Copertina

Deep Learning for Contextualized NetFlow-Based Network Intrusion Detection: Methods, Data, Evaluation and Deployment

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Mahdaouy, Abdelkader El, Yahia, Issam Ait, Oualil, Soufiane, Berrada, Ismail
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Cryptography and Security C.2; I.2
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

DomURLs_BERT: Pre-trained BERT-based Model for Malicious Domains and URLs Detection and Classification
di: Mahdaouy, Abdelkader El, et al.
Pubblicazione: (2024)

Deep Learning-Based Intrusion Detection for Automotive Ethernet: Evaluating & Optimizing Fast Inference Techniques for Deployment on Low-Cost Platform
di: Carmo, Pedro R. X., et al.
Pubblicazione: (2025)

PoTS: Proof-of-Training-Steps for Backdoor Detection in Large Language Models
di: Seddik, Issam, et al.
Pubblicazione: (2025)

Anomaly Detection in IEC-61850 GOOSE Networks: Evaluating Unsupervised and Temporal Learning for Real-Time Intrusion Detection
di: Moore, Joseph
Pubblicazione: (2026)

Temporal Analysis of NetFlow Datasets for Network Intrusion Detection Systems
di: Luay, Majed, et al.
Pubblicazione: (2025)

NatGVD: Natural Adversarial Example Attack towards Graph-based Vulnerability Detection
di: Rath, Avilash, et al.
Pubblicazione: (2025)

Systematic Evaluation of Synthetic Data Augmentation for Multi-class NetFlow Traffic
di: Wolf, Maximilian, et al.
Pubblicazione: (2024)

MathLedger: A Verifiable Learning Substrate with Ledger-Attested Feedback
di: Abdullah, Ismail Ahmad
Pubblicazione: (2025)

Prompted Contextual Vectors for Spear-Phishing Detection
di: Nahmias, Daniel, et al.
Pubblicazione: (2024)

Evaluating the Robustness of Large Language Model Safety Guardrails Against Adversarial Attacks
di: Young, Richard J.
Pubblicazione: (2025)

Binary Image-Based Intrusion Detection for Operational Technology Networks: Extending the SPHBI Methodology from IoT to Modbus TCP
di: Omar, Aamir
Pubblicazione: (2026)

Prismo: A Decision Support System for Privacy-Preserving ML Framework Selection
di: Njungle, Nges Brian, et al.
Pubblicazione: (2025)

Adaptive alert prioritisation in security operations centres via learning to defer with human feedback
di: Jalalvand, Fatemeh, et al.
Pubblicazione: (2025)

A Protocol-Language Model for Network Intrusion (Without Deep Packet Inspection)
di: Sharma, Vivek Kumar
Pubblicazione: (2026)

AI/ML for 5G and Beyond Cybersecurity
di: Pirbhulal, Sandeep, et al.
Pubblicazione: (2025)

Mitigating Trojanized Prompt Chains in Educational LLM Use Cases: Experimental Findings and Detection Tool Design
di: Charles, Richard M., et al.
Pubblicazione: (2025)

Towards Deep Encrypted Training: Low-Latency, Memory-Efficient, and High-Throughput Inference for Privacy-Preserving Neural Networks
di: Njungle, Nges Brian, et al.
Pubblicazione: (2026)

PromptSAM+: Malware Detection based on Prompt Segment Anything Model
di: Wei, Xingyuan, et al.
Pubblicazione: (2024)

SoK: A Review of Differentially Private Linear Models For High-Dimensional Data
di: Khanna, Amol, et al.
Pubblicazione: (2024)

Enhanced Web Payload Classification Using WAMM: An AI-Based Framework for Dataset Refinement and Model Evaluation
di: Osama, Heba, et al.
Pubblicazione: (2025)

Today's Cat Is Tomorrow's Dog: Accounting for Time-Based Changes in the Labels of ML Vulnerability Detection Approaches
di: Paramitha, Ranindya, et al.
Pubblicazione: (2025)

LIPPEN: A Lightweight In-Place Pointer Encryption Architecture for Pointer Integrity
di: Iravani, Erfan, et al.
Pubblicazione: (2026)

MalDataGen: A Modular Framework for Synthetic Tabular Data Generation in Malware Detection
di: Paim, Kayua Oleques, et al.
Pubblicazione: (2025)

DWFS-Obfuscation: Dynamic Weighted Feature Selection for Robust Malware Familial Classification under Obfuscation
di: Wei, Xingyuan, et al.
Pubblicazione: (2025)

POISONCRAFT: Practical Poisoning of Retrieval-Augmented Generation for Large Language Models
di: Shao, Yangguang, et al.
Pubblicazione: (2025)

Lightweight LLMs for Network Attack Detection in IoT Networks
di: Sudasinghe, Piyumi Bhagya, et al.
Pubblicazione: (2026)

MaPPing Your Model: Assessing the Impact of Adversarial Attacks on LLM-based Programming Assistants
di: Heibel, John, et al.
Pubblicazione: (2024)

Mitigating the Impact of Malware Evolution on API Sequence-based Windows Malware Detector
di: Wei, Xingyuan, et al.
Pubblicazione: (2024)

Reflection of Federal Data Protection Standards on Cloud Governance
di: Dye, Olga, et al.
Pubblicazione: (2024)

Evaluating Membership Inference Attacks in heterogeneous-data setups
di: van Dartel, Bram, et al.
Pubblicazione: (2025)

Risk-Calibrated Bayesian Streaming Intrusion Detection with SRE-Aligned Decisions
di: Youssef, Michel
Pubblicazione: (2025)

Efficient LLM Safety Evaluation through Multi-Agent Debate
di: Lin, Dachuan, et al.
Pubblicazione: (2025)

Multiclass Classification Procedure for Detecting Attacks on MQTT-IoT Protocol
di: Alaiz-Moreton, Hector, et al.
Pubblicazione: (2024)

Towards Autonomous Cybersecurity: An Intelligent AutoML Framework for Autonomous Intrusion Detection
di: Yang, Li, et al.
Pubblicazione: (2024)

Power-Softmax: Towards Secure LLM Inference over Encrypted Data
di: Zimerman, Itamar, et al.
Pubblicazione: (2024)

David and Goliath: An Empirical Evaluation of Attacks and Defenses for QNNs at the Deep Edge
di: Costa, Miguel, et al.
Pubblicazione: (2024)

FEDLAD: Federated Evaluation of Deep Leakage Attacks and Defenses
di: Baglin, Isaac, et al.
Pubblicazione: (2024)

Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning
di: Garov, Kostadin, et al.
Pubblicazione: (2023)

A Novel Bifurcation Method for Observation Perturbation Attacks on Reinforcement Learning Agents: Load Altering Attacks on a Cyber Physical Power System
di: Broda-Milian, Kiernan, et al.
Pubblicazione: (2024)

Inverting Cryptographic Hash Functions via Cube-and-Conquer
di: Zaikin, Oleg
Pubblicazione: (2022)