Buchumschlag

No Data? No Problem: Synthesizing Security Graphs for Better Intrusion Detection

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Huang, Yi, Li, Shaofei, Guo, Yao, Chen, Xiangqun, Li, Ding, Hassan, Wajih Ul
Format:	Preprint
Veröffentlicht:	2025
Schlagworte:	Cryptography and Security
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

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

Query Provenance Analysis: Efficient and Robust Defense against Query-based Black-box Attacks
von: Li, Shaofei, et al.
Veröffentlicht: (2024)

PromoGuardian: Detecting Promotion Abuse Fraud with Multi-Relation Fused Graph Neural Networks
von: Li, Shaofei, et al.
Veröffentlicht: (2025)

HADES: Detecting Active Directory Attacks via Whole Network Provenance Analytics
von: Liu, Qi, et al.
Veröffentlicht: (2024)

Towards Small Language Models for Security Query Generation in SOC Workflows
von: Muzammil, Saleha, et al.
Veröffentlicht: (2025)

Connect the Dots: Knowledge Graph-Guided Crawler Attack on Retrieval-Augmented Generation Systems
von: Yao, Mengyu, et al.
Veröffentlicht: (2026)

Rethinking Tamper-Evident Logging: A High-Performance, Co-Designed Auditing System
von: Zhao, Rui, et al.
Veröffentlicht: (2025)

Accurate and Scalable Detection and Investigation of Cyber Persistence Threats
von: Liu, Qi, et al.
Veröffentlicht: (2024)

Moss: Proxy Model-based Full-Weight Aggregation in Federated Learning with Heterogeneous Models
von: Cai, Yifeng, et al.
Veröffentlicht: (2025)

Enhancing SCADA Security: Developing a Host-Based Intrusion Detection System to Safeguard Against Cyberattacks
von: Sen, Omer, et al.
Veröffentlicht: (2024)

Advancing CAN Network Security through RBM-Based Synthetic Attack Data Generation for Intrusion Detection Systems
von: Li, Huacheng, et al.
Veröffentlicht: (2025)

Entente: Cross-silo Intrusion Detection on Network Log Graphs with Federated Learning
von: Xu, Jiacen, et al.
Veröffentlicht: (2025)

GraphFaaS: Serverless GNN Inference for Burst-Resilient, Real-Time Intrusion Detection
von: Wang, Lingzhi, et al.
Veröffentlicht: (2025)

TEESlice: Protecting Sensitive Neural Network Models in Trusted Execution Environments When Attackers have Pre-Trained Models
von: Li, Ding, et al.
Veröffentlicht: (2024)

Intrusion Detection System Using Deep Learning for Network Security
von: Chatterjee, Soham, et al.
Veröffentlicht: (2025)

A PUF-Based Security Framework for Fault and Intrusion Detection
von: Oun, Ahmed, et al.
Veröffentlicht: (2026)

ACTISM: Threat-informed Dynamic Security Modelling for Automotive Systems
von: Huang, Shaofei, et al.
Veröffentlicht: (2024)

I Can Tell Your Secrets: Inferring Privacy Attributes from Mini-app Interaction History in Super-apps
von: Cai, Yifeng, et al.
Veröffentlicht: (2025)

Security Modelling for Cyber-Physical Systems: A Systematic Literature Review
von: Huang, Shaofei, et al.
Veröffentlicht: (2024)

Empowering IoT Security: On-Device Intrusion Detection in Resource Constrained Devices
von: Ieropoulos, Vasilis, et al.
Veröffentlicht: (2026)

AegisMCP: Online Graph Intrusion Detection for Tool-Augmented LLMs on Edge Devices
von: Zhan, Zhonghao, et al.
Veröffentlicht: (2025)

SoK: Harmonizing Attack Graphs and Intrusion Detection Systems
von: Agiollo, Andrea, et al.
Veröffentlicht: (2026)

Enhancing Automotive Security with a Hybrid Approach towards Universal Intrusion Detection System
von: Islam, Md Rezanur, et al.
Veröffentlicht: (2025)

KnowHow: Automatically Applying High-Level CTI Knowledge for Interpretable and Accurate Provenance Analysis
von: Meng, Yuhan, et al.
Veröffentlicht: (2025)

CITADEL: Continual Anomaly Detection for Enhanced Learning in IoT Intrusion Detection
von: Li, Elvin, et al.
Veröffentlicht: (2025)

Incorporating Gradients to Rules: Towards Lightweight, Adaptive Provenance-based Intrusion Detection
von: Wang, Lingzhi, et al.
Veröffentlicht: (2024)

How Far Should We Need to Go : Evaluate Provenance-based Intrusion Detection Systems in Industrial Scenarios
von: Xiao, Yue, et al.
Veröffentlicht: (2026)

Evaluating MCC for Low-Frequency Cyberattack Detection in Imbalanced Intrusion Detection Data
von: Thiyagarajan, Prameshwar, et al.
Veröffentlicht: (2025)

IDGraphs: Intrusion Detection and Analysis Using Stream Compositing
von: Ren, Pin, et al.
Veröffentlicht: (2025)

ContextBuddy: AI-Enhanced Contextual Insights for Security Alert Investigation (Applied to Intrusion Detection)
von: Singh, Ronal, et al.
Veröffentlicht: (2025)

MirGuard: Towards a Robust Provenance-based Intrusion Detection System Against Graph Manipulation Attacks
von: Sang, Anyuan, et al.
Veröffentlicht: (2025)

Simplicity over Complexity: An ARN-Based Intrusion Detection Method for Industrial Control Network
von: Liu, Ziyi, et al.
Veröffentlicht: (2024)

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

SeeWasm: An Efficient and Fully-Functional Symbolic Execution Engine for WebAssembly Binaries
von: He, Ningyu, et al.
Veröffentlicht: (2024)

VAEMax: Open-Set Intrusion Detection based on OpenMax and Variational Autoencoder
von: Qiu, Zhiyin, et al.
Veröffentlicht: (2024)

AOC-IDS: Autonomous Online Framework with Contrastive Learning for Intrusion Detection
von: Zhang, Xinchen, et al.
Veröffentlicht: (2024)

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

Machine Learning-Assisted Intrusion Detection for Enhancing Internet of Things Security
von: Esmaeili, Mona, et al.
Veröffentlicht: (2024)

On the Challenges of Holistic Intrusion Detection in ICS
von: Lenz, Stefan, et al.
Veröffentlicht: (2026)

A Robust Multi-Stage Intrusion Detection System for In-Vehicle Network Security using Hierarchical Federated Learning
von: Althunayyan, Muzun, et al.
Veröffentlicht: (2024)