Data Governance and Digital Transformation in the Public Sector

Having cut his teeth in software development and product management for both commercial and public sector companies, Chet Hayes brings a wealth of technical experience and expertise as the CTO at Vertosoft.

In his current role, he helps emerging tech companies do business with the government while also working with government agencies to adopt digital technologies and integrate them into their systems. Hayes sees a lot of what is happening around data classification, data governance, data sharing, privacy regulations, and evolving cybersecurity threats. He spoke about these with me in a recent Kitecast episode.

Data Governance and Security in the Public Sector

Data security and governance has become increasingly important in the modern business world. From ensuring compliance with regulations, such as Executive Order 14028 and Cybersecurity Maturity Model Certification (CMMC), to protecting against cyber threats, organizations must prioritize data governance and security and ensure both are baked into their cyber risk management strategy.

Data is often stored in unstructured ways, making it difficult to track and govern. Data may be shared via various methods such as email, file sharing, web forms, FTP, and more. Implementing centralized governance controls, such as tracking, can reduce the risk associated with data. Not only does it protect against cyber threats, but it also keeps organizations in compliance with the regulations of the agencies they work with.

In the digital age, data security and governance has become increasingly complex. Not only must organizations ensure compliance with internal and external regulations, but they must also protect against malicious actors. By tracking data in a centralized manner and implementing processes that prioritize data governance, organizations can better protect their data and ensure compliant operations.

Zero-trust Approach to Data Governance

The zero-trust approach to data governance is a modern, more secure way of managing access to sensitive information. The idea is that no user or device should be trusted until they have gone through a series of steps to validate their identity and credentials. This is in contrast to the traditional approach of creating a secure “castle-and-moat” type of perimeter around an organization and trusting anything that is within the network.

Modern networks are more complex due to the rapid expansion of data centers and edge computing. This makes it difficult to not only secure and govern data, but also ensure users and devices have appropriate access to the data. Zero trust addresses this complexity by verifying user identities and requiring users to authenticate devices before being granted access to data.

Zero trust also emphasizes the importance of continuous monitoring. Access is automatically revoked or altered if suspicious or unauthorized activity is detected. Finally, multi-factor authentication is recommended for further validation. This includes methods such as biometrics, passwords, OTPs, and digital certificates.

Where Are Government Agencies at When It Comes to Data Classification?

Data classification is an important concept for government agencies and businesses with which they work to understand as they manage large stores of data from various sources. The development of automated data classification tools can help streamline the process, giving government agencies the ability to quickly and accurately classify data for storage and analysis purposes. This not only helps with safety and compliance but also helps ensure the accuracy of results.

Unfortunately, many government agencies still rely on a manual process to classify data, either due to lack of budget or insufficient personnel at the department level. Automation can be extremely helpful in accelerating the data classification process so that it can be quickly and accurately sorted and analyzed to make other data governance controls effective.

The Role of AI in Data Governance and Cybersecurity

AI has become an indispensable tool for data classification and cybersecurity. It can be used to extract entities, build link analysis, and develop complex relationship models. AI-oriented approaches such as ChatGPT, and generative AI are being utilized to identify anomalous events and detect malicious activities.

AI is not only being used to detect potential threats but also to analyze user behavior and understand the context of their activities. AI-driven analytics can help identify unusual trends and uncover hidden relationships among different data points.

Further, AI-driven cybersecurity can be used to predict and anticipate future attacks in order to create effective preventive measures. AI continues to revolutionize the way we approach data classification and cybersecurity, providing organizations with the ability to gain deeper insights and make more informed decisions.

The Growing Adoption of StateRAMP Across Local and State Governments

As cloud-based services become more prevalent, the need for a standardized security process has become increasingly important for local and state governments and their associated organizations.

Through their secure cloud assessment framework, StateRAMP works with public sector organizations to increase the security of their cloud services and provide an easier and more cost-effective way to promote the adoption of cloud services.

Many states and local governments have seen the benefits of StateRAMP—which parallels FedRAMP certification—already and more are choosing to adopt the framework to simplify cloud security verification. In addition, as the need for cloud security continues to grow, StateRAMP’s security framework provides a common, standardized approach that public sector organizations can turn to for their data security needs. StateRAMP certification generally follows SOC 2 Type 2 Control Sets.

Private Content Governance With Kiteworks

The Kiteworks Private Content Network offers a comprehensive approach to sensitive content communication and risk management. This content-defined zero-trust approach employs least-privilege access and always-on monitoring.

Through policy-driven governance, Kiteworks helps organizations meet regulatory compliance directives like the National Institute of Standards and Technology Cybersecurity Framework (NIST CSF), FedRAMP, CMMC, and SOC 2. Multi-factor authentication is used to control access to sensitive content communication and collaboration. The Kiteworks Private Content Network unifies security and compliance risk management, tracking, control, and protection of private data.

Kiteworks also meets data privacy regulations like the European Union’s General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), Personal Information Protection and Electronic Documents Act (PIPEDA), and the Health Insurance Portability and Accountability Act (HIPAA).Thousands of organizations rely on the Kiteworks Private Content Network for unified tracking, control, and security of sensitive content communications.

Schedule a custom demo to see how Kiteworks can enable your organization to protect sensitive content while leveraging a platform model to extend privacy and compliance of sensitive content across numerous digital channels.

Additional Resources

• Blog Post AI for the Good and Bad in Cybersecurity
• Report Manage Your Data Privacy Exposure Risk for 2023
• Webinar Addressing the Biggest Gap in Your Zero-trust Strategy
• Blog Post How to Protect Business With the NIST Cybersecurity Framework
• Blog Post Learn About Modern Solution for Financial Institutions Seeking Compliance With the FTC Safeguards Rule
• Blog Post Uncovering the Benefits of Working With a C3PAO Organization for CMMC 2.0 Compliance
• Blog Post ITAR Compliance Regulations, Standards, and Penalties
• Blog Post GxP in FDA-regulated Industries: Comply With Complex Good Practices