Copertina

A Novel and Practical Universal Adversarial Perturbations against Deep Reinforcement Learning based Intrusion Detection Systems

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zhang, H., Zhang, L., Epiphaniou, G., Maple, C.
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Cryptography and Security Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

A BERT-based Empirical Study of Privacy Policies' Compliance with GDPR
di: Zhang, Lu, et al.
Pubblicazione: (2024)

Deep Learning-based Intrusion Detection Systems: A Survey
di: Xu, Zhiwei, et al.
Pubblicazione: (2025)

TEAM: Temporal Adversarial Examples Attack Model against Network Intrusion Detection System Applied to RNN
di: Liu, Ziyi, et al.
Pubblicazione: (2024)

Multi-agent Reinforcement Learning-based Network Intrusion Detection System
di: Tellache, Amine, et al.
Pubblicazione: (2024)

A Survey for Deep Reinforcement Learning Based Network Intrusion Detection
di: Yang, Wanrong, et al.
Pubblicazione: (2024)

LiPar: A Lightweight Parallel Learning Model for Practical In-Vehicle Network Intrusion Detection
di: Zhang, Aiheng, et al.
Pubblicazione: (2023)

Vision Transformer with Adversarial Indicator Token against Adversarial Attacks in Radio Signal Classifications
di: Zhang, Lu, et al.
Pubblicazione: (2025)

Enhancing Network Intrusion Detection Systems: A Multi-Layer Ensemble Approach to Mitigate Adversarial Attacks
di: Soltani, Nasim, et al.
Pubblicazione: (2026)

Towards a Practical Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via Randomized Smoothing
di: Gibert, Daniel, et al.
Pubblicazione: (2023)

Diffusion-based Adversarial Purification for Intrusion Detection
di: Merzouk, Mohamed Amine, et al.
Pubblicazione: (2024)

WeiDetect: Weibull Distribution-Based Defense against Poisoning Attacks in Federated Learning for Network Intrusion Detection Systems
di: M., Sameera K., et al.
Pubblicazione: (2025)

Joint Universal Adversarial Perturbations with Interpretations
di: Ning, Liang-bo, et al.
Pubblicazione: (2024)

Targeted Adversarial Traffic Generation : Black-box Approach to Evade Intrusion Detection Systems in IoT Networks
di: Debicha, Islam, et al.
Pubblicazione: (2026)

XAI-based Feature Selection for Improved Network Intrusion Detection Systems
di: Arreche, Osvaldo, et al.
Pubblicazione: (2024)

DECEIVE-AFC: Adversarial Claim Attacks against Search-Enabled LLM-based Fact-Checking Systems
di: Ou, Haoran, et al.
Pubblicazione: (2026)

Adversarial Evasion in Non-Stationary Malware Detection: Minimizing Drift Signals through Similarity-Constrained Perturbations
di: Acharya, Pawan, et al.
Pubblicazione: (2026)

A Robust Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via (De)Randomized Smoothing
di: Gibert, Daniel, et al.
Pubblicazione: (2024)

A Life-long Learning Intrusion Detection System for 6G-Enabled IoV
di: korba, Abdelaziz Amara, et al.
Pubblicazione: (2024)

Eclectic Rule Extraction for Explainability of Deep Neural Network based Intrusion Detection Systems
di: Ables, Jesse, et al.
Pubblicazione: (2024)

CSAGC-IDS: A Dual-Module Deep Learning Network Intrusion Detection Model for Complex and Imbalanced Data
di: Zeng, Yifan
Pubblicazione: (2025)

Adversarial Attacks on Reinforcement Learning-based Medical Questionnaire Systems: Input-level Perturbation Strategies and Medical Constraint Validation
di: Liu, Peizhuo
Pubblicazione: (2025)

LEMDA: A Novel Feature Engineering Method for Intrusion Detection in IoT Systems
di: Ghubaish, Ali, et al.
Pubblicazione: (2024)

C-RADAR: A Centralized Deep Learning System for Intrusion Detection in Software Defined Networks
di: Mustafa, Osama, et al.
Pubblicazione: (2024)

Binary and Multi-Class Intrusion Detection in IoT Using Standalone and Hybrid Machine and Deep Learning Models
di: Akif, Md Ahnaf
Pubblicazione: (2025)

Continual Learning with Strategic Selection and Forgetting for Network Intrusion Detection
di: Zhang, Xinchen, et al.
Pubblicazione: (2024)

Adversarial Attacks against Windows PE Malware Detection: A Survey of the State-of-the-Art
di: Ling, Xiang, et al.
Pubblicazione: (2021)

Explainer-guided Targeted Adversarial Attacks against Binary Code Similarity Detection Models
di: Chen, Mingjie, et al.
Pubblicazione: (2025)

Problem space structural adversarial attacks for Network Intrusion Detection Systems based on Graph Neural Networks
di: Venturi, Andrea, et al.
Pubblicazione: (2024)

Enhancing IoT Security with CNN and LSTM-Based Intrusion Detection Systems
di: Gueriani, Afrah, et al.
Pubblicazione: (2024)

AI-Powered Hybrid Intrusion Detection Framework for Cloud Security Using Novel Metaheuristic Optimization
di: Alhusseini, Maryam Mahdi, et al.
Pubblicazione: (2026)

A Spatiotemporal Stealthy Backdoor Attack against Cooperative Multi-Agent Deep Reinforcement Learning
di: Yu, Yinbo, et al.
Pubblicazione: (2024)

AdaDoS: Adaptive DoS Attack via Deep Adversarial Reinforcement Learning in SDN
di: Shao, Wei, et al.
Pubblicazione: (2025)

Adversarial Reinforcement Learning for Detecting False Data Injection Attacks in Vehicular Routing
di: Eghtesad, Taha, et al.
Pubblicazione: (2026)

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

Emoti-Attack: Zero-Perturbation Adversarial Attacks on NLP Systems via Emoji Sequences
di: Zhang, Yangshijie
Pubblicazione: (2025)

Are We There Yet? Unraveling the State-of-the-Art Graph Network Intrusion Detection Systems
di: Wang, Chenglong, et al.
Pubblicazione: (2025)

Towards Adapting Federated & Quantum Machine Learning for Network Intrusion Detection: A Survey
di: Chaudhary, Devashish, et al.
Pubblicazione: (2025)

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

AMDS: Attack-Aware Multi-Stage Defense System for Network Intrusion Detection with Two-Stage Adaptive Weight Learning
di: Olukola, Oluseyi, et al.
Pubblicazione: (2026)

"What is the Problem Space?" Defining Host-space Adversarial Perturbations against Network Intrusion Detection Systems
di: Verkerken, Miel, et al.
Pubblicazione: (2026)