In order to predict the potential business impact of unexpected digital exposure, Emergynt has developed their machine learning-based 'Instinct Engine' to implement a dynamic, quantitative risk model that captures inputs from key business and security stakeholders. This engine asses risk from cyber exposures, personnel factor, process breakdowns, technology impact, and more. It is instinctive and self-learning, only requiring two to three data sources to begin providing an overview of an organization's digital risks.
Emergynt was known as Emergent Network Defense before re-branding with the new name in April of 2018. Emergynt's Risk Evangelist and Director of Communications, Joel Benge, explained that part of the reason for the 'Y' in the name change is the company's goal of "helping organizations to understand why certain risk exposures are more critical than other."
Earl Crane, PhD, CISSP
Newell Crane, PhD
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- Swarm intelligenceCollective behavior of decentralized, self-organized systems
- Machine learningA field of computer science enabling computers to learn.
- CybersecurityCybersecurity is the protection of software, hardware, and data from digital attacks for the purpose of accessing, changing, destroying, interrupting, or extorting assets and information.