BlackBerry CylanceAI®
Photo Gallery
 |
BlackBerry CylanceAI®
Additional Info
| Company | BlackBerry Limited |
| Website | http://www.blackberry.com |
| Company size (employees) | 1,000 to 4,999 |
| Headquarters Region | North America |
| Type of solution | Software |
Overview
BlackBerry Cylance AI sets the standard among the first machine learning (ML) models for cybersecurity. Now in its seventh generation, Cylance AI has trained on 20+ billion diverse threat data sets over years of real-world operation.
Many security providers’ claims use AI/ML to optimize and automate some aspects of their heuristics or signature-generation processes, as plugins or add-ons. This falls short of the full promise of AI—Prevention First.
Cylance uses AI to determine a threat in less than 50 milliseconds – before it’s run, even before it’s known. Because preventing a breach is faster and more effective than remediating after one.
AI powers all key stages of the data lifecycle: ingesting, processing, and analyzing data, through to correlating and analyzing telemetry from multiple sources.
Our AI leadership has led to being chosen as cybersecurity partner by some of the most sophisticated organizations in the world:
• All 7 of the G7 and 18 of the G20.
• 45 of the Fortune 100
• 77% of Fortune 500 financial services companies.
How we are different
• Every product in the BlackBerry Cylance platform incorporates AI/ML. It powers all stages of the data lifecycle: ingesting, processing, and analyzing data, through to correlating and amalgamating data in our data lakes into contextual intelligence for our customers.
• Many areas where we apply AI/ML aren’t visible to users. For example, we use ML to understand multisensory data across both a time frame and execution sequence to identify when multiple events stack up as an actual attack. In this way, we reduce alert fatigue for platform users and deliver efficiency gains for customers.
• Our AI delivers a 5-year advantage over industry awareness. BlackBerry’s model from 2016 has effectively predicted and prevented malware used in recent attacks. We track worldwide threat actors using ML/AI indicators, and have used AI to analyze, dissect and curate trillions of files, identifying 20 billion+ characteristic files, specifically for maximum effect in model training.
