Artificial Intelligence and SIEM: A Revolution for the Security of Private 5G Networks

A Key Issue in Industry 4.0
With digital transformation and the rise of Industry 4.0, private 5G networks are becoming the backbone of connected industrial environments. However, these networks, particularly the N6 interface that connects the heart of 5G to industrial applications, remain exposed to critical vulnerabilities.
To meet these challenges, the integration of artificial intelligence (AI) into SIEM (Security Information and Event Management) solutions is opening innovative prospects for preventing, detecting, and reacting to cyber threats more effectively and accurately.

SIEM: A complete Cybersecurity Solution
A strategic tool
Unlike other security solutions such as SOAR (Security Orchestration, Automation, and Response), EDR (Endpoint Detection and Response) or IDS (Intrusion Detection System), SIEM offers a holistic view of infrastructure security. It collects, centralises and analyses security event logs in real time, enabling teams to identify threats with precision. 

Its strengths:

• Centralisation of logs and events.
• Intelligent data correlation.
• Real-time analysis for proactive detection.
• Automated reporting for compliance.

AI: a performance accelerator for SIEM
Advanced technologies for cyber security
Artificial intelligence is transforming the cybersecurity landscape with technologies capable of detecting anomalies and predicting threats. 

1. Language Models (LLMs) are used to analyse and understand the context of security logs. They identify suspicious behaviour and assist analysts by simplifying decision-making through in-depth contextual analysis.
2. Transformers, the foundation of LLMs, stand out for their ability to detect complex relationships in data flows. These architectures are ideal for :

• Identifying anomalies in industrial data sequences.
• Understanding complex time patterns.
• Anticipating threats before they impact the system. 

By applying these technologies to industrial data flows, SIEM systems become capable of fine-tuned, rapid and adaptive detection.

A Solution Adapted to 5G-mMTC Networks
Proposed architecture
As part of the 5G-mMTC project, we have developed an AI-enhanced SIEM architecture specifically designed for the N6 interface. This solution enables :

• Continuous, real-time monitoring of critical data flows.
• Early detection of anomalies using AI models (Long Short-Term Memory neural network, Transformers).
• Issue precise, context-sensitive alerts. 

Why this approach?
AI applied to SIEM brings tangible benefits:

• Reduction of false positives for more reliable alerts.
• Improved responsiveness through real-time analysis.
• Dynamic adaptation to new threats.
• In-depth data analysis for contextual understanding.

Next steps and outlook
Innovations in Progress
Our teams are currently working on :

• Continuous improvement of AI models with specific industrial data.
• Optimising detection capabilities to anticipate new forms of threat.
• Seamless integration with existing industrial systems. 

A demonstration to come
A full-scale demonstration is planned for the 2nd quarter of 2025, with clear objectives:

• Validate performance in a real industrial environment.
• Evaluate the effectiveness of alerts and 5G integration.
• Demonstrate the added value of an AI-enhanced SIEM architecture.

Conclusion - Proactive and Adaptive Cybersecurity
The combination of SIEM and artificial intelligence meets the security requirements of private 5G networks in a demanding industrial context. This approach, at the heart of the 5G-mMTC project, ensures early detection, proactive prevention and appropriate response to cyber threats.Thanks to advanced AI technologies and a robust architecture, we offer a solution that evolves with threats, securing the industrial infrastructures of today and tomorrow.