What is Data Protection?

What is Data Protection?

Data protection is the process of safeguarding sensitive data from loss, leakage, or corruption. It ensures that the data remains available, confidential, accurate, and compliant with the regulatory requirements.

With organizations increasingly expanding their reliance on digital information for business operations, data protection has become mandatory for compliance adherence and customer trust.

At its core, data protection involves safeguarding data as well as ensuring its availability, even in the event of a breach or encryption via malware or ransomware, since even a short span of downtime can wreak havoc for organizations - both financially and in terms of brand value.

Thus, data protection isn't just a typical feature - rather, it is a practice that encompasses multiple facets of endpoint security, including peripheral device control, data leakage prevention, malware and ransomware protection, and browser monitoring to prevent phishing attacks.

What are the Core Principles of Data Protection?

Data protection revolves around a fundamental framework, popularly known as the CIA triad. Here's a breakdown:

1. Confidentiality

This ensures that only the right people access the information, thereby focusing on preventing sensitive data/information from unauthorized access or disclosure. Be it customer records, credentials, financial data, or confidential healthcare data - individuals with legitimate permissions are allowed to access the data.

Confidentiality is implemented through various measures such as access control (passwords, MFA, etc.), encryption, zero-trust policies, and data classification to segregate the types of sensitive data and enhance data protection.

2. Integrity

Integrity of the data ensures that it remains unadulterated, complete, and accurate throughout its lifecycle - unless authorized modifications are made. Malware infections, accidental changes, and man-in-the-middle attacks pose a threat to the integrity of the data, and in some cases, even minor changes in the data can cause a chain reaction of errors, including financial misrepresentations, supply chain disruption, and more.

To maintain data integrity, there are several methods, such as tampering detection via checksum and hashing, digital signatures to verify data, and maintaining versioning and audit trails.

3. Availability

Availability of data is yet another important part of data security. Availability ensures that the systems, applications, and all of the required data are available at all times, irrespective of breaches or downtime.

There are several challenges to ensuring the availability of data, including malware intrusions, DDoS attacks, natural disasters, and capacity limitations. To ensure data availability, some of the steps that are taken include clustering and load balancing to reduce redundancy, regular backups and disaster recovery plans, and continuous monitoring to identify outages and threats early.

These three components of the CIA triad ensure efficient data protection and security across organizations.

Why is Data Protection Important?

1. Preventing loss or corruption of data

Data loss prevention forms one of the primary goals of endpoint security solutions. With dedicated modules such as device control and ransomware protection, data loss can be prevented to the maximum extent.

Even then, in case of accidental breaches and corruption, regular and incremental backups ensure that recoverable copies of the data still exist.

2. Maintaining business continuity and customer trust

Organizations heavily rely on data for even the most basic operations. Hence, the inability to access the data leads to disasters and a complete stoppage of operations. With data protection strategies and disaster recovery processes in place, such incidents can be smoothly resolved without creating disruption to business continuity.

Furthermore, customers trust a business or a company with their personal data. As a result, news of data breaches or business disruptions greatly affects customer morale and the brand value in the long term.

3. Adhering to compliance guidelines and legal requirements

As privacy concerns increase, nations are more focused on regulating the storage and use of customer data. With regulations like GDPR, DPDPA, HIPAA, CCPA, and PCI DSS in place, businesses must ensure that the customer's data (personal, medical, or financial) is handled with utmost care.

Most of these compliance regulations mandate scheduled audits and enforce strict guidelines on how the data should be managed, monitored, and stored. Non-compliance with these guidelines can lead to legal consequences and fines. Hence, implementing data protection and security is a prerequisite for compliance adherence.

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What are the Key Components of Data Protection?

The explosive growth in vulnerabilities and ingenious cyber attack techniques over the years renders traditional antivirus solutions obsolete. Hence, endpoint security platforms that combine multi-faceted detection and remediation approaches are the ideal solution now for securing enterprise networks.

1. Prevention and Hardening:

Data protection, as a strategy, requires a combination of both technical prowess and governance frameworks. Below is a breakdown of the components involved in ensuring the protection and security of data:

2. Regular data backups

These backups create secure, accessible copies of data that can be restored in case the original data is corrupted or accidentally deleted. Data backups include full, incremental, and differential backups - based on the requirement.

3. Disaster Recovery (DR)

In the unfortunate event of an outage or a cyberattack, disaster recovery ensures that the data can be restored as quickly as possible - thereby preventing downtime. Some of the key components of disaster recovery are off-site backup storage, failover, and fallback mechanisms.

Additionally, there are hot, warm, and cold sites that vary in cost and the type of data stored. All of these combined ensure rapid data protection and seamless disaster recovery.

4. Data Encryption

With all of the data protection measures in place, even if the data is intercepted, data encryption ensures that the data remains unreadable. Data is typically classified into three types (as mentioned below), and is at threat of cyberattacks in all three.

• Data at rest is when the data isn't moving between devices or networks. Such data can be secured by using encryption and data loss prevention solutions.
• Data in transit when the data is moving from one location to another, be it via email, message, etc. This form of data can be protected by using encryption and authentication, such as the use of secure protocols like HTTPS, TLS, or a VPN.
• Data in use when the data is being used, read, or modified. This form of data can be protected through MFA, strong passwords, and general user education.

