Cybersecurity remains a strategic technological area at Gradiant. We focus on protecting data, systems, and critical infrastructures against constantly evolving digital threats. We develop advanced solutions to identify cyberthreats and respond to incidents through real-time monitoring, intelligent detection, and automated mitigation.
Our portfolio includes encryption, access control, differential privacy, and federated learning, ensuring secure and privacy-preserving environments.
We use User and Entity Behavior Analytics (UEBA), process mining, and reinforcement learning to detect anomalous behavior and anticipate attacks.
Secure communication protocols, both standardized and ad-hoc, along with digital skills training based on Security by Design principles, are key pillars of our approach.
The increasing sophistication of digital attacks requires a proactive approach to early threat detection. At Gradiant, we develop technologies that go beyond simple monitoring by incorporating User and Entity Behavior Analytics (UEBA), process mining, and reinforcement learning to identify anomalous patterns that may signal attacks before they occur. Our solutions rely on advanced anonymization, differential privacy, and Privacy-Preserving Machine Learning (PPML), ensuring data protection even during analysis.
Detecting an attack in time is essential, but equally important is having an effective and automated response. At Gradiant, we research and develop solutions that analyze, contain, and mitigate security incidents in real time, ensuring the continuity of critical services. Our platforms apply Security Data Analytics, deep learning, and multi-agent models to classify alerts and coordinate adaptive defensive strategies. We combine secure communication protocols, advanced encryption, and confidential... Continue reading
