Data Protection

What is Data Protection?

Data protection means keeping information safe from being lost, corrupted, or compromised. Essentially, it’s about protecting the privacy and security of your data.

It covers a few key areas:

• Data Integrity: Making sure data is accurate and reliable.
• Data Privacy: Controlling who can access and use your information.
• Security: Protecting data from errors, damage, and unauthorized changes.
• Guidelines: Setting rules for how businesses should handle data.

This concept applies to everyone, from individuals and businesses to government and international organizations. As we collect and store more and more data digitally, having strong data protection measures is more important than ever for staying secure and compliant.

Why Data Protection?

• Prevent Misuse: To stop personal data from being misused, mishandled, or exploited.
• Uphold Rights: To make sure the fundamental rights and freedoms of individuals providing data are respected.
• Ensure Fair Practices: To guarantee fair and trustworthy commercial activities between consumers and businesses.
• Assign Responsibility: To clearly place the responsibility on organizations for properly handling personal data.
• Empower Individuals: To give people greater control and understanding over how their data is collected and used.

Data Protection Principles

The main data protection principles are outlined in the General Data Protection Regulation (GDPR). This is a key EU regulation focused on data protection and privacy.

The GDPR’s Purpose

The primary goals of the GDPR are to:

• Give individuals more control over their personal data.
• Simplify the regulatory environment for businesses that operate internationally.

The GDPR establishes seven core principles that govern the lawful processing of personal data. Data processing includes virtually any operation performed on data, such as:

• Collection and storage
• Organising and structuring
• Altering and consulting
• Usage and communication
• Restricting, erasure, or destruction

GDPR Protection Principles

1. Lawful, Fairness, and Transparency

Organizations must process data in a way that is lawful, fair, and transparent.

• Lawfulness: This means that an organization’s data activities must not break the law. Specifically, they need to be fully aware of and follow GDPR data collection rules.
• Transparency: This ensures that data subjects know exactly what is being done with their information. All communication about personal data usage should be easily accessible, clear, and simple to understand.

2. Purpose Limitation

The Purpose Limitation principle dictates that data must be collected for a specific, explicit, and legitimate purpose.

• The reason for collecting the data must be clearly explained.
• Organizations cannot perform any further processing that doesn’t align with that original, stated purpose.

There is an exception to this rule: data processing for archiving in the public interest or for scientific, historical, or statistical purposes is considered compatible with the initial reasons. These specific activities are therefore allowed more flexibility.

3. Data Minimization

The principle of Data Minimization states that organizations should only process personal data that is adequate and strictly necessary for the specific purpose of the collection.

This approach offers several benefits:

• Limits Risk: If a data breach occurs, cyber-criminals will only be able to access a limited amount of data.
• Improves Accuracy: It helps keep the collected data accurate and up-to-date.

Data should only be processed if the intended purpose cannot be achieved by other means. Furthermore, Data Minimization requires that the storage period for personal data must be kept to an absolute minimum.

4. Accuracy

The Accuracy principle requires organizations to ensure that all personal data is accurate and, where necessary, kept up to date.

Organizations must take reasonable steps to:

• Erase or correct any personal data that is found to be inaccurate or incomplete as quickly as possible.
• Understand that data is considered accurate only in relation to the purpose for which it is being processed. Data that isn’t regularly updated can become inaccurate.

To support this, every data record should clearly include the data itself, its source, and the time it was collected.

5. Storage Limitation

The Storage Limitation principle requires that personal data be kept in a system only for as long as needed. Once the data has served the specific purpose for which it was collected, it must be deleted.

To follow this rule, organizations need to:

• Regularly review all collected data to confirm it’s still necessary for its original purpose.
• Adopt a formal data retention policy that sets a definite time limit for storing personal data.

This storage time limit should be determined based on the original reason the data was collected and the type of industry the organization operates in.

6. Integrity and Confidentiality

The principle of Integrity and Confidentiality is focused entirely on data security.

It requires that data be processed in a way that ensures its protection, which includes preventing:

• Unlawful or unauthorized access.
• Accidental loss.
• Destruction or damage.

Organizations must take suitable technical and organizational measures to guarantee this security.

The GDPR does not mandate specific security measures. Instead, it allows organizations to choose appropriate solutions based on current technological and corporate best practices. A common technique used to secure personal data is encryption.

7. Accountability

Organizations must demonstrate compliance with all the GDPR principles and show accountability in their personal data protection efforts. This means they must clearly demonstrate they are taking responsibility for how personal data is processed.

If an organization is uncertain about how to comply with the GDPR requirements, they should take action by:

• Consulting a legal practitioner or data protection expert.
• Enrolling in appropriate training courses.

Check out our course on GDPR – Data Protection in Practice

Data Protection Strategies

Organizations employ various strategies to protect their data from being lost or stolen. One common threat is the failure of storage systems, where media becomes corrupted and leads to data loss. The solution is to ensure data remains accessible even when storage devices fail.