5. Access Control and Identity Management

One of the major reasons for a data breach is unauthorized access. To curb that, strong governance practices coupled with authentication and authorization should be implemented to ensure that only the authorized employees/individuals have access to the data.

Role-based access control (RBAC), Zero Trust access, and Privileged Access Management (PAM) are some of the techniques that can minimize risks from compromised credentials, misuse of privilege, and other insider threats.

6. Monitoring Data Integrity

Data protection also requires preventing unauthorized access to it. To ensure that the data is unadulterated and trustworthy, several techniques such as checksum verification, digital signatures, and audit trails are used.

Continuously monitoring the data for unauthorized edits or changes helps detect signs of corruption or any other suspicious activity early on, thus preventing any further damage.

What are the Best Practices for Data Protection?

Securing and protecting data requires a combination of strong technical and security protocols, coupled with user awareness and governance policies within the organization.

1. Real-time inventory and data classification

Enterprises store and access vast amounts of data on a daily basis, but not all of it needs to be secured with the same level of protection. Hence, the network should be monitored in real-time to account for newer/obsolete IT assets and shadow IT.

Additionally, data should be classified based on the priority, i.e., Internal, Confidential, Public, and so on. Based on the classification, teams should strategize data protection to ensure that the critical data receives maximum protection.

2. Data encryption wherever possible

Even if you feel that you have maxed out on data protection, it is always important to be aware. Data encryption acts as an added layer of security, wherein even if the data is intercepted, encryption ensures that the data remains unreadable.

It is recommended to encrypt data at rest and in transit. Some of the best encryption practices include using AES-256 and TLS 1.2, as well as masking the sensitive fields in the data.

3. Secure access controls and zero-trust security

The first step to data security and protection is to limit access to only authorized personnel. Using role-based access control (RBAC) and implementing zero-trust policies greatly reduces the scope of data access. Furthermore, when it comes to sensitive data, it is best to restrict the data on a need-to-know basis.

4. Regular backups

To ensure the availability of data at all times, it is important to have scheduled and regular backups. Some of the recommended backup strategies include performing full backups and then scheduling incremental backups.

Moreover, the backups should be periodically tested and restored for verification and seamless disaster recovery.

5. Monitoring data activity to detect anomalies

To ensure early detection of breaches, insider threats, and any accidental misuse, it is imperative to monitor the data and related activities. Security teams can leverage User Behaviour Analytics, Security Information and Event Management (SIEM), and File Integrity Monitoring (FIM) to detect anomalies and policy violations early on.

Data Protection Technologies

To ensure the CIA triad of data protection, organizations use multiple strategies and techniques, including:

• Data Loss Prevention (DLP) helps organizations monitor and secure how sensitive information is being accessed and shared. These solutions extend their scopes to endpoints, cloud applications, and networks to prevent data breaches and any unauthorized access.
• Endpoint Security Solutions involve multiple functionalities that collectively secure endpoints and prevent data from being breached, for instance, through device control and browser control.Additionally, Endpoint Detection and Response monitors the endpoints in real time to proactively identify threats with behavioural analytics, file integrity monitoring, threat analytics, and so on.
• Data Backup and Disaster Recovery safeguard the data in case of unforeseen events, breaches, and natural disasters. Full, incremental, and differential backups coupled with cloud-based storage are some of the most-used practices.
  To further strengthen the process of disaster recovery with site replication and failover, Continuous Data Protection (CDP) ensures that the data remains recoverable and available, even in the most critical scenarios.
• Firewalls and Network Security Solutions create a secure boundary between internal and external networks, thereby inspecting, filtering, and controlling the traffic. Additionally, deeper packet inspections combined with other security engines enable firewalls to block malicious traffic, prevent lateral movements, and implement granular controls.

 

FAQs on Data Protection

1. What are the 3 elements of data protection?

The three key elements of data protection are:

• Confidentiality to ensure data access to only the authorized users.
• Integrity to maintain data accuracy and prevent tampering.
• Availability to ensure that the data is accessible whenever required.

2. What is an example of protected data?

An example of protected data can be the details of information that give out an individual's identity, such as name, address, medical records, or biometric data. Such data should be protected in accordance with data governance rules.

3. Who is responsible for data protection?

Data protection in an organization is a shared responsibility. An ideal data protection framework involves the leadership and the Data Protection Officer (DPO) defining the policies, IT teams implementing the required security measures, and employees following safe data practices.

4. What are the golden rules of data protection?

The golden rules of data protection are:

• Collecting only the necessary data
• Securing the collected data and maintaining accuracy
• Limiting access to data on a need-to-know basis
• Deleting the data when no longer in use
• Being transparent about how the data is used

5. Is GDPR the same as data protection?

No, GDPR and data protection are not the same. GDPR is a specific data protection law in the EU, while data protection is the broader practice of securing and managing organizational and personal data.

About the author



Anupam Kundu is a Product Specialist at ManageEngine in the Unified Endpoint Management and Security suite. With a background in digital marketing, his expertise includes creating technical and long-form content for SEO and user education in the IT and cybersecurity domain.