FlexServe: A Fast and Secure LLM Serving System for Mobile Devices with Flexible Resource Isolation
arXiv:2606.23370v2 Announce Type: replace-cross Abstract: Device-side Large Language Models (LLMs) have grown explosively, offering stronger privacy and higher availability than their cloud-side counterparts. During LLM inference, both the model weights and the user data are valuable, and attackers may compromise the OS kernel to steal them. ARM TrustZone is the de facto hardware-based isolation technology on mobile devices, used to protect sensitive applications from a compromised OS. However, protecting LLM inference with TrustZone incurs significant overhead to both the secure inference and
The proliferation of device-side LLMs creates urgency for robust security solutions, contrasting with existing hardware isolation's performance limitations.
This development addresses a critical security vulnerability for sensitive AI models and user data on ubiquitous mobile devices, pivotal for mainstream LLM adoption.
Mobile LLM inference can now achieve a better balance between security through hardware isolation and performance, reducing the overhead typically associated with such protection.
- · ARM Holdings
- · Mobile device manufacturers
- · On-device AI developers
- · Consumers of mobile AI
- · Malicious actors targeting mobile AI
- · Developers solely reliant on cloud-based LLMs
Wider adoption and trust in device-side LLMs for sensitive applications due to enhanced security.
Increased demand for specialized hardware and software integration that optimizes secure AI execution on edge devices.
Potential for new business models and applications built on highly secure, private on-device AI, challenging existing cloud dominance in certain sectors.
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Read at arXiv cs.LG