3D Guard-Layer: An Integrated Agentic AI Safety System for Edge Artificial Intelligence

TL;DR

This paper introduces a 3D integrated agentic AI safety system for edge AI devices that dynamically learns and mitigates security threats, enhancing safety, resilience, and performance with minimal overhead.

Contribution

It presents a novel 3D safety architecture that combines local learning and threat mitigation directly on edge devices, improving security and system robustness.

Findings

Enhanced threat detection and mitigation capabilities.

Improved system resilience and reliability.

Minimal integration overhead with 3D architecture.

Abstract

AI systems have found a wide range of real-world applications in recent years. The adoption of edge artificial intelligence, embedding AI directly into edge devices, is rapidly growing. Despite the implementation of guardrails and safety mechanisms, security vulnerabilities and challenges have become increasingly prevalent in this domain, posing a significant barrier to the practical deployment and safety of AI systems. This paper proposes an agentic AI safety architecture that leverages 3D to integrate a dedicated safety layer. It introduces an adaptive AI safety infrastructure capable of dynamically learning and mitigating attacks against the AI system. The system leverages the inherent advantages of co-location with the edge computing hardware to continuously monitor, detect and proactively mitigate threats to the AI system. The integration of local processing and learning capabilities enhances resilience against emerging network-based attacks while simultaneously improving system reliability, modularity, and performance, all with minimal cost and 3D integration overhead.