Time
2 months
Location
USA
Sector
Cybersecurity
Description
A cybersecurity company needed a solution to analyze and classify a large amount of data collected from the internal networks of their customers. The objective was to use a machine learning model to achieve this, requiring a deep understanding of web applications and a scientific approach.
Solution
The solution involved the collection of a data set and the development of a machine learning solution for the company to use as part of their detection service. The result was a highly-scalable, reliable, fault-tolerant system designed for data collection, server fingerprinting, web crawling, indexing, and real-time semantic analysis of 10 million web pages per day.
Results
The newly developed system achieved an accuracy rate of 97%. It optimized the risk assessment process for the client, enabling them to enhance their business operations.
“Good work, will use again”
Richard Wells, CTO of ThreatInformer, London