mlsanityData to 14 Oct 2026

FlexServe: A Fast and Secure LLM Serving System for Mobile Devices with Flexible Resource Isolation

arXiv 2606.23370 ↗First posted 22 Jun 2026cs.CR cs.LG cs.OScited by 0

Not on the map. Why?

Abstract (arXiv)

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 normal aplications, due to two challenges: the inflexible resource isolation and the inefficient secure resource management. To address these challenges, this paper presents FlexServe, a fast and secure LLM inference system for mobile devices. The key idea is to decouple the access permission from the management permission of secure resources, so that the normal-world OS cannot access them but can still manage them as usual. First, FlexServe introduces a Recallable Resource Isolation mechanism to construct Recallable Secure Memory (Flex-Mem) and a Recallable Secure NPU (Flex-NPU). They can only be accessed by the secure world, but can be efficiently allocated and reclaimed by the normal-world OS. Based on them, FlexServe further introduces a FlexServe Framework to run secure LLM inference in the secure world. It works together with the normal-world OS to perform cooperative secure memory management. We implement a prototype of FlexServe and compare it with two TrustZone-based strawman designs. The results show that FlexServe achieves average TTFT speedups of 10.05X over the strawman and 2.44X over an optimized strawman.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 23 of its 80 references that are in the map. First posted on arXiv 22 Jun 2026.

Builds on

23 of 80 references.

References · 23

  1. 2024The Llama 3 Herd of Modelscited by 14,715
  2. 2023Efficient Memory Management for Large Language Model Serving with PagedAttentioncited by 5,944
  3. 2023Qwen Technical Reportcited by 3,344
  4. 2025Gemma 3 Technical Reportcited by 1,824
  5. 2024Phi-4 Technical Reportcited by 711
  6. 2023PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Financecited by 222
  7. 2023You Only Look at Screens: Multimodal Chain-of-Action Agentscited by 185
  8. 2024Ferret-UI: Grounded Mobile UI Understanding with Multimodal LLMscited by 176
  9. 2021Lawformer: A Pre-trained Language Model for Chinese Legal Long Documentscited by 116
  10. 2024On-Device Language Models: A Comprehensive Reviewcited by 104
  11. 2024The rising costs of training frontier AI modelscited by 95
  12. 2020DarkneTZ: Towards Model Privacy at the Edge using Trusted Execution Environmentscited by 58
11 more
  1. 2024Ferret-UI 2: Mastering Universal User Interface Understanding Across Platformscited by 51
  2. 2025Apple Intelligence Foundation Language Models: Tech Report 2025cited by 28
  3. 2025Characterizing Mobile SoC for Accelerating Heterogeneous LLM Inferencecited by 22
  4. 2025Position: The Most Expensive Part of an LLM should be its Training Datacited by 16
  5. 2020Serdab: An IoT Framework for Partitioning Neural Networks Computation across Multiple Enclavescited by 11
  6. 2024TransLinkGuard: Safeguarding Transformer Models Against Model Stealing in Edge Deploymentcited by 11
  7. 2025MobiAgent: A Systematic Framework for Customizable Mobile Agentscited by 9
  8. 2025UI-UG: A Unified MLLM for UI Understanding and Generationcited by 5
  9. 2025TZ-LLM: Protecting On-Device Large Language Models with Arm TrustZonecited by 5
  10. 2023Robust Safe Reinforcement Learning under Adversarial Disturbancescited by 4
  11. 2017TrustShadow: Secure Execution of Unmodified Applications with ARM TrustZonecited by 3

Built on by

Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2026FlexServe: A Fast and Secure LLM Serving System for Mobile Devices with Flexible Resource Isolation
  2. 2023LinguaLinked: A Distributed Large Language Model Inference System for Mobile Devices
  3. 2025AttestLLM: Efficient Attestation Framework for Billion-scale On-device LLMs
  4. 2025A Survey: Towards Privacy and Security in Mobile Large Language Models
  5. 2026Securing LLMs in the Wild: Privacy and Security Challenges at the Edge
  6. 2026Is Your NPU Ready for LLMs? Dissecting the Hidden Efficiency Bottlenecks in Mobile LLM Inference
  7. 2025Towards Confidential and Efficient LLM Inference with Dual Privacy Protection
  8. 2025A Systematic Evaluation of On-Device LLMs: Quantization, Performance, and Resources