In today’s digital landscape, organizations constantly face the threat of cyberattacks and data breaches. Data protection has become crucial for businesses across virtually every sector. A 2022 IBM report found that the average cost of a data breach was $4.35 million globally. In the United States, that average jumps to $9.44 million. The report also determined that it took an average of 277 days to identify and contain a data breach.
An organization’s data is among its most valuable assets, so safeguarding it should undoubtedly be a high priority. But how does an organization go about protecting its data?
In this article, we’ll provide a concise yet comprehensive overview of data protection, cover its key principles, its relationship to compliance regulations and protecting business interests, and best practices your organization can follow.
What is data protection?
Data protection involves the policies, procedures, and technologies used to secure data from unauthorized access, alteration, or destruction. Ultimately, the goal of data protection is to safeguard an organization’s critical data — whether it’s customers’ personal information, intellectual property, or confidential business records. Organizations must implement data protection measures in order to:
- Prevent data breaches
- Minimize the risk of data leaks
- Ensure data availability
- Maintain data integrity
- Comply with relevant regulations
With the proper strategies, organizations can protect their reputation and forge customer trust. In addition, organizations that protect their data effectively also avoid potential legal and financial consequences.
Note that data protection is different from data privacy. Data protection focuses on safeguarding data, whereas data privacy deals with how organizations collect, store, and use personal information — while respecting the rights and consent of their customers and users.
Data protection ensures that organizations have the necessary security measures in place to protect sensitive information and comply with privacy regulations. In this way, data protection lays the foundation for achieving data privacy.
Legal and regulatory frameworks
Compliance regulations are legal requirements — some specific to a geographic region, some specific to an industry — that businesses must adhere to in order to ensure the security and privacy of sensitive data.
In addition to facing an increased risk of data breaches or incidents, non-compliant organizations also face potential legal and financial repercussions. Examples of data protection and data privacy regulations include:
- The General Data Protection Regulation (GDPR): A comprehensive data protection regulation applicable in the European Union. GDPR focuses on the privacy rights of individuals and seeks to provide them with greater control over their personal data.
- The California Consumer Privacy Act (CCPA): A state-level data protection law in the US. The CCPA grants California residents specific rights related to the collection, use, and sale of their personal information.
- The Health Insurance Portability and Accountability Act (HIPAA): A US federal law that sets privacy and security standards for protecting patient information.
- The Payment Card Industry Data Security Standard (PCI DSS): A set of security standards designed to ensure that companies accepting, processing, storing, or transmitting credit card information maintain a secure environment.
While compliance with regulations is crucial, organizations must be vigilant about data protection simply for the purposes of safeguarding valuable assets, such as intellectual property and sensitive data. Implementing data protection practices goes beyond mere compliance, ensuring that these critical assets remain secure and uncompromised.
Key principles of data protection
Different data protection regulations may outline specific principles, but many of these principles share common themes across regulatory frameworks. One set of principles that organizations can follow to ensure that they handle sensitive data responsibly and securely is the set outlined by GDPR:
- Lawfulness, fairness, and transparency: Personal data must be processed lawfully, fairly, and in a transparent manner in relation to the data subject.
- Purpose limitation: Personal data should be collected for specified, explicit, and legitimate purposes and not further processed in a manner incompatible with those purposes.
- Data minimization: Personal data collected should be relevant and limited to, as well as adequate for, the purposes for which it’s processed.
- Accuracy: Personal data must be accurate and, where necessary, kept up to date, with reasonable steps taken to correct or erase inaccurate data.
- Storage limitation: Personal data should be stored in a form that allows identification of data subjects for no longer than necessary for the purposes it was collected.
- Integrity and confidentiality: Personal data must be processed in a manner that ensures appropriate security, including protection against unauthorized or unlawful processing, accidental loss, destruction, or damage.
- Accountability: Data controllers must demonstrate compliance with the above data protection principles and take responsibility for the processing activities they perform.
Data protection techniques and best practices
The following data protection techniques can help guide your organization in protecting its sensitive data:
- Identification of sensitive data and assets: Performing an inventory of your organization’s data to determine what constitutes sensitive data. This helps you assess the potential risk and impact that would come with unauthorized access, misuse, or loss. This process likely involves collaboration across departments, ensuring a holistic understanding of your organization’s data landscape.
- Data classification: The categorization of data based on its sensitivity and importance. Common classifications include public, private, internal use only, confidential, and restricted. Classifications such as these help you prioritize security measures and allocate resources appropriately.
- Data encryption: The conversion of readable data into an encoded format to protect against unauthorized access. By employing cryptographic algorithms, data encryption protects data from being accessed or deciphered without the corresponding decoding key.
- Tokenization: A form of data obfuscation that replaces sensitive data with unique tokens. This is sometimes referred to as data anonymization and pseudonymization. By removing or replacing identifiable information with opaque identifiers, your organization can make it difficult for attackers to link sensitive data back to an individual.
- Secure data storage: Ensuring sensitive information — whether it’s stored on-premises or in the cloud — is protected from unauthorized access, data breaches, and physical theft. Secure data storage measures include techniques such as encryption of data at rest and physical security measures at data centers.
- Data backup and recovery: Involves regularly creating copies of essential data and ensuring they can be quickly restored in case of data loss, corruption, or system failure. This technique is often grouped with data redundancy measures, which involve creating multiple copies of data for storage in different locations.
- Data lifecycle management: This includes the processes and policies that guide the creation, storage, usage, and disposal of data, ensuring its security and compliance throughout its existence.
- Access control and authentication: Restricting access to sensitive data based on user roles, privileges, and credentials.
- Data loss prevention (DLP): This includes strategies and tools that detect and prevent the loss, leakage, or misuse of data through breaches, exfiltration transmissions, and unauthorized use. DLP tools include patching, application control, and device control, which help protect data by limiting the surface area available to threat actors. Two specific components are worth highlighting:
- Endpoint security: An essential component of DLP, focused on defending endpoints — such as desktops, laptops, and mobile devices — from malicious activity. By implementing strong endpoint security 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 most trusted 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.
- Employee training and awareness: Because human error and insider threats are among the most common causes of data breaches, educating employees about how to handle data safely, spot phishing attempts, and use strong passwords can significantly mitigate these threats. Through regular training programs and simulations, an organization can ensure its employees stay updated on the latest threats used by cybercriminals.
Data breaches and incident response
When data has not been adequately safeguarded using the techniques and best practices outlined above, an organization might soon face adverse effects, such as a data breach.
Common causes of a data breach include:
- Phishing attacks
- Compromised credentials
- Malware infections
- Insider threats
- Misconfigured security settings
Incident response (IR) planning is therefore another vital aspect of data protection. With IR planning, your organization can outline the steps that must be taken to address a data breach or security incident effectively.
A well-prepared IR plan involves a cross-functional team of experts with clearly defined roles and responsibilities. This will ensure prompt and coordinated actions to contain, investigate, and remediate incidents. Crafting an IR plan is only the first step; it must also be regularly updated. In this way, you can minimize the impact of data breaches, preserving both your reputation and your customers’ trust.
When implementing the necessary measures to protect your data, you can pair DLP solutions with next-generation antivirus (NGAV) and endpoint detection and response (EDR), features that are built into CrowdStrike Falcon® endpoint security. CrowdStrike Falcon® also provides incident response (IR), a set of resources and services that help you to identify and respond to incidents and breaches.
Conclusion
In this article, we explored the concept of data protection, focusing on its importance to businesses in light of the potentially massive impact of data breaches. We touched upon regulatory frameworks and key principles that govern data protection efforts. Finally, we examined various data protection techniques and best practices to help you get started.
The key takeaway is that organizations like yours need to prioritize data protection. Only by ensuring the security of your sensitive information can you maintain compliance and safeguard your most valuable assets.