As cyber threats continue to evolve and become increasingly sophisticated, it has become imperative for organizations to have a comprehensive understanding of the data they possess and how it should be protected.
In an insightful and thought-provoking discussion on the complexities of data classification, Dorene Rettas, Co-founder of Cyber Security Tribe and Dana Morris, Senior Vice President of Engineering at Virtru together explore a critical subject that lies at the heart of modern cybersecurity practices: the paramount significance of data classification and tagging.
The Significance of Data Classification
Data classification is not merely a security measure; it is the cornerstone of effective information governance. Morris emphasized that classification helps organizations understand the types of data they possess, their associated value, and how they should be protected. This knowledge is vital for implementing policies that govern data effectively.
For example, a simple email about scheduling lunch is less critical than one containing a client list with sensitive personal information. Data classification allows organizations to differentiate between these types of data, ensuring that critical information receives appropriate protection.
Beyond security, data classification provides additional benefits. It grants organizations visibility into how data is used internally, improving user experience and simplifying decision-making processes. Furthermore, it eases compliance with regulations like GDPR and HIPAA by simplifying the decision-making process for end-users who may not know all of the nuances and regulations.
Simplifying Data Governance
Traditionally, organizations have relied on manual processes for data classification, requiring users to make complex decisions regarding data protection. Morris stressed that automating this process is key to enhancing data governance. Instead of expecting users to grasp intricate regulations, organizations can introduce simple classification schemes, such as "secure" or "not secure."
For instance, one of Virtru's clients, a large bank, adopted a straightforward tagging system. Users had to decide if an email was "secure" or not by using a simple hashtag. In the background, Virtru's system encrypted and protected emails tagged as "secure" automatically. This approach reduced the burden on end-users and ensured consistent data protection.
4 Steps to Effective Data Classification
Morris outlined a systematic approach to effective data classification:
- Define Classification Scheme: Begin by defining a straightforward data classification scheme tailored to your organization's needs. Simplicity is key to user adoption.
- Identify Data Sources: Catalog all data sources within your organization, prioritizing them based on importance and risk. This will help you identify where to start implementing data classification.
- Prioritize and Execute: Prioritize data sources and roll out data classification incrementally. Avoid trying to tackle everything at once, as it can overwhelm users and disrupt operations.
- Select the Right Tools: Choose the right tools for data classification, whether through manual or automated methods, depending on your organization's size and complexity.
Real World Use Cases
Morris shared two real-world use cases where Virtru's data classification and tagging solutions have had a significant impact:
Simplified Email Encryption: A large bank switched to Virtru's solution, asking users to classify emails as "secure" or not with a simple hashtag. Virtru's system automatically encrypted and protected emails tagged as "secure," streamlining data protection without disrupting user experience.
Defense and Intelligence Classification: Virtru collaborates with government agencies in the defense and intelligence sector, automating the extraction of classification tags from documents, emails, and other sources. This allows for universal application of classification rules, enhancing data governance across boundaries and agencies.
Takeaways
Data classification and tagging are fundamental aspects of cybersecurity and information governance. Dana Morris's insights shed light on the importance of simplifying and in many cases, automating, this process, emphasizing the need for user-friendly approaches and systematic execution.
Organizations can learn from Virtru's real-world use cases to streamline data protection and governance, ultimately improving security and user experience in an increasingly complex digital landscape.
