Image de couverture de livre

AttackGNN: Red-Teaming GNNs in Hardware Security Using Reinforcement Learning

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Gohil, Vasudev, Patnaik, Satwik, Kalathil, Dileep, Rajendran, Jeyavijayan
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning Cryptography and Security
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

LLMPirate: LLMs for Black-box Hardware IP Piracy
par: Gohil, Vasudev, et autres
Publié: (2024)

ReFuzz: Reusing Tests for Processor Fuzzing with Contextual Bandits
par: Chen, Chen, et autres
Publié: (2025)

Effective and Efficient Jailbreaks of Black-Box LLMs with Cross-Behavior Attacks
par: Gohil, Vasudev
Publié: (2025)

Leveraging Reinforcement Learning in Red Teaming for Advanced Ransomware Attack Simulations
par: Wang, Cheng, et autres
Publié: (2024)

Security Concerns in Quantum Machine Learning as a Service
par: Kundu, Satwik, et autres
Publié: (2024)

PISmith: Reinforcement Learning-based Red Teaming for Prompt Injection Defenses
par: Yin, Chenlong, et autres
Publié: (2026)

TROJAN-GUARD: Hardware Trojans Detection Using GNN in RTL Designs
par: Thorat, Kiran, et autres
Publié: (2025)

Beyond Random Inputs: A Novel ML-Based Hardware Fuzzing
par: Rostami, Mohamadreza, et autres
Publié: (2024)

Co-RedTeam: Orchestrated Security Discovery and Exploitation with LLM Agents
par: He, Pengfei, et autres
Publié: (2026)

Adversarial Threats in Quantum Machine Learning: A Survey of Attacks and Defenses
par: Ghosh, Archisman, et autres
Publié: (2025)

Evaluating Efficacy of Model Stealing Attacks and Defenses on Quantum Neural Networks
par: Kundu, Satwik, et autres
Publié: (2024)

Label Inference Attacks against Node-level Vertical Federated GNNs
par: Arazzi, Marco, et autres
Publié: (2023)

Benchmarking GNNs Using Lightning Network Data
par: Feichtinger, Rainer, et autres
Publié: (2024)

Fine-tuning is Not Fine: Mitigating Backdoor Attacks in GNNs with Limited Clean Data
par: Zhang, Jiale, et autres
Publié: (2025)

CryptGNN: Enabling Secure Inference for Graph Neural Networks
par: Sen, Pritam, et autres
Publié: (2025)

GRAPHTEXTACK: A Realistic Black-Box Node Injection Attack on LLM-Enhanced GNNs
par: Ma, Jiaji, et autres
Publié: (2025)

GRID: Protecting Training Graph from Link Stealing Attacks on GNN Models
par: Lou, Jiadong, et autres
Publié: (2025)

GNN-Based Code Annotation Logic for Establishing Security Boundaries in C Code
par: Gadey, Varun, et autres
Publié: (2024)

PrivGNN: High-Performance Secure Inference for Cryptographic Graph Neural Networks
par: Wang, Fuyi, et autres
Publié: (2025)

SecureLearn -- An Attack-agnostic Defense for Multiclass Machine Learning Against Data Poisoning Attacks
par: Paracha, Anum, et autres
Publié: (2025)

Fuzzerfly Effect: Hardware Fuzzing for Memory Safety
par: Rostami, Mohamadreza, et autres
Publié: (2024)

Confidential Computing for Cloud Security: Exploring Hardware based Encryption Using Trusted Execution Environments
par: Agarwal, Dhruv Deepak, et autres
Publié: (2025)

Attack Atlas: A Practitioner's Perspective on Challenges and Pitfalls in Red Teaming GenAI
par: Rawat, Ambrish, et autres
Publié: (2024)

GNNBleed: Inference Attacks to Unveil Private Edges in Graphs with Realistic Access to GNN Models
par: Song, Zeyu, et autres
Publié: (2023)

Red Teaming with Artificial Intelligence-Driven Cyberattacks: A Scoping Review
par: Al-Azzawi, Mays, et autres
Publié: (2025)

Uncovering Attacks and Defenses in Secure Aggregation for Federated Deep Learning
par: Zhang, Yiwei, et autres
Publié: (2024)

Covert Attacks on Machine Learning Training in Passively Secure MPC
par: Jagielski, Matthew, et autres
Publié: (2025)

Adversarial Inception Backdoor Attacks against Reinforcement Learning
par: Rathbun, Ethan, et autres
Publié: (2024)

Local Environment Poisoning Attacks on Federated Reinforcement Learning
par: Ma, Evelyn, et autres
Publié: (2023)

Enhancing Network Security: A Hybrid Approach for Detection and Mitigation of Distributed Denial-of-Service Attacks Using Machine Learning
par: Shohan, Nizo Jaman, et autres
Publié: (2025)

From Firewalls to Frontiers: AI Red-Teaming is a Domain-Specific Evolution of Cyber Red-Teaming
par: Sinha, Anusha, et autres
Publié: (2025)

Evaluating Differential Privacy Against Membership Inference in Federated Learning: Insights from the NIST Genomics Red Team Challenge
par: Bertoli, Gustavo de Carvalho
Publié: (2026)

RoBCtrl: Attacking GNN-Based Social Bot Detectors via Reinforced Manipulation of Bots Control Interaction
par: Yang, Yingguang, et autres
Publié: (2025)

Persona-Conditioned Adversarial Prompting: Multi-Identity Red-Teaming for Adversarial Discovery and Mitigation
par: Morasso, Cristian, et autres
Publié: (2026)

Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack
par: Meng, Nicole, et autres
Publié: (2024)

Enhancing Security in Deep Reinforcement Learning: A Comprehensive Survey on Adversarial Attacks and Defenses
par: Yichao, Wu, et autres
Publié: (2025)

Interpreting GNN-based IDS Detections Using Provenance Graph Structural Features
par: Mukherjee, Kunal, et autres
Publié: (2023)

Disttack: Graph Adversarial Attacks Toward Distributed GNN Training
par: Zhang, Yuxiang, et autres
Publié: (2024)

Can In-Context Reinforcement Learning Recover From Reward Poisoning Attacks?
par: Sasnauskas, Paulius, et autres
Publié: (2025)

Red Teaming GPT-4V: Are GPT-4V Safe Against Uni/Multi-Modal Jailbreak Attacks?
par: Chen, Shuo, et autres
Publié: (2024)