The Darktrace cyber solution
The Enterprise Immune System is uniquely capable of ‘self’ learning and adaptively understanding what represents real threat within complex, changing environments.
Darktrace’s unique technology provides Maritime corporations with true cyber intelligence, leveraging the most advanced technology and expertise in the world today to stop damaging cyber-attack.
Installation and operation
A single Darktrace appliance can be installed in 1-2 hours, passive data collection commences immediately and the system begins analysing and modelling the network data.
The threat visualizer is a unique online interface that provides a real time operational overview of the organisations entire network. The threat visualizer is intuitive and provides a platform to highlight threats in real time. See the graphic user interface (GUI) video below.
The Enterprise Immune System technology is powered by a new branch of Bayesian probability theory developed at Cambridge University in the United Kingdom. This ground breaking technology is unique in its ability to adapt to changing environments based on the activity and information it sees. The technology is able to spot fresh threats that have not yet been seen including insider attacks.
Our technologists are world experts in signal processing and machine learning and have experience deploying some of the world’s largest software systems, dealing with highly sensitive data while complying with changing standards. Over the past decade, the team has worked to protect critical information assets and intellectual property in an increasingly hostile global environment. Working at the forefront of national security they learned how to observe and monitor behaviours to determine what is normal and abnormal. By analysing subtle information, we were able to make decisions about when to act on relevant threats.
With our affiliates in the Middle East, Southeast Asia and Europe Clearwater is able to deliver a range of practical cyber solutions to the maritime industry including:
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