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Addressing the Problem with Collaborative Secure Data Sharing

As you’ve increasingly seen in news headlines, secure access to shared data is not only an issue for Federal and local government agencies and the Intelligence Community – it has also become an issue for business enterprises needing to protect their intellectual property and other sensitive business data while engaging on a global scale with their partners and contractors.

Looking closely at system designer experience and challenges in the Defense and Intelligence Communities helps gain insight on sharing data across multiple security classifications among individuals with different levels of security clearance.  Traditional Defense and Intelligence solutions have tended to rely on a separation of data at different security classifications into isolated standalone compute and storage systems, usually with one for each classification level.

Seagate Multilevel Security Cov.This is the second article in a series designed to address the needs of government and business or collaborative and secure information sharing within a Multilevel Security (MLS) framework. Click here for the PDF.

In this configuration, an individual user requiring sources of data from different classification levels (along with need to know requirements) would have to navigate through many steps to manually connect and then re-connect their terminal or workstation between isolated, or “stovepiped”, secured networks and systems in order to collect, process, and distribute the data.  Unfortunately, manual procedures impede a user’s ability to quickly complete tasks, causing increased operational complexity, unnecessary delays and cost.

This gets even worse as assignments grow and involve more data sharing among collaborating teams and organizations.  Beyond just the capital cost to manage data on multiple isolated networks and standalone systems, the administrative, maintenance and operating costs grow ever more unmanageable with the explosion of more problems and very large data sets.

While data sharing between groups brings valuable results, world events raise the bar for generating more results quicker.  New initiatives accelerate multi-agency or “enterprise-wide” collaborations, increased organizational efficiency, and greater resource sharing to drive down cost and the time to get actionable results.

In today’s world, virtually all Congressional, Department of Defense (DoD) and Office of the Director of National Intelligence (ODNI) recommendations push for compute and storage resources to be actively inter-networked while existing regulations require strict security to protect data.  Initiatives that widely adopt and leverage Big Data and HPC computing methods are already well underway.  But what impact does this have on users working with multiple data classifications?  What happens in a multilevel secure environment if it needs to scale up?  How do users efficiently and effectively navigate through isolated networks when sensitive information needs to flow securely between different agencies and organizations across the globe?

In times of disaster or national threats, analysts need to collaborate quickly and across agencies.  As threats evolve, there is a fundamental need to adjust focus, priorities, analysis resources and contributor expertise.

Similar issues arise when enterprises open their internal networks to global partners and contractors, putting their business-critical intellectual property and information at risk. Can collaboration with Multilevel Security controls still promote information sharing and foster innovation in a way that is both efficient and profitable?

The next article in this series looks at Multilevel Security Frameworks. If you prefer you can download the entire article series in PDF format from the insideHPC White Paper Library courtesy of Seagate.

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