Data protection is a cornerstone of any successful Zero Trust strategy. As highlighted in the recent teissTalk episode Zero Trust, Classification, and AI-Powered Data Protection, featuring Karim Eldefrawy, Thom Langford, Jean C., and Alexandra Pavelovna Henry, ensuring data security at every stage of your Zero Trust journey is critical. Here's why.
Zero Trust Network Access (ZTNA): Falling Short of Expectations
A recent survey of 200 CISOs revealed a glaring gap: current Zero Trust implementations are not the “magic bullet” many had hoped for. Most organizations are still in the early phases of ZTNA adoption, with 95% of providers failing to offer comprehensive capabilities. Legacy technology and existing network architectures pose additional challenges, making it clear why ZTNA hasn't fully delivered on its promises.
Where ZTNA falters, vulnerabilities arise. Organizations must fill these gaps by strengthening other security measures—starting with data classification.
ZTNA and the Missing Data Layer
ZTNA solutions often overlook protection at the data level—a significant oversight. When Zero Trust principles are applied to data (data-centric Zero Trust), access is restricted not just to files but to specific sensitive data points within them. This granular approach minimizes risk and adds depth to your Zero Trust implementation.
The best part? You don’t need to overhaul your existing infrastructure. Applying Zero Trust principles at the data level works independently of network architecture, making it especially valuable in hybrid and legacy environments where implementing ZTNA can be cost-prohibitive or disruptive to the business.
However, achieving this granularity can overwhelm already stretched security teams, particularly with challenges like data proliferation (particularly unstructured data), siloed infrastructure, and the lack of awareness and ownership of data within companies.
A Back-to-Basics Approach for Better Data Protection
To build a strong foundation for data security, organizations must step back and address the basics before moving forward with broader strategies like ZTNA. Here's how:
1. Measure Your Attack Surface
"You can't protect what you don't know." It’s the data protection-relevant equivalent of the immortal words of the United States Secretary of Defense Donald Rumsfeld "There are unknown unknowns". Start by identifying your data assets, mapping your attack surface, and gaining a broader awareness of the threat and regulatory landscape to understand the risks associated with sensitive data. There is no one-size-fits-all approach to data security. So, find the level of risk and protections you need in your vertical - the first step is critical to tailoring your data protection strategy.
2. Start Classifying Data
Once you’ve identified your data, classify it with simple categories like internal, external, sensitive, or regulated. Organizations need data to operate, and this classification enables you to prioritize protections without massively disrupting operations.
3. Lock Down Sensitive Data
Encryption is one of the most basic security tools to ensure the CIA triad (confidentiality, integrity, and authenticity), and it’s proven to work when correctly implemented and maintained. Once you classify the data, the next step is to lock down what you consider sensitive. Even if you start small by encrypting data under a single label like PII, taking this first step immediately strengthens your security posture. Encryption ensures that data is not accessible or manipulatable by unauthorized actors — regardless of the network segment they’re in, their credentials, or the fact that they are humans or AI agents — unless they have the appropriate decryption key.
4. Embrace Automation
With massive amounts of data across various environments, manual classification and protection are nearly impossible. Use AI and machine learning (ML) tools to automate data scanning, classification, and selective encryption to expedite the process and do the heavy lifting.
5. Automate Lifecycle Procedures for Onboarding and Offboarding Staff
Insider threats are a top concern. Automate workflows to ensure data access controls are in place for new employees as soon as they join, and privileges are automatically removed when they leave. Automating these security procedures prevents many types of compromises down the line.
Why Data Classification Matters Now
Data classification is not just a compliance checkbox; it’s the foundation for proactive data security. As highlighted in the teissTalk discussion, organizations must take actionable steps to protect their most valuable asset: data.
Confidencial can help streamline this process by automating data discovery, classification, and encryption. With tools designed to map your data’s attack surface and enforce protection policies across hybrid environments, you’ll gain control and visibility faster than ever.
Watch the Full Episode
For more insights into Zero Trust, data classification, and AI-driven protection, watch the full episode of teissTalk. Start building your data security strategy today and ensure that your Zero Trust journey addresses the gaps ZTNA leaves behind.
Watch the full episode of the teissTalk for a thought-provoking discussion and actionable recommendations. As you start discovering and classifying your data, the right solution can streamline and expedite the entire process, delivering results faster. Confidencial can become a proactive partner as you go back to basics, delineating your data’s attack surface with detailed mapping across all your environments and automating data classification and selective encryption based on your custom-built policies.
Comments