A Cyber StartUp Leverages NLP To Provide Better Insight To Corporate Data
Natural Language Processing can help you discover and protect sensitive data. Learn how it can work for you.
These days there is a major challenge facing CISOs - how to properly manage an enterprise’s most sensitive data over a plethora of platforms. A new Israeli startup has developed a system that wants to utilize ML and NLP capabilities to help combat this growing worry.
Sensitive information made visible
Organizations both big and small produce tons of sensitive information, making tracking the troves of financial data, customer info, transactions, corporate secrets, legal documents, and other, dependent on each organization’s own resources.
This leads security teams to madness trying to constantly adapt visibility over the river of sensitive data flowing through an organization’s network.
Suridata.ai’s system maps the sensitive info, enabling organizations complete visibility over their most private data. The Israeli startup’s platform allows DevSecOps teams access to modify data collection/security requirements based on their specific needs. However, the system does not stop there, it continues to learn and optimize the prioritization of data based on an organization’s future needs or cyber threat landscape.
To this end, the system utilizes NLP (Natural Language Processing) algorithms that self-analyze collected info to better learn how to categorize and prioritize an enterprise’s sensitive data. The company’s AI system can accurately automate the data mapping process without requiring extensive enterprise’ resources. The different Ops teams will be able to continuously monitor every user’s access to the corporate data, with the system alerting to security protocol abnormalities.
Suridata’s flagship product was launched back in February, and has already been implemented in major organizational networks. In a conversation with Geektime, CEO Lee Kappon explains that Suridata’s main market competitors provide data classification solutions based on pattern identification, which she elaborates that this usually results in long implementation processes and the demanding of complex maintenance resources: “These solutions lack the abilities to accurately prioritize and understand what data is deemed sensitive,” notes Kappon.
Suridata.ai, which was founded in 2019 by Lee Kappon and COO Haviv Ohayon, recently completed a $2.1 million Seed round, led by the Israel-Colorado Innovation Fund (ICI), with participation from Israeli VC Sapir Venture Partners, ICONYC - a NYC based accelerator, and private investors.