:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Meng, Nicole, Manicke, Caleb, Chen, David, Lao, Yingjie, Ding, Caiwen, Hong, Pengyu, Mahmood, Kaleel
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Cryptography and Security
Online Access:	https://arxiv.org/abs/2411.12071
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Busting the Paper Ballot: Voting Meets Adversarial Machine Learning
by: Mahmood, Kaleel, et al.
Published: (2025)

Attacking the Spike: On the Transferability and Security of Spiking Neural Networks to Adversarial Examples
by: Xu, Nuo, et al.
Published: (2022)

UIBDiffusion: Universal Imperceptible Backdoor Attack for Diffusion Models
by: Han, Yuning, et al.
Published: (2024)

UltraClean: A Simple Framework to Train Robust Neural Networks against Backdoor Attacks
by: Zhao, Bingyin, et al.
Published: (2023)

Certifying Adapters: Enabling and Enhancing the Certification of Classifier Adversarial Robustness
by: Deng, Jieren, et al.
Published: (2024)

VisInject: Disruption != Injection -- A Dual-Dimension Evaluation of Universal Adversarial Attacks on Vision-Language Models
by: Liu, Pang, et al.
Published: (2026)

TROJAN-GUARD: Hardware Trojans Detection Using GNN in RTL Designs
by: Thorat, Kiran, et al.
Published: (2025)

Learning-based Detection of GPS Spoofing Attack for Quadrotors
by: Wang, Pengyu, et al.
Published: (2025)

Leveraging Reinforcement Learning in Red Teaming for Advanced Ransomware Attack Simulations
by: Wang, Cheng, et al.
Published: (2024)

SSNet: A Lightweight Multi-Party Computation Scheme for Practical Privacy-Preserving Machine Learning Service in the Cloud
by: Duan, Shijin, et al.
Published: (2024)

Inf2Guard: An Information-Theoretic Framework for Learning Privacy-Preserving Representations against Inference Attacks
by: Noorbakhsh, Sayedeh Leila, et al.
Published: (2024)

HashVFL: Defending Against Data Reconstruction Attacks in Vertical Federated Learning
by: Qiu, Pengyu, et al.
Published: (2022)

Enhancing Security in Deep Reinforcement Learning: A Comprehensive Survey on Adversarial Attacks and Defenses
by: Yichao, Wu, et al.
Published: (2025)

Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data
by: Lin, Huawei, et al.
Published: (2025)

On the Evidentiary Limits of Membership Inference for Copyright Auditing
by: Ertan, Murat Bilgehan, et al.
Published: (2026)

Short-length Adversarial Training Helps LLMs Defend Long-length Jailbreak Attacks: Theoretical and Empirical Evidence
by: Fu, Shaopeng, et al.
Published: (2025)

AdaPI: Facilitating DNN Model Adaptivity for Efficient Private Inference in Edge Computing
by: Zhou, Tong, et al.
Published: (2024)

Local Environment Poisoning Attacks on Federated Reinforcement Learning
by: Ma, Evelyn, et al.
Published: (2023)

Adversarial Inception Backdoor Attacks against Reinforcement Learning
by: Rathbun, Ethan, et al.
Published: (2024)

Leveraging Optimization for Adaptive Attacks on Image Watermarks
by: Lukas, Nils, et al.
Published: (2023)

Enhancing Adversarial Attacks via Parameter Adaptive Adversarial Attack
by: Jin, Zhibo, et al.
Published: (2024)

Redesigning Traffic Signs to Mitigate Machine-Learning Patch Attacks
by: Shua, Tsufit, et al.
Published: (2024)

Preparing for Kyber in Securing Intelligent Transportation Systems Communications: A Case Study on Fault-Enabled Chosen-Ciphertext Attack
by: Zhang, Kaiyuan, et al.
Published: (2025)

Low-Cost Hard-Label Adversarial Attack with Theoretical Foundations
by: Liu, Jun, et al.
Published: (2026)

Can In-Context Reinforcement Learning Recover From Reward Poisoning Attacks?
by: Sasnauskas, Paulius, et al.
Published: (2025)

BLAST: A Stealthy Backdoor Leverage Attack against Cooperative Multi-Agent Deep Reinforcement Learning based Systems
by: Fang, Jing, et al.
Published: (2025)

Leveraging Soft Prompts for Privacy Attacks in Federated Prompt Tuning
by: Nguyen, Quan Minh, et al.
Published: (2026)

Malware Classification Leveraging NLP & Machine Learning for Enhanced Accuracy
by: Gond, Bishwajit Prasad, et al.
Published: (2025)

FHE-Agent: Automating CKKS Configuration for Practical Encrypted Inference via an LLM-Guided Agentic Framework
by: Xu, Nuo, et al.
Published: (2025)

SleeperNets: Universal Backdoor Poisoning Attacks Against Reinforcement Learning Agents
by: Rathbun, Ethan, et al.
Published: (2024)

AttackGNN: Red-Teaming GNNs in Hardware Security Using Reinforcement Learning
by: Gohil, Vasudev, et al.
Published: (2024)

Distributional Black-Box Model Inversion Attack with Multi-Agent Reinforcement Learning
by: Bao, Huan, et al.
Published: (2024)

Online Poisoning Attack Against Reinforcement Learning under Black-box Environments
by: Li, Jianhui, et al.
Published: (2024)

Distilling Adversarial Robustness Using Heterogeneous Teachers
by: Deng, Jieren, et al.
Published: (2024)

Beware Untrusted Simulators -- Reward-Free Backdoor Attacks in Reinforcement Learning
by: Rathbun, Ethan, et al.
Published: (2026)

TooBadRL: Trigger Optimization to Boost Effectiveness of Backdoor Attacks on Deep Reinforcement Learning
by: Zhang, Mingxuan, et al.
Published: (2025)

Noise as a Probe: Membership Inference Attacks on Diffusion Models Leveraging Initial Noise
by: Lian, Puwei, et al.
Published: (2026)

Leveraging VAE-Derived Latent Spaces for Enhanced Malware Detection with Machine Learning Classifiers
by: Ajayi, Bamidele, et al.
Published: (2025)

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning
by: Chen, Depeng, et al.
Published: (2024)

Safeguarding Graph Neural Networks against Topology Inference Attacks
by: Fu, Jie, et al.
Published: (2025)