:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Simon, Raphael, Libin, Pieter, Mees, Wim
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Cryptography and Security
Accesso online:	https://arxiv.org/abs/2509.20008
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

NASimJax: GPU-Accelerated Policy Learning Framework for Penetration Testing
di: Simon, Raphael, et al.
Pubblicazione: (2026)

Leveraging AI to optimize website structure discovery during Penetration Testing
di: Antonelli, Diego, et al.
Pubblicazione: (2021)

Mind the Gap: Towards Generalizable Autonomous Penetration Testing via Domain Randomization and Meta-Reinforcement Learning
di: Zhou, Shicheng, et al.
Pubblicazione: (2024)

Guided Reasoning in LLM-Driven Penetration Testing Using Structured Attack Trees
di: Nakano, Katsuaki, et al.
Pubblicazione: (2025)

Knowledge-Informed Auto-Penetration Testing Based on Reinforcement Learning with Reward Machine
di: Li, Yuanliang, et al.
Pubblicazione: (2024)

Robustness of Selected Learning Models under Label-Flipping Attack
di: Bhargava, Sarvagya, et al.
Pubblicazione: (2025)

P3LS: Partial Least Squares under Privacy Preservation
di: Duy, Du Nguyen, et al.
Pubblicazione: (2024)

On Evaluating the Poisoning Robustness of Federated Learning under Local Differential Privacy
di: Wang, Zijian, et al.
Pubblicazione: (2025)

On the Statistical Complexity of Estimation and Testing under Privacy Constraints
di: Lalanne, Clément, et al.
Pubblicazione: (2022)

Adversarial Robustness of Time-Series Classification for Crystal Collimator Alignment
di: Fink, Xaver, et al.
Pubblicazione: (2026)

SUB-PLAY: Adversarial Policies against Partially Observed Multi-Agent Reinforcement Learning Systems
di: Ma, Oubo, et al.
Pubblicazione: (2024)

Robust Feature Inference: A Test-time Defense Strategy using Spectral Projections
di: Singh, Anurag, et al.
Pubblicazione: (2023)

Auto-ART: Structured Literature Synthesis and Automated Adversarial Robustness Testing
di: Talluri, Abhijit
Pubblicazione: (2026)

A System for Interactive Examination of Learned Security Policies
di: Hammar, Kim, et al.
Pubblicazione: (2022)

ARMOR: Robust Reinforcement Learning-based Control for UAVs under Physical Attacks
di: Dash, Pritam, et al.
Pubblicazione: (2025)

Methods for generating and evaluating synthetic longitudinal patient data: a systematic review
di: Perkonoja, Katariina, et al.
Pubblicazione: (2023)

On the Conflict of Robustness and Learning in Collaborative Machine Learning
di: Raynal, Mathilde, et al.
Pubblicazione: (2024)

Coded Robust Aggregation for Distributed Learning under Byzantine Attacks
di: Li, Chengxi, et al.
Pubblicazione: (2025)

Graph Unlearning with Efficient Partial Retraining
di: Zhang, Jiahao, et al.
Pubblicazione: (2024)

Quantifying Policy Administration Cost in an Active Learning Framework
di: Zhang, Si, et al.
Pubblicazione: (2023)

CCLab: Adversarial Testing of Learning- and Non-Learning-Based Congestion Controllers
di: Chen, Zhi, et al.
Pubblicazione: (2026)

Simple and Efficient Partial Graph Adversarial Attack: A New Perspective
di: Zhu, Guanghui, et al.
Pubblicazione: (2023)

FL-PLAS: Federated Learning with Partial Layer Aggregation for Backdoor Defense Against High-Ratio Malicious Clients
di: Zhang, Jianyi, et al.
Pubblicazione: (2025)

On the Robustness of Distributed Machine Learning against Transfer Attacks
di: Andreina, Sébastien, et al.
Pubblicazione: (2024)

Robust Subgraph Learning by Monitoring Early Training Representations
di: Neshatfar, Sepideh, et al.
Pubblicazione: (2024)

DRGW: Learning Disentangled Representations for Robust Graph Watermarking
di: Li, Jiasen, et al.
Pubblicazione: (2026)

TA3: Testing Against Adversarial Attacks on Machine Learning Models
di: Jin, Yuanzhe, et al.
Pubblicazione: (2024)

Deep Learning under Fractional-Order Differential Privacy
di: Partohaghighi, Mohammad, et al.
Pubblicazione: (2026)

A Robust Adversary Detection-Deactivation Method for Metaverse-oriented Collaborative Deep Learning
di: Li, Pengfei, et al.
Pubblicazione: (2023)

Neutral Agent-based Adversarial Policy Learning against Deep Reinforcement Learning in Multi-party Open Systems
di: Peng, Qizhou, et al.
Pubblicazione: (2025)

ModSec-AdvLearn: Countering Adversarial SQL Injections with Robust Machine Learning
di: Floris, Giuseppe, et al.
Pubblicazione: (2023)

SLVR: Securely Leveraging Client Validation for Robust Federated Learning
di: Choi, Jihye, et al.
Pubblicazione: (2025)

FedRE: Robust and Effective Federated Learning with Privacy Preference
di: Xiao, Tianzhe, et al.
Pubblicazione: (2025)

Learning Robust and Privacy-Preserving Representations via Information Theory
di: Zhang, Binghui, et al.
Pubblicazione: (2024)

Confundo: Learning to Generate Robust Poison for Practical RAG Systems
di: Hu, Haoyang, et al.
Pubblicazione: (2026)

Early-Stage Anomaly Detection: A Study of Model Performance on Complete vs. Partial Flows
di: Pekar, Adrian, et al.
Pubblicazione: (2024)

Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients
di: Cundy, Chris, et al.
Pubblicazione: (2020)

FedRDF: A Robust and Dynamic Aggregation Function against Poisoning Attacks in Federated Learning
di: Campos, Enrique Mármol, et al.
Pubblicazione: (2024)

Lower Bounds for Public-Private Learning under Distribution Shift
di: Setlur, Amrith, et al.
Pubblicazione: (2025)

FRAME : Comprehensive Risk Assessment Framework for Adversarial Machine Learning Threats
di: Shapira, Avishag, et al.
Pubblicazione: (2025)