What Is Data Protection? How Do You Protect User Data?

The core of businesses is data. Meeting customer needs, adapting to unexpected events, and responding to rapid market fluctuations ultimately depend on data. 

Companies generate vast amounts of data from a variety of sources. The sheer volume and granularity of data generated during business require constant attention to data protection and maintenance. After all, data is more than just a collection of static records.

Whether small or big, data protection must be at the forefront of considerations for any business. While solutions like data-centric security software ensure that the data stored within a database is secure and used properly, it is vital to understand what data protection is, how it works, and its related technologies and trends. 

The need for data protection grows as the quantity of data generated and saved expands at unprecedented rates. There is also minimal tolerance for downtime, which might make access to critical information impossible.

As a result, ensuring that data can be recovered rapidly after corruption or loss is an essential aspect of a successful data protection strategy. Data protection also includes safeguarding data against compromise and preserving data privacy.

Data protection principles aid in preserving data and ensuring its accessibility at all times. It includes adopting data management and availability elements, operational data backup, and business continuity disaster recovery (BCDR).

The following are the key data management principles of data protection:

• Data availability ensures users can still access and use the information they need to do business, even if lost or corrupted.
• Automating the transfer of crucial data between offline and online storage is part of data lifecycle management.
• The valuation, categorization, and protection of information assets from various threats, such as facility interruptions, application and user mistakes, equipment failure, malware infections, and virus assaults, are all part of information lifecycle management.

Data protection acts and laws govern specific data types’ collection, transmission, and use. Names, images, email addresses, account numbers, internet protocol (IP) addresses of personal computers, and biometric information are only a few examples of the many different forms of information that constitute personal data.

Different nations, jurisdictions, and sectors have different data protection and privacy laws. Depending on the infraction and the instructions provided by each legislation and regulatory body, non-compliance may result in reputational harm and financial penalties.

The observance of one set of rules does not imply adherence to all laws. All rules are susceptible to change, and each legislation has various provisions that can apply in one situation but not another. Implementing compliance consistently and acceptably is challenging, given this amount of complexity.

Notable data protection regulations

Governments all around the globe are focusing on data security and privacy legislation, which has a significant influence on how these systems work. Some prominent data protection acts are discussed below. 

GDPR of the European Union

The General Data Protection Regulation (GDPR) is an EU regulation that was enacted in 2016. It allows individual users of digital services additional rights and control over the personal information they provide to companies and other organizations. 

Businesses operating in or collaborating with EU nations and not complying with these rules face hefty fines of up to 4% of their global sales, or 20 million Euros.

United States legislation on data protection.

The U.S. lacks a single primary data protection law, in contrast to the EU. Instead, hundreds of federal and state privacy regulations are intended to safeguard Americans’ data. Below are some illustrations of such laws.

In the subsequent years, U.S. regulatory requirements may change as data protection becomes an increasingly important concern in a society that is becoming more digital.

Australia’s CPS 234

In 2019, Australia implemented the Prudential Standard CPS 234 to govern how financial and insurance businesses defend their information security from cyber attacks. It also necessitates the implementation of tight auditing and reporting mechanisms to guarantee that systems remain compliant.

Data protection is crucial since it aids businesses in preventing data breaches, exfiltration, downtime, reputational harm, and financial loss. Organizations must also enforce data protection to restore lost or damaged data and comply with legal obligations. 

This approach has become more critical as workforces become more volatile and run the danger of illicit data removal.

While object storage solutions house all sorts of data, businesses need data protection to address specific security issues. Although they can vary depending on the type of business, the following typical problems affect most businesses and can be avoided with data protection. 

• Backups on tape or discs comprise physical devices security teams use to store or back up digital assets. 
• Storage snapshots take the form of an image or other reference point, representing data at a precise time. 
• Continuous data protection (CDP) is a system that backs up data on a computer system whenever a change is made.
• Firewalls are devices that monitor network traffic. They permit or deny traffic depending on a set of security standards.
• Encryption safely transforms data to and from the scrambled text to be stored or transferred between devices without compromising the raw content. 
• Endpoint protection is a data security solution that monitors and blocks threats on endpoint devices, such as laptops and smartphones, at the network’s edge. 
• Data loss prevention (DLP) systems identify possible leaks and exfiltration. They necessitate significant data categorization for network administrators to monitor and govern the data that users transport. A DLP will not monitor data that a corporation has not classified.
• Insider risk management (IRM) is a risk-based approach to data security. Unlike traditional DLP approaches, IRM systems monitor all data, not only data that has already been tagged by a corporation, making it an appropriate option for managing a rapidly changing workforce. IRM assists security teams in prioritizing what data is most important to their specific needs and responding quickly to data hazards without limiting employee productivity.

Understanding all of the technologies available for data protection can help determine which solution is appropriate for your business.

There are several crucial distinctions between data privacy, data security, and data protection, even though these terms are often used interchangeably, as mentioned below:

• Data protection is the collection of procedures and systems that guards against data exploitation, guarantee that it is accessible to those who are authorized to use it, and promote worker productivity.
• Data privacy limits who has access to sensitive information, often personal data, and it complies with data protection laws.
• Data security is a subset of data protection and guarding against manipulation and dangerous conduct from internal and external threats.

When working with departments outside of security, in particular, recognizing the differences between these terminologies can assist in avoiding misunderstandings.

• It safeguards essential data, including financial statements and corporate activities. 
• It improves both the quality of data during transactions and saved data.
• It is independent of any specific technology and applies to everyone.
• The risk of financial loss is decreased.
• It stops software, project or product papers, and corporate strategies from being stolen by rival businesses.

A hyper-converged infrastructure combines storage, computation, and networking into a single system. Instead of handling the complexities of dispersed hardware and resources, IT managers may communicate under this paradigm with a single interface, generally through virtual machines (VMs).

From the data safety standpoint, hyper convergence’s benefit decreases the surface area the security team must control. Furthermore, it can automate much of the complexity associated with resource allocation, data duplication, and backups.

Protection from ransomware 

Ransomware is a particular kind of malware that encrypts vital data, making it inaccessible to users. It usually demands a ransom payment from the victim to the attacker to unlock the data. This conduct forces the victim to choose between losing data and paying a considerable ransom without guaranteeing that the attacker will solve the problem.

Businesses may use ransomware prevention solutions to monitor specific malware entry points, such as phishing campaigns. These solutions can also aid in isolating infected devices, preventing lateral movement, and reducing the attack surface area.

Zero trust 

A zero-trust security model or architecture requires all users to authenticate when accessing internal applications, data, and servers.

In a zero-trust system, traffic is not assumed to originate from a trusted source, unlike a typical network that relies primarily on firewalls to protect an isolated network.

Organizations no longer trust cloud applications and remote workers within a secure local network, so the zero-trust paradigm is becoming increasingly critical for modern data protection. Other types of authentication, such as single sign-on (SSO) and user access control, must be used by systems to authenticate users and prevent unauthorized access.

Protect, regulate, accelerate 

Establishing a thorough understanding of and enforcing good data practices (e.g., guaranteeing that data is not just physically protected but also that users understand how it may be used) combined with protection that backs that up allows data to be more valuable. 

Organizations produce quintillion bytes of data every day. Therefore, it makes sense that they are always looking for improved data management technologies. Data protection, after all, is a part of overall data management. 

Want to understand data better? Learn more about data as a service (DaaS) and how it’s relevant today!