How can cloud systems learn to defend themselves

A new generation of institutions safety frameworks-interacting with threats in actual time. Hassan RihanCyber ​​security engineer, at the forefront of this transformation. His action on the predictive defense systems driven by artificial intelligence is to transform the cloud infrastructure protection model. His workforce is implemented in energy and vital environments on a large scale, and has multi -systems response flows and reduce the time to detect the threat by more than 60 %.

Hassan normative framework includes machine learning, behavioral analysis and contextual decision -making. It has the links of the advanced public sector alone as well as those. Its designs focus on the ability to adapt, transparent and speed, which allows original cloud environments to override risk relief and dynamic adaptation with advanced changes in attack patterns. This framework differs from traditional designs in that it is able to expand multi -service expansion, allowing the provision of feedback rings in actual time.

The change in the dynamics of cybersecurity of business comes from the latest and more complex threats present in a cloud distributed environment. Since the non -advanced approach is increasingly fighting the complex attack strategies, there is a change in Focus AI technologies that learn and adapt, strongly dependent on context and government.

Progress in behavioral analyzes, detection of homosexuality, and predictive analysis can create a self -compensation security structure that improves diverse users, infrastructure and constantly advanced threats. Among the most prominent contributors to the applications of modern institutions in which these principles of the system can be applied is Hassan Rihan.