文献データベース

PrivCode++: Latent-Conditioned Differentially Private Code Generation for Comprehensive Guarantees

Authors: Zheng Liu, Chen Gong, Terry Yue Zhuo, Zhou Yang, Kecen Li, Wenlong Meng, Xinwen Hou, Yu Liu, Xiaochen Li | Published: 2026-06-08
データ生成の安全性
プライバシー保護機械学習
差分プライバシー

Steganography Without Modification: Hidden Communication via LLM Seeds

Authors: Felix Mächtle, Jonas Sander, Sebastian Berndt, Ben Weimar, Nils Loose, Thomas Eisenbarth | Published: 2026-06-08
LLMの安全機構の解除
トークン識別手法
確率分布

Unveiling Privacy Risks in Multi-modal Large Language Models: Task-specific Vulnerabilities and Mitigation Challenges

Authors: Tiejin Chen, Pingzhi Li, Kaixiong Zhou, Tianlong Chen, Hua Wei | Published: 2026-06-08
データ生成の安全性
プライバシー保護機械学習
プロンプトインジェクション

PAC-Bayesian Adversarially Robust Generalization for Message Passing Graph Neural Networks: A Sensitivity Analysis

Authors: Ziling Liang, Xinping Yi, Qingsong Wen, Shi Jin | Published: 2026-06-04
モデルの頑健性保証
ロバスト性分析
機械学習

Robust Ensemble of Selectively Strengthened and Augmented Predictors

Authors: Parsa Memarzadehsaghezi, Zahra Hashemi, Pooria Madani, Mehran Ebrahimi | Published: 2026-06-04
モデル抽出攻撃の検知
ロバスト性向上手法
敵対的攻撃評価

TinyML-Driven Cybersecurity for Autonomous Spacecraft: Latency-Accuracy Analysis for SPARTA RF and Cyber Threat Detection

Authors: Van Le, Trevor Tran, Tan Le | Published: 2026-06-04
ロバスト性評価
効率性評価
機械学習

Membrane: A Self-Evolving Contrastive Safety Memory for LLM Agent Defense

Authors: Minseok Choi, Seungbin Yang, Dongjin Kim, Subin Kim, Jungmin Son, Yunseung Lee, Jaegul Choo, Youngjun Kwak | Published: 2026-06-04
データ収集手法
プロンプトインジェクション
ロバスト性評価

An Embarrassingly Simple Detector for Model Extraction Attacks in Large Language Model API Traffic

Authors: Shuze Liu, Qianwen Guo, Yushun Dong | Published: 2026-06-04
モデル抽出攻撃
効率性評価
検出手法の分析

Hybrid CNN-LSTM Framework for Intelligent Cyber Attack Detection and Prevention in U.S. Critical Digital Infrastructure: A Comparative Machine Learning Evaluation on CSE-CIC-IDS2018

Authors: Md. Iqbal Hossan, Md. Serajul Kabir Chowdhury Rubel, Md. Arifur Rahman, B. M. Taslimul Haque | Published: 2026-06-04
文献レビュー
機械学習
機械学習フレームワーク

Explainable AI-Driven Cyber Risk Analytics and Model Reliability Assessment for Intelligent Governance of U.S. Critical Infrastructure: An XGBoost and SHAP-Based Intrusion Detection Framework

Authors: B. M. Taslimul Haque, Md. Arifur Rahman, Md. Serajul Kabir Chowdhury Rubel, Md. Iqbal Hossan | Published: 2026-06-04
リスク評価
解釈可能性
説明可能性評価