One Article Review
| Source |  Checkpoint |
|---|---|
| Identifiant | 8611727 |
| Date de publication | 2024-11-15 13:00:02 (vue: 2024-11-15 14:07:55) |
| Titre | 5G network AI models: Threats and Mitigations |
| Texte | >Modern communications networks are increasingly reliant on the use of AI models for enhancing the performance, reliability and security of their offerings. 5G networks especially, with a landscape of service-based architecture, increasingly use AI models for real-time data processing, predictive maintenance and traffic optimization. Large volumes of network data, user behavior data and device interactions are analyzed more thoroughly and quickly than can ever be possible without AI. AI-driven traffic management models dynamically allocate resources based on demand, reducing latency and improving user experience. AI can also be used to enhance Defense communications infrastructure, coordinating non-terrestrial networks with air/ground/sea assets […]
>Modern communications networks are increasingly reliant on the use of AI models for enhancing the performance, reliability and security of their offerings. 5G networks especially, with a landscape of service-based architecture, increasingly use AI models for real-time data processing, predictive maintenance and traffic optimization. Large volumes of network data, user behavior data and device interactions are analyzed more thoroughly and quickly than can ever be possible without AI. AI-driven traffic management models dynamically allocate resources based on demand, reducing latency and improving user experience. AI can also be used to enhance Defense communications infrastructure, coordinating non-terrestrial networks with air/ground/sea assets […] |
| Notes | ★★ |
| Envoyé | Oui |
| Condensat | >modern air/ground/sea allocate also analyzed architecture are assets based behavior can communications coordinating data defense demand device driven dynamically enhance enhancing especially ever experience improving increasingly infrastructure interactions landscape large latency maintenance management mitigations models models: more network networks non offerings optimization performance possible predictive processing quickly real reducing reliability reliant resources security service terrestrial than thoroughly threats time traffic use used user volumes without |
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