Data protection vs data security

Data is the lifeblood of the modern world, powering businesses, driving innovation, and shaping our daily lives. However, an organization’s data is constantly under threat. Cyberattacks and data breaches have become increasingly common, with devastating consequences. A 2023 IBM report found that the average cost of a data breach was $4.45 million globally. In the United States, that average was $9.44 million for 2022, more than double the global average.

Ensuring the security and protection of data is not just an essential business practice — it’s also a compliance mandate for many industries. Let's take a closer look at data protection and data security, break down what they encompass, and explore how to put them into action.

What is the difference between data protection and data security?

Data protection and data security are often used interchangeably, but they have distinct focuses and objectives.

Data security primarily revolves around safeguarding digital data from unauthorized access, use, or disclosure in a manner consistent with an organization’s risk strategy. It also includes protecting data from breaches, theft, modification or destruction.

Data protection goes beyond security. It encompasses not only safeguarding data but the policies, procedures, and technologies to ensure its lawful and ethical use. This involves compliance with privacy laws, data minimization, obtaining consent for data processing, and giving individuals control over their data. Data protection addresses the technical aspects included in data security and the legal and ethical aspects of data handling.

In essence, data security is a subset of data protection. Though both are crucial for preserving the trust and integrity of data, data protection extends its scope to encompass the broader spectrum of privacy and compliance concerns. Organizations need to implement both data security and data protection measures to create a comprehensive strategy for safeguarding their data in today's digital landscape.

The comparative table below highlights the fundamental components distinguishing data security from data protection.

What is data privacy?

Data privacy refers to an organization’s responsible and ethical handling of personal data collected from individuals. Laws such as GDPR and CCPA provide data privacy oversight to govern how organizations collect, store, process, and share personal information. This includes obtaining informed consent from individuals and respecting individuals' rights to control and access their data.

Data protection ensures organizations have the necessary security measures in place to secure sensitive information and comply with privacy regulations. In this way, data protection lays the foundation for achieving data privacy.

Best practices to keep your data safe

Keeping your organization's data safe is crucial to protect sensitive information, maintain trust, and comply with data protection regulations. Here are some best practices to guide your organization in protecting its sensitive data:

• Data classification: Classify data based on its sensitivity and importance. Common classifications include public, private, customer personally identifiable information (PII), protected health information (PHI), internal use only, confidential, and restricted. Not all data is equally valuable or sensitive, so you can allocate appropriate security measures based on each classification.
• Access control: Access control helps regulate employee access to files in an organization, making it easy for IT teams to govern who is allowed access to which data. Applying the principle of least privilege (POLP) — where employees only have the minimum access privileges to data that’s necessary for them to perform a specific job or task and nothing more — is the best practice approach.
• Security awareness training: Train your employees on data security best practices and the importance of keeping your organization’s sensitive data safe. When you provide consistent training to keep them updated on the latest threats and best practices, you’ll create a culture of security awareness within the organization.
• Strong passwords and multi-factor authentication (MFA): Implement and enforce strong password policies and use MFA to add an extra layer of security to accounts. MFA is a multi-layered security system that grants users access to a network, system, or application only after confirming their identity with more than one credential or authentication factor.
• Data encryption: Encrypt data at rest and in transit. This ensures that even if data is stolen, it is unreadable. By employing cryptographic algorithms, data encryption protects data from being accessed or deciphered without the proper decryption key.
• Data backups: Regularly back up your data and test the process to ensure your data can be quickly restored in case of cyberattacks, system failures, or other disasters.
• Zero Trust: Zero Trust is a security framework requiring all users — whether they’re inside or outside the organization’s network — to be authenticated, authorized, and continuously validated for security configuration and posture before being granted or keeping access to applications and data. Zero Trust assumes that there is no traditional network edge; networks can be local, in the cloud, or in a hybrid environment with resources and workers anywhere.
• Incident response plan: Develop a comprehensive incident response plan that outlines the steps to take in case of a data breach or security incident. Test and update this plan regularly.
• Data protection: Data protection is a part of a company’s overall security strategy that focuses on detecting and preventing the loss, leakage, or misuse of data through breaches, exfiltration transmissions, and unauthorized use. Traditional data loss prevention (DLP) tools include patching, application control, and device control, which help protect data by limiting the surface area available to threat actors. However, implementation challenges, disjointed visibility, and inconsistent policies in traditional DLP offerings have made adversaries' jobs too easy. A modern approach to data protection combines content with context, providing deep real-time visibility into what is happening with your sensitive data. This includes visibility into data artifacts as they move from web sources and endpoints to USBs and via web browsers to cloud and software as a service (SaaS) applications. Two specific components are worth highlighting:
  • Endpoint security: An essential component of data protection focused on defending endpoints — such as desktops, laptops, and mobile devices — from adversarial data exfiltration techniques. By implementing strong endpoint protection measures, organizations can prevent unauthorized access and mitigate the risk of data loss through these devices.
  • Insider risk management: Monitoring and analyzing the behavior of your organization’s users to detect and respond to potential data loss, whether it stems from malicious intent or accidental actions. By implementing an effective insider risk management strategy, you can more easily identify unusual activity and better detect data exfiltration attempts.
• Data compliance: Stay informed about data protection regulations like GDPR, CCPA, HIPAA and others. Make sure to comply with these rules if they are relevant to your organization, and don't forget the important tasks of managing consent and data retention.

Keep your data protected with CrowdStrike

Data protection is paramount for organizations of all sizes because it safeguards your sensitive information, fostering customer trust and loyalty and preventing costly data breaches. When you adopt strong data protection practices, it helps mitigate legal risks and enhances your company's reputation as a responsible and ethical entity in today's data-driven world.

CrowdStrike Falcon^® Data Protection has been purposefully crafted to prevent breaches and preserve the privacy and integrity of personal information. Falcon Data Protection — a part of the CrowdStrike Falcon® platform — provides full visibility into data in motion that is classified by both content and context for faster, accurate egress investigations, all through a unified console. Furthermore, the platform offers comprehensive visibility and protection across the most critical areas of an organization’s data risk: your endpoints, workloads, data, and identity.

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