Neural-X is at the core of Intelligent threat detection and defense. Threat Intelligence is organized, analyzed and refined information that enables organizations to understand, assess and prevent against known and severe risks from external sources.

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Deep learning is a complex element of machine learning inspired by the function of interconnecting neurons in the human brain. It is part of Artificial Intelligence and is considered an evolution of Machine Learning. As the names implies, it teaches itself by observing and processing massive amounts of data, allowing it to make more accurate & faster predictions.

One of the ways Neural-X uses deep learning is to break down cryptic domain names into vectors that are machine readable. In-depth analysis of vector association detects domain names used by malware of similar families. Over time, the deep learning function will begin to operate and learn independently – thus maintaining a proactive approach to malware detection, identification and elimination within Neural-X.

Hackers are becoming more sophisticated by abandoning fixed IP addresses and use dynamic domain names instead. These cryptic domain names are used to connect botnets to their controller using secret algorithms. They are notoriously difficult to detect because DNS queries behave similarly to the average user. Neural-X uses advanced flow analysis, visual calculation and deep learning technology to uncover botnets.

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