In the digital age, data is the lifeblood of any organization. Its effective management, including classification, is paramount to the organization's success. While automated data classification tools have become increasingly sophisticated, many organizations still rely on manual processes. This manual approach poses significant risks, particularly if staff members are not fully conversant with the organization's data classification policy.

The Human Element in Data Classification

  1. Lack of Familiarity with Classification Policy: Many employees are not fully aware of or do not completely understand the data classification policies in place within their organization. This can lead to unintentional misclassification of sensitive information, with serious implications for security and compliance.
  2. Personal Convenience Over Policy Compliance: Staff members may intentionally misclassify data at a lower level so they can transmit or handle the data in a manner that suits them. This deviation from the correct classification level, while convenient for the employee, exposes the data to unnecessary risks.

Key Risks Associated with Improper Data Classification

  1. Security Risks: Misclassifying data, whether intentionally or not, can expose sensitive information to unauthorized access. This can lead to breaches, identity theft, and other cybercrimes.
  2. Compliance Risks: Many industries are subject to stringent regulatory requirements regarding data handling. Misclassification can lead to non-compliance, resulting in hefty fines and reputational damage.
  3. Operational Risks: Incorrect classification may lead to inefficient data handling and retrieval, hampering business processes and decision-making.
  4. Legal Risks: Mishandling data due to misclassification may also expose the organization to legal liabilities, particularly if it involves personal or sensitive information.

Solutions and Best Practices

  1. Invest in Education and Training: Regular training sessions can ensure that all employees are conversant with the data classification policy, reducing the risk of unintentional errors.
  2. Implement Robust Policies and Monitoring: A clear and comprehensive data classification policy should be in place, and compliance should be monitored regularly.
  3. Consider Automation: Automation can remove the human error factor and bring consistency and efficiency to the data classification process. Many insider threat detection platforms, such as SaaS solutions designed to detect data leakage, offer robust automated classification tools.

In Summary

The manual classification of data presents serious risks to organizations, ranging from security breaches to legal liabilities. These risks are exacerbated when staff members are not fully conversant with data classification policies or choose to misclassify data for their convenience.

Mitigating these risks requires a multipronged approach, including comprehensive education and training, robust policies, regular monitoring, and consideration of automated tools. By recognizing and addressing the risks associated with manual data classification, organizations can better safeguard their information assets and ensure continued compliance with relevant laws and regulations. The correct classification of data is not a task to be taken lightly, nor is it one that should be left entirely to the judgment of individual staff members. It is a complex process requiring a holistic approach, careful consideration, and constant vigilance. The stakes are high, and the consequences of getting it wrong can be severe. Organizations must take appropriate steps to ensure that their data classification process is both robust and resilient.

Christopher McNaughton

Strategic Advisor, ShadowSight

Who is Christopher McNaughton

Chris is a proficient problem solver with a strategic aptitude for anticipating and addressing potential business issues, particularly in areas such as Insider Threat, Data Governance, Digital Forensics, Workplace Investigations, and Cyber Security. He thrives on turning intricate challenges into opportunities for increased efficiency, offering pragmatic solutions derived from a practical and realistic approach.

Starting his career as a law enforcement Detective, Chris transitioned to multinational organisations where he specialised and excelled in Cyber Security, proving his authority in the field. Even under demanding circumstances, his commitment to delivering exceptional results remains unwavering, underpinned by his extraordinary ability to understand both cyber and business problems swiftly, along with a deep emphasis on active listening.

What is ShadowSight

ShadowSight is an innovative insider risk staff monitoring tool that proactively guards your business against internal threats and safeguards vital data from unauthorised access and malicious activities. We offer a seamless integration with your current systems, boosting regulatory compliance while providing unparalleled visibility into non-compliant activities to reinforce a secure digital environment. By prioritising actionable intelligence, ShadowSight not only mitigates insider threats but also fosters a culture of proactive risk management, significantly simplifying your compliance process without the overwhelming burden of false positives.