SVX-AD
SVX-AD is an identity-centric security protocol for Vehicle-to-Infrastructure (V2I) environments that integrates Zero Trust verification with AI/ML-based anomaly detection. The protocol is designed for high-consequence cyber-physical systems where errors or malicious manipulation can translate into unsafe roadway decisions.
Artifact Overview
Connected transportation systems increasingly rely on V2I services for safety messaging, signal timing, routing optimization, and situational awareness. This dependency creates a security discontinuity: the roadway becomes dependent on networked trust decisions, yet the environment remains adversarial, partially observable, and latency-sensitive.
Intelligent Transportation Systems (ITS) and multi-jurisdiction V2I deployments where infrastructure services must remain trustworthy under adversarial conditions.
Simulation5 metrics
1. Problem Statement & Operational Motivation
Connected transportation systems increasingly rely on V2I services for safety messaging, signal timing, routing optimization, and situational awareness. This dependency creates a security discontinuity: the roadway becomes dependent on networked trust decisions, yet the environment remains adversarial, partially observable, and latency-sensitive.
This problem arises in the context of intelligent transportation systems (its) and multi-jurisdiction v2i deployments where infrastructure services must remain trustworthy under adversarial conditions. and reflects constraints commonly encountered in production systems, including scale, adversarial behavior, regulatory requirements, and operational continuity.
2. Artifact Description
SVX-AD is an identity-centric security protocol for Vehicle-to-Infrastructure (V2I) environments that integrates Zero Trust verification with AI/ML-based anomaly detection. The protocol is designed for high-consequence cyber-physical systems where errors or malicious manipulation can translate into unsafe roadway decisions.
The artifact is designed to be identity-first, treating authentication, authorization, federation, and policy enforcement as the primary control plane. It is intended to function under real operational conditions rather than idealized assumptions.
3. Design Science Research Methodology (DSRM) Mapping
SVX-AD follows DSRM with research contributions expressed as an operational artifact.
• Problem Identification & Motivation
The operational problem was defined based on observed risks and limitations in existing systems.
• Design & Development
SVX-AD is built on the following design principles:
- IAM as the control plane for V2I service access (AuthN/AuthZ as first-order security controls)
- Zero Trust by default, using continuous verification rather than implicit trust
- Behavioral anomaly detection to complement cryptographic and policy controls
- Operational resilience, ensuring safe behavior under degraded or attacked connectivity
• Build
The artifact is defined as a protocol specification that includes: message exchange and validation flow, identity and authorization checkpoints, detection and control logic for anomalous interactions, and response guidance for safety-aligned outcomes.
• Demonstration
SVX-AD is demonstrated through a simulation framework in which representative V2I message flows are subjected to adversarial attack patterns. The protocol's detection and response behavior is measured across multiple scenarios to evaluate operational feasibility.
• Evaluation
Evaluation is designed around measurable outcomes: detection performance, response latency, and operational stability under attack. Results are reported in a form suitable for publication-grade figures and grant deliverables.
• Communication
The artifact is documented as a citable protocol object and connected to research notes, simulation plans, and deployment guidance.
4. Evaluation & Evidence
Evaluation Method: Simulation
Evaluation Metrics:
- Detection performance (e.g., ROC/AUC where applicable)
- Responsiveness by attack type (time-to-detect, time-to-contain)
- False positive / false negative balance
- Model efficiency metrics (compute footprint, latency)
- Operational continuity under attack (service degradation profile)
Evaluation Contexts:
- Attack simulation suite design for V2I interactions
- Protocol responsiveness analysis under adversarial conditions
- Comparative evaluation across attack categories (spoofing, replay, jamming, integrity tampering)
The evaluation approach treats the environment as adversarial and constrained. SVX-AD is not assessed on theoretical correctness alone; it is assessed on whether it can deliver trustworthy behavior under realistic deployment assumptions.
5. Applicability & Use Cases
SVX-AD applies to:
Use cases include:
- Architecture design and review
- Security control implementation
- Research extension and replication
- Teaching and laboratory exercises
- Policy and governance analysis
6. Limitations & Scope
SVX-AD's simulation-driven evaluation depends on the realism of attack modeling, network constraints, and traffic assumptions. Field validation requires access to pilot infrastructure and operational approvals, and may necessitate adaptations for device diversity, regional policy constraints, and integration with existing transportation vendor ecosystems.
7. Iteration & Evolution
SVX-AD is designed to evolve as new attack patterns and adversary capabilities emerge, additional evaluation datasets and simulation fidelity are introduced, deployment feedback is incorporated from pilots and operational stakeholders, and identity federation requirements expand across jurisdictions.
8. How to Cite This Artifact
J. Nsoh, "SVX-AD: An Identity-Centric V2I Security Protocol Artifact for Anomaly Detection," Artifact, Nsoh Research, 2025. Available: https://jovita.io/artifacts/svx-ad
9. Related Research & Teaching
10. License & Availability
License: TBD
Last Updated: 2025-12-20
Where applicable, reference implementations and simulation configurations will be published as linked materials under this artifact record.
SVX-AD represents an applied research contribution produced through Design Science Research Methodology. Its value lies not only in correctness, but in whether it can be implemented, evaluated, and trusted in real operational environments.