[Privacy Enhancing Computing] HEPIC: Private Inference over Homomorphic Encryption with Client Intervention, ASPLOS 2026

HEPIC: Private Inference over Homomorphic Encryption with Client Intervention

Kevin Nam, Youyeon Joo, Seungjin Ha, Hyungon Moon*, Yunheung Paek*

The ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2026 (ASPLOS 2026)

∗ : Correspondence should be addressed to H. Moon and Y. Peak

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International Papers

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AI Security Precise Extraction of Deep Learning Models via Side-Channel Attacks on Edge/Endpoint Devices, ESORICS 2022
AI Security A pilot study of machine-learning-based algorithms to assist integrated care for older community-dwelling adults, Computers, Informatics, Nursing (CIN), Feb 2022
AI Security A Data Embedding Scheme for Efficient Program Behavior Modeling with Neural Networks (early access), IEEE Transactions on Emerging Topics in Computational Intelligence (Impact Factor: 8.28), May 2022
AI Security Panop: Mimicry-Resistant ANN-based Distributed NIDS for IoT Networks, IEEE Access, July 2021
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AI Security Hawkware: Network Intrusion Detection based on Behavior Analysis with ANNs on an IoT Device, Design Automation Conference (DAC), Jul 2020
AI Security DADE: a fast data anomaly detection engine for kernel integrity monitoring, The Journal of Supercomputing, Aug 2019
AI Security Hawkware: Network Intrusion Detection based on Behavior Analysis with ANNs on an IoT Device, Design Automation Conference WIP, Jun 2019
AI Security Real-Time Anomalous Branch Behavior Detection with a GPU-inspired Engine for Machine Learning Models, DATE, Mar 2019
AI Security An SoC Architecture for Learning-Based Online Anomaly Detection on ARM, Design Automation Conference WIP, Jun 2018
AI Security Mimicry Resilient Program Behavior Modeling with LSTM based Branch Models, DEEP LEARNING AND SECURITY WORKSHOP, May2018
AI Security LSTM-Based System-Call Language Modeling and Robust Ensemble Method for Designing Host-Based Intrusion Detection Systems, arXiv preprint arXiv:1611.01726, Nov 2016
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