The Illusion of Security: Bridging the Gap Between Data Protection Protocols and Reality

In May 2023, Tesla faced an insider data breach when two former employees leaked over 23,000 internal documents—amounting to nearly 100GB of confidential information—to a news outlet. The specifics of how these perpetrators accessed the data remain undisclosed. However, evidence suggests that Tesla may have failed to revoke the ex-employees' access permissions after termination, a critical oversight.

Unfortunately, breaches like this continue to occur despite growing awareness and enhanced data privacy initiatives. This year, 96% of organizations stated that data privacy is a business imperative. Yet, the latest Data Breach Investigations Report (DBIR) revealed staggering statistics: out of 30,458 security incidents, 10,626 were confirmed breaches—double the numbers from the previous year.

This alarming trend underscores a harsh reality: organizations often lag in implementing effective measures, even when they’ve established robust data protection policies. For instance, 74% of cybersecurity leaders acknowledge that sensitive data is being fed into public AI models despite having security protocols in place.

Why the Gap Between Policy and Practice?

The disconnect between written security policies and real-world implementation stems from several factors:

1. The Challenge of Massive Data Volumes

64% of organizations manage one petabyte or more of data, and 41% handle over 500 petabytes. Enforcing defined security becomes challenging without advanced tools capable of covering large-scale datasets. Sensitive data can slip through the cracks, becoming vulnerable to misuse and compromise.

2. The Pitfall of Unstructured Data

Unstructured data accounts for 80-90% of what organizations manage and doesn’t fit neatly into databases. It is often overlooked by data protection tools that primarily secure structured datasets.

3. Lack of Visibility Across Data Environments

Sensitive information is dispersed across disparate systems and environments—on-premise, hybrid, and multi-cloud. This data sprawl makes it difficult for organizations to locate and classify all data to enforce necessary controls.

4. Limited Awareness Among Employees

Almost 40% of employees are unaware of their company's security policies. Complex technical jargon from security teams can alienate employees from other departments, leading to a lack of buy-in and poor policy adherence.

5. Friction in Following Security Protocols

Complex security workflows, such as multi-step access controls, discourage users from compliance. Many bypass these protocols or resort to unauthorized applications, exposing sensitive data to risks.

6. Compliance-driven Approaches

Businesses often aim only to tick boxes to meet the bare minimum needed for regulatory compliance (e.g., GDPR, HIPAA), leaving protocols insufficient to combat real-world threats.

From Policy to Practice: Operationalizing Data Security

Here’s how you can ensure that data security policies and protocols are not only defined but also operational across the entire organization:

1. Scan and Discover

Regularly scan all systems and environments — public and private cloud, on-premise servers, and local storage of endpoint devices — to identify and classify all structured and unstructured sensitive data as soon as it's created or shared. 

2. Automate Security Measures

Apply encryption and access controls automatically when sensitive data is discovered, ensuring no manual intervention is required.

3. Embrace Granularity

Organizations need data to operate, and it's impractical to lock it all down for everyone. Choose security controls that can be applied at a granular level. Instead of locking entire folders and files, selectively encrypt sensitive parts of files and documents, leaving the rest accessible and available for use and collaboration. 

4. Make Security Frictionless

Don’t leave it up to the end users and employees to implement data security measures, nor rely on them to always follow all protocols to the letter. Embed security controls directly into data, preventing users from unintentionally bypassing protocols.

5. Continuously Monitor Sensitive Data

Track sensitive files across their lifecycle, maintaining audit trails to identify unauthorized actions.

6. Integrate Security in Workflows

Make security a seamless part of daily tasks, ensuring workflows such as data requests, sharing, and document signing occur through appropriate and authorized channels, with the data protected at its core.

7. Build a Culture of Awareness

Conduct regular training and simulations to enhance employee understanding of security risks and encourage accountability.

8. Measure Success

Use metrics to track policy adherence and adjust strategies accordingly. Data security posture should always be improving.

From Policy to Implementation: Enforce and Automate Data Protection with Confidencial

Confidencial is a data-centric security platform that allows organizations to operationalize security at scale. Combining actionable DSPM (Data Security Posture Management) and proactive DLP (Data Loss Prevention) goes beyond discovery and classification to automate policy enforcement.  

Here’s what makes Confidencial stand out:

• Comprehensive Scanning: Covers on-premise, hybrid, and multi-cloud environments, identifying sensitive data in unstructured formats.

  
  

• Automated Policy Enforcement: Automatically applies selective encryption and granular access controls to protect data at its source.

  
  

• Proactive Protection: Embeds protection and access controls into documents, ensuring sensitive data remains secure and never exposed to unauthorized parties, even if users fail to follow protocols.

Confidencial doesn’t wait for breaches to happen—it prevents them by securing data at scale.

See how Confidencial can close the gap between policy and practice. See it for yourself. Request a free demo now!