Author

Marius Portmann

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Review Open access 2026

Programmable Data Planes for AI Infrastructure Readiness: Abstractions, Accelerators, and Systems—A Survey

This survey provides a detailed examination of the practical capability boundaries of prominent programmable data plane technologies, including Protocol-Oblivious Forwarding (POF), Programming Protocol-independent Packet Processors (P4), the extended Berkeley Packet Filter (eBPF), and the Network Programming Language (...

Yaying Chen, S. Layeghy, Marius Portmann · IEEE Access · 0 citations

Preprint Aug 2026

LLMs for Zero-Shot Threat Detection via Structured Risk Indicators

It is shown that the quality of the generated risk indicators is the main driver of zero-shot cyber threat detection performance, and that retrieval mainly benefits weaker LLMs by generating more discriminative risk indicators, whereas stronger models achieve comparable performance without retrieved context.

A. Al-Ghamdi, S. Layeghy, Marius Portmann · 0 citations

#machine learning Open access Mar 2025

Time Matters: Temporal NetFlow Features for ML-Based Network Intrusion Detection

The results demonstrate that augmenting conventional flow features with temporal information yields consistent gains; binary detection improves by up to 3% in F1 score, while macro-averaged multi-class F1 increases by approximately 27%, with the most significant improvements occurring in attack classes with pronounced...

Majed Luay, S. Layeghy, Niloufar Noorbin et al. · IEEE Access · 21 citations