Image de couverture de livre

AMDS: Attack-Aware Multi-Stage Defense System for Network Intrusion Detection with Two-Stage Adaptive Weight Learning

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Olukola, Oluseyi, Rahimi, Nick
Format:	Preprint
Publié:	2026
Sujets:	Cryptography and Security Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Adversarial Machine Learning for Robust Password Strength Estimation
par: Jha, Pappu, et autres
Publié: (2025)

Pedagogical Safety in Educational Reinforcement Learning: Formalizing and Detecting Reward Hacking in AI Tutoring Systems
par: Olukola, Oluseyi, et autres
Publié: (2026)

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

FAST-IDS: A Fast Two-Stage Intrusion Detection System with Hybrid Compression for Real-Time Threat Detection in Connected and Autonomous Vehicles
par: S, Devika, et autres
Publié: (2025)

Multi-Stage Prompt Inference Attacks on Enterprise LLM Systems
par: Balashov, Andrii, et autres
Publié: (2025)

DeepStage: Learning Autonomous Defense Policies Against Multi-Stage APT Campaigns
par: Phan, Trung V., et autres
Publié: (2026)

Multi-agent Reinforcement Learning-based Network Intrusion Detection System
par: Tellache, Amine, et autres
Publié: (2024)

Enhancing Network Intrusion Detection Systems: A Multi-Layer Ensemble Approach to Mitigate Adversarial Attacks
par: Soltani, Nasim, et autres
Publié: (2026)

DeepXplain: XAI-Guided Autonomous Defense Against Multi-Stage APT Campaigns
par: Phan, Trung V., et autres
Publié: (2026)

MC-CPO: Mastery-Conditioned Constrained Policy Optimization
par: Olukola, Oluseyi, et autres
Publié: (2026)

TEAM: Temporal Adversarial Examples Attack Model against Network Intrusion Detection System Applied to RNN
par: Liu, Ziyi, et autres
Publié: (2024)

Resource-Aware Deployment Optimization for Collaborative Intrusion Detection in Layered Networks
par: Gómez, André García, et autres
Publié: (2026)

Eclectic Rule Extraction for Explainability of Deep Neural Network based Intrusion Detection Systems
par: Ables, Jesse, et autres
Publié: (2024)

MCP-Guard: A Multi-Stage Defense-in-Depth Framework for Securing Model Context Protocol in Agentic AI
par: Xing, Wenpeng, et autres
Publié: (2025)

Deep Learning-based Intrusion Detection Systems: A Survey
par: Xu, Zhiwei, et autres
Publié: (2025)

XAI-based Feature Selection for Improved Network Intrusion Detection Systems
par: Arreche, Osvaldo, et autres
Publié: (2024)

Robustness Analysis of Machine Learning Models for IoT Intrusion Detection Under Data Poisoning Attacks
par: Wulnye, Fortunatus Aabangbio, et autres
Publié: (2026)

A Survey for Deep Reinforcement Learning Based Network Intrusion Detection
par: Yang, Wanrong, et autres
Publié: (2024)

Are We There Yet? Unraveling the State-of-the-Art Graph Network Intrusion Detection Systems
par: Wang, Chenglong, et autres
Publié: (2025)

Payload-Aware Intrusion Detection with CMAE and Large Language Models
par: Kim, Yongcheol, et autres
Publié: (2025)

IRSDA: An Agent-Orchestrated Framework for Enterprise Intrusion Response
par: Panigrahi, Damodar, et autres
Publié: (2025)

PenTiDef: Decentralized Federated Intrusion Detection System with Differential Privacy and Latent-Space Defense via Blockchain Coordination in IIoT
par: Duy, Phan The, et autres
Publié: (2026)

FLTG: Byzantine-Robust Federated Learning via Angle-Based Defense and Non-IID-Aware Weighting
par: Wen, Yanhua, et autres
Publié: (2025)

Problem space structural adversarial attacks for Network Intrusion Detection Systems based on Graph Neural Networks
par: Venturi, Andrea, et autres
Publié: (2024)

TED-LaST: Towards Robust Backdoor Defense Against Adaptive Attacks
par: Mo, Xiaoxing, et autres
Publié: (2025)

Defenses Against Prompt Attacks Learn Surface Heuristics
par: Li, Shawn, et autres
Publié: (2026)

Strengthening Network Intrusion Detection in IoT Environments with Self-Supervised Learning and Few Shot Learning
par: Atitallah, Safa Ben, et autres
Publié: (2024)

Adversarial Machine Learning: Attacks, Defenses, and Open Challenges
par: Jha, Pranav K
Publié: (2025)

MA-IDS: Multi-Agent RAG Framework for IoT Network Intrusion Detection with an Experience Library
par: Islam, Md Shamimul, et autres
Publié: (2026)

An Investigation into the Performance of Non-Contrastive Self-Supervised Learning Methods for Network Intrusion Detection
par: Fard, Hamed, et autres
Publié: (2025)

Towards Adapting Federated & Quantum Machine Learning for Network Intrusion Detection: A Survey
par: Chaudhary, Devashish, et autres
Publié: (2025)

DNN-Defender: A Victim-Focused In-DRAM Defense Mechanism for Taming Adversarial Weight Attack on DNNs
par: Zhou, Ranyang, et autres
Publié: (2023)

Surviving the Unseen: Predictive Defense for Novel Multi-Turn Multimodal Attacks
par: You, Doohee
Publié: (2026)

Latent Adversarial Detection: Adaptive Probing of LLM Activations for Multi-Turn Attack Detection
par: Kulkarni, Prashant
Publié: (2026)

LiPar: A Lightweight Parallel Learning Model for Practical In-Vehicle Network Intrusion Detection
par: Zhang, Aiheng, et autres
Publié: (2023)

Targeted Adversarial Traffic Generation : Black-box Approach to Evade Intrusion Detection Systems in IoT Networks
par: Debicha, Islam, et autres
Publié: (2026)

A Life-long Learning Intrusion Detection System for 6G-Enabled IoV
par: korba, Abdelaziz Amara, et autres
Publié: (2024)

Behavior-Aware and Generalizable Defense Against Black-Box Adversarial Attacks for ML-Based IDS
par: Ennaji, Sabrine, et autres
Publié: (2025)

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

FedSecurity: Benchmarking Attacks and Defenses in Federated Learning and Federated LLMs
par: Han, Shanshan, et autres
Publié: (2023)