FlexServe: A Fast and Secure LLM Serving System for Mobile Devices with Flexible Resource Isolation
arXiv:2603.09046v3 Announce Type: replace-cross Abstract: Device-side Large Language Models (LLMs) have witnessed explosive growth, offering higher privacy and availability compared to cloud-side LLMs. During LLM inference, both model weights and user data are valuable, and attackers may even 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 due to its inflexible isolation of memory
The rapid growth of device-side LLMs creates an immediate need for robust security solutions that can protect sensitive models and user data without compromising performance on mobile hardware.
This development addresses a critical vulnerability in the expanding deployment of AI on personal devices, directly impacting privacy, data security, and the viability of edge AI applications.
The ability to run secure and fast LLM inference on mobile devices with flexible resource isolation could accelerate the adoption of private, device-centric AI and potentially reduce reliance on cloud infrastructure for certain applications.
- · Mobile device manufacturers
- · On-device AI developers
- · Cybersecurity firms
- · Consumers prioritizing privacy
- · Cloud-dependent AI service providers (for certain use cases)
- · Attackers targeting LLM weights and user data on mobile
Increased trust and adoption of on-device LLMs for sensitive information processing.
Decentralization of personal AI, shifting data processing from cloud servers to individual devices.
New business models emerging around secure, localized AI services that prioritize user data ownership and privacy.
This signal links to a primary source. Continuum Brief monitors and indexes it as part of the live intelligence stream — we do not republish source content.
Read at arXiv cs.LG