Memory-Efficient and Secure DNN Inference on TrustZone-enabled Consumer IoT Devices

arXiv:2403.12568v1 Announce Type: new
Abstract: Edge intelligence enables resource-demanding Deep Neural Network (DNN) inference without transferring original data, addressing concerns about data privacy in consumer Internet of Things (IoT) devices. For privacy-sensitive applications, deploying models in hardware-isolated trusted execution environments (TEEs) becomes essential. However, the limited secure memory in TEEs poses challenges for deploying DNN inference, and alternative techniques like model partitioning and offloading introduce performance degradation and security issues. In this paper, we present a novel approach for advanced …

applications arxiv consumer consumer internet consumer iot cs.ai cs.cr data data privacy devices edge environments hardware intelligence internet internet of things iot iot devices memory network neural network privacy resource sensitive things