Data Protection: Challenges and Opportunities

Daniel Selans

Protecting sensitive information has become a top priority for businesses of all sizes. They face an urgent need to strengthen their data protection measures as data breaches and cyber threats continue to make headlines. To do so, they must invest in the tools, expertise, and strategies necessary to navigate the complex landscape of data protection regulations and maintain the trust of customers and partners.

What is Data Protection?

Data protection entails putting in place technical and organizational safeguards to ensure data security, availability, and integrity. This includes technologies and practices aimed at preventing unauthorized data access, corruption, and loss. Some common data protection technologies include backups, encryption, access controls, and network security.

Data Protection vs. Data Privacy

While data protection and data privacy are related concepts, they focus on different aspects of handling sensitive information. Data protection is concerned with the technical measures used to secure data from unauthorized access, corruption, and loss. In contrast, data privacy focuses on setting user controls and determining who has authorized access to data.

Data privacy depends on data protection. If a business lacks the data protection measures necessary to ensure the data’s security, availability, and integrity, they cannot ensure that PPI and other sensitive data are managed in compliance with data privacy regulations.

Key Data Protection Regulations in the U.S.

There are numerous data protection regulations that businesses must comply with to ensure the security of sensitive data and avoid hefty fines. The General Data Protection Regulation (GDPR) is the most impactful for businesses with EU customers. It aims to make businesses more transparent and accountable for their handling of personal data. The GDPR requires companies to obtain consent for the collection and processing of personal information, notify users in the event of a data breach, and implement appropriate security measures.

Another important data protection regulation is the Health Insurance Portability and Accountability Act (HIPAA), which establishes national security standards for the protection of electronic protected health information (e-PHI). Covered entities, such as health care providers, must implement reasonable and appropriate security measures to ensure the confidentiality, integrity, and availability of e-PHI.

Additionally, the Gramm–Leach–Bliley Act (GLBA) Safeguards Rule requires financial institutions to develop a written information security plan that describes how they will protect clients’ nonpublic personal information. The Safeguards Rule requires financial services businesses to implement and periodically review access controls as part of a reasonable information security and data protection program.

These are just three of the data protection regulations U.S. businesses are required to comply with. We could also have mentioned the California Consumer Privacy Act (CCPA), the Children’s Online Privacy Protection Act (COPPA), the Family Educational Rights and Privacy Act (FERPA), the Fair Credit Reporting Act (FCRA), the Federal Trade Commission Act (FTCA), and several more.

The Components of a Data Protection Strategy

The makeup of a data protection plan differs depending on the type of data, the market in which a company operates, and the regulatory frameworks or industry standards they are expected to comply with. However, most businesses should implement a data protection strategy that includes the following components:

Access controls to ensure that only authorized individuals can access sensitive data.
Encryption to protect data in transit and at rest.
Network security systems, including firewalls, intrusion detection and prevention systems, and other security measures to protect networks from unauthorized access.
Employee training on data protection best practices and how to avoid cyber threats such as phishing attacks.
Incident response procedures for detecting, containing, and responding to security incidents, including data breaches.
Risk assessments to regularly evaluate potential risks and threats to sensitive data and identify vulnerabilities in networks, systems, or applications that could result in a data breach or unauthorized access.
Data discovery tools and processes to discover, categorize, and catalog data—particularly sensitive data—across networks and systems.

The Role of Automation in Data Protection

Automation plays a pivotal role in enhancing data protection by streamlining processes, improving efficiency, and reducing human errors. As organizations generate and process vast amounts of data, safeguarding sensitive information becomes increasingly challenging. Implementing automation in data protection can alleviate some of these challenges and bolster the overall security posture of the organization.

For example, data discovery and classification involve inventorying and categorizing data, which is essential for determining the best ways to secure it. Typically, this is done using a downstream detection method focused on detecting and mitigating data risks in already-collected data.

However, the downside of downstream detection is that sensitive data may already have propagated to connected services before being identified, making it difficult for organizations to guarantee that their customers’ data is managed in compliance with regulations.

More sophisticated tools use an upstream detection method that automatically identifies data as it is generated and before it is consumed by the app. This approach helps organizations proactively secure sensitive information and better ensure compliance with data protection regulations.

The Future of Data Protection: Challenges and Opportunities

As the digital landscape continues to evolve, the importance of data protection cannot be overstated. Organizations face an ever-growing list of challenges, including the increasing sophistication of cyber threats, compliance with multiple regulations, and the balancing act between data privacy and data protection. However, these challenges also present opportunities for organizations to enhance their data protection strategies and stay ahead of potential risks.