敵対的サンプルから守る、敵対的学習New
敵対的サンプルに対する対策技術の1つに、敵対的学習があります。本記事では、敵対的学習を用いて、どのように敵対的サンプルの影響を防ぐかを解説します。
Acoustic Side-Channel Attacks on a Computer Mouse
Authors: Mauro Conti, Marin Duroyon, Gabriele Orazi, Gene Tsudik | Published: 2025-05-05
Unveiling the Landscape of LLM Deployment in the Wild: An Empirical Study
Authors: Xinyi Hou, Jiahao Han, Yanjie Zhao, Haoyu Wang | Published: 2025-05-05
Bayesian Robust Aggregation for Federated Learning
Authors: Aleksandr Karakulev, Usama Zafar, Salman Toor, Prashant Singh | Published: 2025-05-05
Advancing Email Spam Detection: Leveraging Zero-Shot Learning and Large Language Models
Authors: Ghazaleh SHirvani, Saeid Ghasemshirazi | Published: 2025-05-05
Analysis of the vulnerability of machine learning regression models to adversarial attacks using data from 5G wireless networks
Authors: Leonid Legashev, Artur Zhigalov, Denis Parfenov | Published: 2025-05-01
LLM-Based Threat Detection and Prevention Framework for IoT Ecosystems
Authors: Yazan Otoum, Arghavan Asad, Amiya Nayak | Published: 2025-05-01
An Empirical Study on the Effectiveness of Large Language Models for Binary Code Understanding
Authors: Xiuwei Shang, Zhenkan Fu, Shaoyin Cheng, Guoqiang Chen, Gangyang Li, Li Hu, Weiming Zhang, Nenghai Yu | Published: 2025-04-30
LASHED: LLMs And Static Hardware Analysis for Early Detection of RTL Bugs
Authors: Baleegh Ahmad, Hammond Pearce, Ramesh Karri, Benjamin Tan | Published: 2025-04-30
Bilateral Differentially Private Vertical Federated Boosted Decision Trees
Authors: Bokang Zhang, Zhikun Zhang, Haodong Jiang, Yang Liu, Lihao Zheng, Yuxiao Zhou, Shuaiting Huang, Junfeng Wu | Published: 2025-04-30