Why should governments take an AI-based approach to information security?

Every day, intra- and cross-functional government teams exchange diverse datasets to achieve their citizen-centric missions. The approach to this information exchange could be a proactive…

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OpenText

January 7, 20223 minutes read

Every day, intra- and cross-functional government teams exchange diverse datasets to achieve their citizen-centric missions. The approach to this information exchange could be a proactive one that identifies common gaps and barriers in data needed to assess social and economic trends, or a requested one, like determining if new or additional cybersecurity support is needed for the nation’s transportation systems. Either approach helps governments make policy recommendations or act on policy decisions, including the latest U.S. National Defense Authorization Act, which admits agency reports will include highly sensitive classified information.

With data exchange and requests coming from every direction, at every sensitivity level and in every format, how can agencies apply a single risk management framework across all repositories?

Data as a strategic asset must first be discoverable and managed

When considering the shifting landscape of continual cyber threats and evolving cyber requirements, agencies are required to advance their abilities in addressing risks associated with processing, storing and transmitting sensitive information.

The challenge: data comes in two forms. Some is structured data, such as information recorded when filling out an online form or setting up an account. But 80% to 90% of data is unstructured like photographs, videos, audio clips, instant messages and ID card scans. Unlike structured data, unstructured data is difficult to manage and analyze. Because the data can be stored in so many formats, it’s almost impossible to assess what should be protected when using traditional tools.

Complexity mounts with the realization that only 28% of surveyed federal agencies have full knowledge of where their data is stored and only one-third can classify whether their data is sensitive or not.

This combination of challenges leaves many agencies in the dark when it comes to safeguarding sensitive data, developing a secured, information collaboration environment and complying with Federal regulations and statues. That’s where Artificial Intelligence (AI) can help.

Achieving readiness and designation goals with AI

AI can search vast quantities of data—both structured and unstructured—to identify the location of sensitive content, no matter where it’s stored on the network. When it’s located, the same AI tools can help government agencies determine what actions to take on the data: “keep it there,” “delete it” or “take further action.” And the same AI tools let you act on the data on a file-by-file basis or across large repositories of classified data.

Using AI-enabled applications, government can establish and quickly scale uniform data collection standards, seamlessly connecting the highest-priority user needs to any services provided by departments while governing the designation and use of classified, sensitive and personal data.

OpenText™ Magellan™ Risk Guard uses powerful machine learning to track sensitive information in an intuitive, AI-driven approach. It is simple to use and includes 20+ pre-configured models and more than 25,000 classifications. The solution lets users establish risk levels and actions to match their agency’s unique requirements.

OpenText Magellan Risk Guard can help your agency proactively identify, mitigate and prevent uncontrolled use of sensitive content. To learn more, register for our upcoming webinar “Structure the Unstructured: Identifying Risks and Trends of Privacy Information with AI,” on Thursday, January 27 at 1:00 PM ET / 10:00am PT.

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OpenText

OpenText, The Information Company, enables organizations to gain insight through market-leading information management solutions, powered by OpenText Cloud Editions.

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