Cybersecurity & Security
Fight advanced threats by sharing intelligence—without sharing data
Use Cases
Collective Threat Detection
Unify signals from multiple organizations to detect complex attack patterns without exposing internal systems.
Stronger Defense Models Across Companies
Train federated models on cross-company data to prevent more sophisticated attacks.
Proactive Ransomware Prevention
Identify suspicious behavior early without needing to share internal logs.
Protection of Critical Infrastructures
Collaborate with other entities to secure essential environments while maintaining full control over your data.
Scalable and Private Object Detection with Federated Learning
This study evaluates training object detection models (YOLOv8) in privacy-sensitive environments without sharing data or metadata. Sherpa.ai’s Horizontal Federated Learning significantly outperforms local baselines, proving its effectiveness while ensuring full data privacy.
Collaborative and Private Ransomware Detection with Federated Learning
This study shows how organizations can collaboratively detect ransomware using Horizontal Federated Learning with Sherpa.ai. The federated model outperforms locally trained models and closely matches centralized performance, all while preserving privacy and avoiding data sharing.