Here are key strategies used to protect against data loss:

1. Failure of Storage Systems

Media that store data can fail or become corrupted, leading to data loss. The strategy here is to ensure that data is available even in media failure.

• Synchronous Mirroring: This strategy involves storing data on two locations, an on-site storage system and a remote site at the exact same time. Mirroring ensures that both sites are always identical, providing immediate data availability if one fails..
• RAID Protection: RAID (Redundant Array of Independent Disks) is a cost-effective alternative. It works by combining multiple physical drives into a single logical unit. RAID increases performance and protection because data is stored across different disks, allowing input/output operations to overlap efficiently.
• Erasure Coding: This technology is used in large-scale storage environments. It is a parity-based system where both the data and its parity (redundancy information) are spread across a cluster of storage nodes. If one node fails, the other nodes in the cluster work together to restore the lost data.
• Replication: Replication is a simpler method for scale-out storage where data is mirrored onto multiple nodes. While easier to manage than Erasure Coding, it requires more storage capacity, often consuming at least twice the space of the original protected data.

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2. Data Corruption

Snapshots: Snapshots are a crucial strategy for dealing with data corruption or accidental deletion. A snapshot creates a clean copy of the data at a specific moment in time. They are supported by various storage systems, including SQL Server and Oracle.

Snapshots offer:

• Instant Recovery: If data is corrupted or deleted, the organization can quickly load the stored snapshot, and the clean data is instantly copied back and replaced.
• Minimal Loss: By allowing for recurrent snapshots that can be stored for longer periods, they ensure that any data loss is kept to a minimum.

3. Failure of Storage System

When dealing with a potential failure of the storage system, Snapshot Replication is a key defense.

This technology builds on snapshots to prevent the failure of multiple drives in a data center:

Recovery: It ensures that replicated data is available for immediate recovery if the primary storage system fails completely, providing a robust backup solution.

How it Works: Snapshot technology copies data structures that have been changed on the primary storage system and sends them to an off-site secondary storage system.

4. Data Center Failure

Losing an entire data center requires a comprehensive disaster recovery plan to restore functionality quickly. Two key strategies are used here:

As mentioned previously, Snapshot Replication involves copying and replicating data to a secondary, geographically separate site.

• Drawback: The main limitation is the high cost of maintaining this secondary storage site.

Using Cloud Services combines replication technology with cloud-based backup solutions.

• Benefit: This enables speedy recovery if a data center breaks down. By storing the most recent and critical data copies in the cloud, organizations can access the relevant data needed for disaster recovery right away.

Trends in Data Protection

Ransomware

Ransomware is a type of malware that holds personal data hostage and forces victims (consumers or organizations) to pay a ransom to get their data back.

Over time, ransomware has become much more sophisticated. It can now infiltrate a system slowly so that when a backup is performed, the ransomware is included in the backup data itself.

IT experts are constantly working to counter these advanced threats. However, the inability to deal with this sophisticated malware means organizations may not be able to rely on a “clean” backup to restore their systems. This leaves data unprotected and unusable.

Therefore, it is absolutely crucial that organizations take steps to ensure backup data itself is protected and isolated from the main system.

Hyper-Convergence Infrastructure (HCI)

Hyper-Converged Infrastructure (HCI) is a unified system that combines traditional data center components storage, computing, networking, and management into a single platform.

HCI is becoming essential because its built-in data protection capabilities are replacing older data center equipment. This results in:

• Decreased complexity in the data center.
• Increased scalability for future growth.

Vendors now offer backup and recovery tools that support both HCI and non-HCI environments. Using HCI, organizations can easily:

• Build a private cloud.
• Extend their system to a public cloud.
• Achieve a true hybrid cloud setup.

Copy Data Management (CDM)

Copy Data Management (CDM) is a technology that helps organizations cut down on the number of data copies they need to store.

By reducing redundant copies, CDM offers several significant benefits:

• Lower Costs: It reduces the overall overhead for storage and data management, which lowers administrative expenses.
• Simplified Protection: It makes data protection simpler and more effective.
• Increased Productivity: It boosts the productivity of IT teams.

Artificial Intelligence and Machine Learning

Artificial Intelligence (AI) and Machine Learning (ML) are rapidly being adopted to enhance data protection efforts.

These technologies play a significant role by helping organizations detect potential cyberattacks before they can fully develop or materialize. This proactive approach strengthens overall data security measures.

Internet of Things (IoT)

Extra data protection measures are now essential because our devices are highly interconnected. This interconnectedness makes it easier for attackers to penetrate the system. Protecting data across these devices is crucial to ensuring user privacy.

The COVID-19 pandemic significantly accelerated our digital mindset. However, this rapid shift to the digital world introduces new issues, with data protection being a top concern. Therefore, the key challenge today is balancing the risks associated with digital life with the rewards it offers.

4eCheck out our course on Data Protection