Data Protection and Privacy: 7 Ways to Protect User Data
The terms data protection and data privacy are often used interchangeably, but there is an important difference between the two. Data privacy defines who has access to data, while data protection provides tools and policies to actually restrict access to the data. Compliance regulations help ensure that user’s privacy requests are carried out by companies, and companies are responsible to take measures to protect private user data.
Data protection and privacy is typically applied to personal health information (PHI) and personally identifiable information (PII). It plays a vital role in business operations, development, and finances. By protecting data, companies can prevent data breaches, damage to reputation, and can better meet regulatory requirements.
Data protection relies on technologies such as data loss prevention (DLP), storage with built-in data protection, firewalls, encryption, and endpoint protection.
In this article, you will learn:
- What is data protection
- What is data privacy and why it is important
- Data protection vs data privacy
- Data protection technologies and practices
- Best practices for ensuring data privacy
- Data protection and privacy with Cloudian HyperStore
What Is Data Protection?
Data protection is a set of strategies and processes you can use to secure the privacy, availability, and integrity of your data. It is sometimes also called data security or information privacy.
A data protection strategy is vital for any organization that collects, handles, or stores sensitive data. A successful strategy can help prevent data loss, theft, or corruption and can help minimize damage caused in the event of a breach or disaster.
For information about data protection in the cloud, refer to our guide: Data Protection in the Cloud: Challenges and Best Practices.
What Is Data Privacy and Why Is it Important?
Data privacy is a guideline for how data should be collected or handled, based on its sensitivity and importance. Data privacy is typically applied to personal health information (PHI) and personally identifiable information (PII). This includes financial information, medical records, social security or ID numbers, names, birthdates, and contact information.
Why is data privacy important?
Data privacy concerns apply to all sensitive information that organizations handle, including that of customers, shareholders, and employees. Often, this information plays a vital role in business operations, development, and finances.
Data privacy helps ensure that sensitive data is only accessible to approved parties. It prevents criminals from being able to maliciously use data and helps ensure that organizations meet regulatory requirements.
Data privacy is enforced by data protection regulations. Non-compliance may result in monetary fines or loss of brand authority. You can learn more about regulations in our article about Keeping Up with Data Protection Regulations.
Data Protection vs Data Privacy
Although both data protection and privacy are important and the two often come together, these terms do not represent the same thing.
One addresses policies, the other mechanisms
Data privacy is focused on defining who has access to data while data protection focuses on applying those restrictions. Data privacy defines the policies that data protection tools and processes employ.
Creating data privacy guidelines does not ensure that unauthorized users don’t have access. Likewise, you can restrict access with data protections while still leaving sensitive data vulnerable. Both are needed to ensure that data remains secure.
Users control privacy, companies ensure protection
Another important distinction between privacy and protection is who is typically in control. For privacy, users can often control how much of their data is shared and with whom. For protection, it is up to the companies handling data to ensure that it remains private. Compliance regulations reflect this difference and are created to help ensure that users’ privacy requests are enacted by companies.
7 Data Protection Technologies and Practices that Can Help You Protect User Data
When it comes to protecting your data, there are many storage and management options you can choose from. Solutions can help you restrict access, monitor activity, and respond to threats. Here are some of the most commonly used practices and technologies:
- Data loss prevention (DLP)—a set of strategies and tools that you can use to prevent data from being stolen, lost, or accidentally deleted. Data loss prevention solutions often include several tools to protect against and recover from data loss.
- Storage with built-in data protection—modern storage equipment provides built-in disk clustering and redundancy. For example, Cloudian’s Hyperstore provides up to 14 nines of durability, low cost enabling storage of large volumes of data, and fast access for minimal RTO/RPO.
- Firewalls—utilities that enable you to monitor and filter network traffic. You can use firewalls to ensure that only authorized users are allowed to access or transfer data.
- Authentication and authorization—controls that help you verify credentials and assure that user privileges are applied correctly. These measures are typically used as part of an identity and access management (IAM) solution and in combination with role-based access controls (RBAC).
- Encryption—alters data content according to an algorithm that can only be reversed with the right encryption key. Encryption protects your data from unauthorized access even if data is stolen by making it unreadable. Learn more in our article: Data Encryption: An Introduction.
- Endpoint protection—protects gateways to your network, including ports, routers, and connected devices. Endpoint protection software typically enables you to monitor your network perimeter and to filter traffic as needed.
- Data erasure—limits liability by deleting data that is no longer needed. This can be done after data is processed and analyzed or periodically when data is no longer relevant. Erasing unnecessary data is a requirement of many compliance regulations, such as GDPR. For more information about GDPR, check out our guide: GDPR Data Protection.
Best Practices for Ensuring Data Privacy
Creating policies for data privacy can be challenging but it’s not impossible. The following best practices can help you ensure that the policies you create are as effective as possible.
Practice minimal data collection
Ensure that your policies dictate that only necessary data is collected. If you collect more than what you need, you increase your liability and can create an undue burden on your security teams. Minimizing your data collection can also help you save on bandwidth and storage.
One way of achieving this is to use “verify not store” frameworks. These systems use third-party data to verify users and eliminate the need to store or transfer user data to your systems.
Include your users
Many users are aware of privacy concerns and are likely to appreciate transparency when it comes to how you’re using and storing data. Reflecting this, GDPR has made user consent a key aspect of data use and collection.
You can be sure to include users and their consent in your processes by designing privacy concerns into your interfaces. For example, having clear user notifications outlining when data is collected and why. You should also include options for users to modify or opt-out of data collection.
Inventory your data
Part of ensuring data privacy is understanding what data you have, how it is handled, and where it is stored. Your policies should define how this information is collected and acted upon. For example, you need to define how frequently data is scanned for and how it is classified once located.
Your privacy policies should clearly outline what protections are needed for your various data privacy levels. Policies should also include processes for auditing protections to ensure that solutions are applied correctly.
Data Protection and Privacy with Cloudian HyperStore
Data protection requires powerful storage technology. Cloudian’s storage appliances are easy to deploy and use, let you store Petabyte-scale data and access it instantly. Cloudian supports high-speed backup and restore with parallel data transfer (18TB per hour writes with 16 nodes).
Cloudian provides durability and availability for your data. HyperStore can backup and archive your data, providing you with highly available versions to restore in times of need.
In HyperStore, storage occurs behind the firewall, you can configure geo boundaries for data access, and define policies for data sync between user devices. HyperStore gives you the power of cloud-based file sharing in an on-premise device, and the control to protect your data in any cloud environment.
Learn more about data protection with Cloudian.