Cybersecurity is the fastest growing segment of the security industry. Cyberattacks can have catastrophic results in transportation, healthcare, government, and other verticals. The need for reliable, cutting-edge solutions continues to grow.
Frost & Sullivan conducted research that offers a 360-degree view of security industry challenges, trends, and issues to evaluate innovative technologies. It found that, due to the adoption of endpoint devices across many verticals, endpoint protection in particular is in high demand.
“Because of Deep Instinct’s unique technology and deep learning-based endpoint protection solution, it delivers a high level of cybersecurity no other competitors can match, helping companies acquire a wide range of customers across many industries. Rakesh Vishwanath, Reasearch Analyst Frost & Sullivan. With its strong overall performance, Deep Instinct has earned the 2017 Frost & Sullivan Technology Innovation Award.”
What is the Technology Innovation Award Methodology?
Technology Innovation can only be sustained if 3 key areas of leadership exist: understanding demand, nurturing the brand, and differentiating from competition.
To best assess award candidates, Frost & Sullivan analysts evaluated two key factors— Technology Attributes and Future Business Value—according to preset criteria.
Using a customized decision support scorecard with a 10-point scale, Frost & Sullivan research and consulting teams objectively analyzed candidates’ performance and assigned ratings:
After evaluating all companies according to this system, the analysts could truly visualize which companies are considered breakthrough and which are yet to operate at best-in-class levels.
Often enough, companies make important growth decisions based on a narrow understanding of their environment, resulting in various errors. But successful growth strategies are founded on a deep and thorough understanding of market needs, best practices, technical analyses and more.
Frost & Sullivan applauds the fact that Deep Instinct’s zero-day attack protection solution is based on a deep learning mechanism that demonstrated improved accuracy of 20 to 30% over competing solutions that are based on machine learning.
Deep Instinct is proud to continue to demonstrate a low false positive rate compared to competitors, allowing us to carve a niche in a highly competitive landscape.
To learn more about the benchmarking criteria used for the research, and the measurements and the steps used to best recognize and identify best practices, download the full report.