassis).
Choosing between symmetric and asymmetric cryptography for inter-ECU communication based on latency and key management overhead.
Hardening Ethernet AVB streams carrying perception data using IEEE 802.1AE (MACsec) in time-sensitive networking environments.
Validating end-to-end encryption coverage across sensor fusion nodes to prevent in-transit data interception during platooning operations.

Module 3: Secure Software Development Lifecycle (S-SDLC) for AD Systems

Integrating static application security testing (SAST) tools into CI/CD pipelines for AUTOSAR C++14 codebases with minimal false positives.
Enforcing memory-safe coding practices in perception algorithms written in C++ to mitigate buffer overflow risks in real-time execution.
Managing third-party library vulnerabilities in open-source sensor drivers using SBOMs and automated patching workflows.
Conducting threat-informed code reviews for machine learning inference components handling object detection models.
Implementing secure boot verification chains across heterogeneous compute platforms (CPU, GPU, AI accelerators).
Applying binary integrity checks during OTA updates using Uptane framework principles with fallback mechanisms for failed validations.

Module 4: Functional Safety and Cybersecurity Integration

Resolving conflicts between fail-operational requirements (ISO 26262) and secure shutdown procedures during cyberattack detection.
Designing redundancy strategies that do not inadvertently create additional attack surfaces in dual-computing AD platforms.
Mapping cybersecurity events (e.g., GPS spoofing) to safety hazard logs and updating FMEA documentation accordingly.
Coordinating safety and security monitors in runtime environments to avoid race conditions during fault injection testing.
Aligning cybersecurity validation test cases with safety validation scenarios in HIL (Hardware-in-the-Loop) environments.
Defining escalation protocols for security operations centers (SOCs) when safety-critical systems exhibit anomalous behavior.

Module 5: Over-the-Air (OTA) Update Security and Management

Designing delta update mechanisms that preserve cryptographic signatures while minimizing bandwidth in low-connectivity zones.
Implementing rollback protection using monotonic counters in ECUs with limited non-volatile memory resources.
Validating update package authenticity across multiple trust anchors (OEM, supplier, fleet operator) in multi-tenant deployments.
Segmenting update schedules by vehicle subsystem to prevent denial-of-service during concurrent ECU flashing.
Monitoring post-update system behavior for unintended side effects using embedded diagnostic logs and anomaly detection.
Establishing secure key management policies for update signing certificates with role-based access controls and audit trails.

Module 6: Sensor and Perception System Security

Deploying optical filters and signal validation logic to detect adversarial light patterns targeting LiDAR receivers.
Implementing plausibility checks between camera, radar, and ultrasonic data to identify spoofed object presence.
Hardening GPS/IMU fusion algorithms against location spoofing using multi-constellation GNSS and inertial consistency checks.
Securing raw sensor data pipelines from tampering by isolating sensor drivers in trusted execution environments (TEEs).
Evaluating adversarial machine learning defenses for neural networks processing camera feeds under real-world lighting conditions.
Logging sensor data anomalies for forensic analysis during post-incident investigations involving perception failures.

Module 7: Incident Response and Forensic Readiness for AD Vehicles

Designing event data recorders (EDRs) to capture cybersecurity-relevant logs without violating privacy regulations in public road deployments.
Establishing secure remote access protocols for forensic data extraction from compromised AD vehicles in field incidents.
Defining data retention policies for security logs under varying jurisdictional requirements (e.g., EU GDPR vs. US state laws).
Integrating vehicle telemetry into SIEM platforms using standardized formats (e.g., OpenXDM) for centralized correlation.
Conducting tabletop exercises for coordinated response between cybersecurity teams, safety engineers, and legal departments.
Preserving chain of custody for firmware images and log files during regulatory investigations involving automated driving crashes.

Module 8: Governance, Compliance, and Supply Chain Security

Conducting cybersecurity audits of Tier 1 suppliers using UN R155 compliance checklists with technical verification steps.
Managing cryptographic key lifecycle across joint development programs involving OEMs, suppliers, and cloud providers.
Enforcing secure configuration baselines for development and test environments used in AD software prototyping.
Documenting cybersecurity design decisions in system architecture reviews to satisfy regulatory audit requirements.
Implementing secure data sharing agreements for training datasets used in perception model development.
Tracking emerging threats through participation in automotive ISACs and integrating intelligence into vulnerability management processes.