[AI Security] PI-FD: Property Inference Attacks on Federated Learning with Distillation via Synthetic Data Generation, IEEE Access, May 2026

PI-FD: Property Inference Attacks on Federated Learning with Distillation via Synthetic Data Generation

Yungi Cho, Miseon Yu, Jaejin Kim, Younghan Lee, Yunheung Paek

IEEE Access, May 2026

0
 0
목록 답변 다음글

International Papers

AI Security PI-FD: Property Inference Attacks on Federated Learning with Distillation via Synthetic Data Generation, IEEE Access, May 2026
AI Security Rethinking the Capability of Fine-Tuned Language Models for Automated Vulnerability Repair, ICSE 2026
AI Security VFLIP: A Backdoor Defense for Vertical Federated Learning via Identification and Purification, ESORICS 2024
AI Security FLGuard: Byzantine-Robust Federated Learning via Ensemble of Contrastive Models, ESORICS 2023
AI Security Exploring Clustered Federated Learning’s Vulnerability against Property Inference Attack, RAID 2023
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
AI Security Learn2Evade: Learning-based Generative Model for Evading PDF Malware Classifiers, IEEE Transactions on Artificial Intelligence, July 2021
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
목록

© Copyright ⓒ 2011~2018 by SOR Lab. All Rights Reserved.
SOR Lab., Department of Electrical and Computer Engineering,
Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea