Data Protection vs. Data Security

Although these terms may seem interchangeable and a matter of personal preference, there are distinctions between them.

Data protection is an “umbrella” term that includes regulatory compliance and legal and ethical considerations. Examples include privacy regulations, which affect data policies, procedures, and technologies. Protection also aims to ensure that data is available, accessible, and recoverable. It is particularly important in the event of a disaster, system failure, interruption, or accidental loss.

Because data protection deals with lawful and ethical use, it naturally focuses on individuals’ personal data and how it is collected, handled, maintained, and stored. Regulations and standards governing data protection vary by state, country, and region. For example, one pillar of the General Data Protection Regulation (GDPR) in the European Union is an individual’s right to protection of their personal data. The California Consumer Privacy Act gives consumers the right to know what personal information a business collects and sells. In China, the Personal Information Protection Law is similar to the GDPR.

Compliance with such regulations is especially important for certain industries, such as healthcare, financial services, and retail, which deal heavily with personal information from patients[SS1] , financial services clients, and retail customers.

Effective data protection requires safeguarding data throughout the lifecycle, from creation to destruction. Besides policies and procedures, organizations employ a range of technologies for data protection. They include data backups and replication, failover data centers, and data lifecycle management solutions.

Data security is considered a subset of data protection. Its focus is safeguarding data from internal and external threats such as unauthorized access, breaches, theft, or misuse. Security encompasses all types of data, not just personal information, such as proprietary price lists and intellectual property. Securing data involves using tools like encryption, access controls, firewalls, monitoring systems, and multi-factor authentication to prevent cybercriminals and hackers from successfully conducting attacks.

In contrast to data protection’s emphasis on regulatory compliance, data security is primarily concerned with adhering to industry frameworks, standards, and protocols.

Taken together, data protection and data security help maintain the safety, privacy, integrity, availability, and recoverability of business and personal data.

Data protection is the foundation of data privacy, which is often defined as the ability of individuals to control their personal details, such as name, address, and Social Security number, and other sensitive information like financial and medical data. Data privacy is concerned with data collection, handling, storage, and dissemination, such as when, how, and with whom the information can be shared. Typical controls involve obtaining explicit consent by the individual, and notifying the person about intended uses of their data.

Key principles of data privacy include:

• Transparency: Giving consumers clear, accessible information regarding collection, storage, and usage of their personal data.
• Specific purpose: Limiting how data will be used and ensuring the purpose is legitimate and lawful. A related principle is restricting data collection to that specific purpose.
• Confidentiality: Making sure personal data is accessible only to authorized users.
• Integrity: Protecting data against unauthorized alterations.
• Accountability: Taking responsibility for data management processes, data security, and compliance with laws and regulations.
• Retention: Keeping personal data only as long as it is needed for the intended purpose, and then disposing of it in a secure manner.

The importance of data privacy has sharply increased due to the widespread use of social media platforms, AI, and SaaS apps, as well as the increasing frequency of data breaches being highlighted in the news. People are very concerned about protecting their private details from being stolen, exposed, sold, or used against them in scams or even political repression.

A number of countries consider data privacy to be a human right and regulate personal data usage accordingly. For example, according to the European Union, “It is not enough to simply opt out, for example by checking a box saying you don’t want to receive marketing emails. You have to opt in and agree to your personal data being stored and/or re-used for this purpose.”

Besides being top of mind for many individuals, data privacy is crucial for enterprises because:

• Data is among the most important assets of any organization. Customer and partner data is extremely valuable for sales, marketing, business development, quality assurance, and many other functional areas. The right data can help drive business growth and expansion.

  Further, an enterprise’s perceived trustworthiness – and its overall reputation — are heavily influenced by the care and diligence it uses in protecting customers’ data privacy. A data breach that exposes personal information can do significant damage to an organization in terms of customer loyalty, brand image, and competitive position.

• Effective privacy measures help ensure compliance. Adhering to data privacy regulations can help an enterprise avoid fines and other penalties locally and internationally.
• Strong privacy practices help thwart fraud and cybercrime. Implementing strong data privacy measures protects more than just personal data – this strategy also spills over into other types of data, such as intellectual property, which are attractive to malicious actors.
• Privacy is becoming a competitive advantage. Customers seek out products, such as smartphones, which promise strong privacy protections.

Safeguarding personal data and sensitive business information is fundamental to an effective protection strategy that encompasses data security, compliance, availability, and integrity. Following are best practices recommended and followed by leading organizations.

1. Identify and categorize all the data held by the enterprise, based on its sensitivity and value. Typical data categories are personally identifiable information (PII), protected health information (PHI), financial information, confidential business information such as intellectual property and earnings reports, and classified government information. Categorizing data provides guidance for prioritizing protection measures.
2. Understand data usage by investigating which users can access data and under which conditions; how data is used in business processes; where it is being sent; and how it is stored. This knowledge is essential in identifying risks and complying with regulations and standards.
3. Implement access controls according to the principle of least privilege and zero trust frameworks. Strong access controls can include role-based access control (RBAC)., robust password policies, and multi-factor authentication. Conduct regular audits to verify that access controls are functioning properly.
4. Encrypt data at rest and in transit so it cannot be read without a decryption key. Strong encryption, such as AES-256, is particularly important when transmitting sensitive data over unsecure networks.
5. Back up data regularly to ensure it remains available and accessible during a planned or unplanned interruption, system failure, or cyberattack. Other tactics for ensuring data availability and access include using redundant array of independent disks (RAID) technology on servers, establishing a failover data center, and moving data to the cloud.
6. Create policies for data collection and retention to strengthen compliance with regulatory requirements. These policies should define which types of data are collected, how they are shared, used, and stored, and how long each type should be retained.
7. Conduct training for employees and contractors on organizational rules, regulations, and best practices for protecting personal data and other sensitive information. Awareness training can help reduce risks to data such as insider threats.
8. Perform vulnerability assessments and penetration tests to identify security weaknesses that can provide attack vectors for cybercriminals seeking to compromise or exfiltrate personal or business data.
9. Stay current regarding regulations governing data privacy and protection to be sure the organization complies with the latest changes.