K
Khin Mi Mi Aung
Researcher at Institute for Infocomm Research Singapore
Publications - 100
Citations - 1202
Khin Mi Mi Aung is an academic researcher from Institute for Infocomm Research Singapore. The author has contributed to research in topics: Encryption & Homomorphic encryption. The author has an hindex of 16, co-authored 88 publications receiving 830 citations. Previous affiliations of Khin Mi Mi Aung include Agency for Science, Technology and Research & Data Storage Institute.
Papers
More filters
Book ChapterDOI
A Blockchain-Based Storage System for Data Analytics in the Internet of Things
TL;DR: This chapter proposes a blockchain-based storage system, named Sapphire, for data analytics applications in the Internet of Things, and presents an OSD-based smart contract (OSC) approach employed in Sapphire as a transaction protocol, where IoT devices interact with such blockchains.
Journal ArticleDOI
Towards the AlexNet Moment for Homomorphic Encryption: HCNN, the First Homomorphic CNN on Encrypted Data With GPUs
Ahmad Al Badawi,Chao Jin,Jie Lin,Chan Fook Mun,Sim Jun Jie,Benjamin Hong Meng Tan,Xiao Nan,Khin Mi Mi Aung,Vijay Chandrasekhar +8 more
TL;DR: This paper evaluated a CNN to classify homomorphically the MNIST dataset into 10 classes using a number of techniques such as low-precision training, unified training and testing network, optimized FHE parameters and a very efficient GPU implementation to achieve high performance.
Journal ArticleDOI
Implementation and Performance Evaluation of RNS Variants of the BFV Homomorphic Encryption Scheme
TL;DR: This work implements and evaluates the performance of two optimized variants, namely Bajard-Eynard-Hasan-Zucca (BEHZ) and Halevi-Polyakov-Shoup (HPS), of the most promising homomorphic encryption scheme in CPU and GPU, and finds that the HPS variant in practice scales significantly better with increase in multiplicative depth of the computation circuit than BEHZ.
Proceedings ArticleDOI
High-Performance FV Somewhat Homomorphic Encryption on GPUs: An Implementation using CUDA
TL;DR: This work presents a CUDAbased implementation of the Fan and Vercauteren (FV) Somewhat HomomorphicEncryption (SHE) scheme and demonstrates several algebraic tools such as the Chinese Remainder Theorem, Residual Number System (RNS) and Discrete Galois Transform (DGT) to accelerate and facilitate FV computation on GPUs.
Journal ArticleDOI
A loss-free multipathing solution for data center network using software-defined networking approach
TL;DR: Simulation results show that the combined solution can further improve network throughput with FFD mechanism and guarantee loss-free delivery with integrated CC, and Software-Defined Networking techniques are employed in the implementation, which decouples routing intelligence from data transmission.