What is Data Protection and Privacy?

Data Protection

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 solutions rely on technologies such as data loss prevention (DLP), storage with built-in data protection, firewalls, encryption, and endpoint protection.

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What Is Data Protection and Why Is It Important?

What Is Data Protection?

Data protection signifies the strategic and procedural steps undertaken to safeguard the privacy, availability, and integrity of sensitive data, and is often interchangeably used with the term ‘data security.’ These protective measures, critical for organizations that collect, process, or store sensitive data, aim to prevent data corruption, loss, or damage. In an era where data generation and storage are surging at an unprecedented rate, the importance of a robust data protection strategy is paramount. The primary goal of data protection is not just to safeguard sensitive information but to ensure that it remains accessible and reliable, thus preserving trust and compliance in data-centric operations.

What Are Data Protection Principles?

Data protection principles help protect data and make it available under any circumstances. It covers operational data backup and business continuity/disaster recovery (BCDR) and involves implementing aspects of data management and data availability.

Here are key data management aspects relevant to data protection:

  • Data availability—ensuring users can access and use the data required to perform business even when this data is lost or damaged.
  • Data lifecycle management—involves automating the transmission of critical data to offline and online storage.
  • Information lifecycle management—involves the valuation, cataloging, and protection of information assets from various sources, including facility outages and disruptions, application and user errors, machine failure, and malware and virus attacks.

Related content: Read our guide to data protection principles

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.

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.

Understanding the Data Protection Market

Data Protection Market Size and Growth

The global data protection market is growing rapidly as organizations invest more heavily in cybersecurity and data resilience. The market is valued at USD 172.67 billion and is projected to reach USD 656.47 billion by 2034, growing at a compound annual growth rate (CAGR) of 16.10%. North America accounts for the largest share of the market, driven by strong cybersecurity investment and increasing awareness of data-related risks.

This growth is largely fueled by the rising number of cyberattacks and data breaches. According to IBM, the average global cost of a data breach has reached USD 4.45 million, while organizations in the United States faced average losses of USD 9.44 million.

Major Market Segments

Data Loss Prevention (DLP) solutions currently represent one of the largest segments of the market. Organizations increasingly use data classification and DLP tools to monitor sensitive information and prevent unauthorized sharing or leakage.

Encryption, tokenization, and data masking solutions are expected to experience some of the fastest growth rates. These technologies help organizations protect confidential information stored in cloud platforms, databases, and enterprise applications.

Large enterprises currently account for the biggest share of the market because they manage extensive infrastructure and face higher cybersecurity risks. However, small and mid-sized enterprises (SMEs) are also increasing adoption of data protection tools due to growing use of cloud services, mobile devices, and BYOD policies.

From an industry perspective, the BFSI sector remains the largest adopter of data protection technologies due to strict compliance requirements and high exposure to cyber threats. Manufacturing is also becoming a major growth area as ransomware attacks increasingly target industrial operations.

Regional Market Overview

North America leads the global data protection market due to high cybersecurity spending, advanced IT infrastructure, and frequent cyber threats. The region continues to invest heavily in technologies such as AI-driven security platforms and cloud-based data protection systems.

Europe is another major market, supported by strong privacy regulations and growing digital transformation initiatives across finance, government, and retail sectors. GDPR compliance remains a key factor driving adoption.

Asia Pacific is expected to see strong growth due to rapid digitalization and expanding use of AI, cloud computing, and IoT technologies in countries such as China, India, Japan, and South Korea. Governments in the region are also introducing stricter cybersecurity laws, increasing demand for enterprise data protection solutions.

Latin America and the Middle East & Africa are also experiencing steady growth as organizations adopt cloud technologies and invest more in cybersecurity infrastructure.

What Are Data Protection Regulations?

Data protection regulations govern how certain data types are collected, transmitted, and used. Personal data includes various types of information, including names, photos, email addresses, bank account details, IP addresses of personal computers, and biometric data.

Data protection and privacy regulations vary between countries, states, and industries. For example, China has created a data privacy law that went into effect on June 1, 2017, and the European Union’s (EU) General Data Protection Regulation (GDPR) went into effect during 2018. Non-compliance may result in reputation damages and monetary fines, depending on the violation as instructed by each law and governing entity.

Compliance with one set of regulations does not guarantee compliance with all laws. Additionally, each law contains numerous clauses that may apply to one case but not another, and all regulations are subject to changes. This level of complexity makes it difficult to implement compliance consistently and appropriately.

Learn more in our detailed guides to:

5 Expert Tips that can help you better strengthen your Data Protection strategy

Jon Toor, CMO

With over 20 years of storage industry experience in a variety of companies including Xsigo Systems and OnStor, and with an MBA in Mechanical Engineering, Jon Toor is an expert and innovator in the ever growing storage space.

Establish a Zero Trust Architecture: Implement a Zero Trust approach, which assumes that threats can come from both inside and outside the network. Continuously verify user and device identities before granting access to data, even within the network perimeter.

Implement Data De-identification Techniques: Beyond encryption, use techniques like tokenization and pseudonymization to further protect sensitive data, especially when data is shared across departments or with third parties.

Regularly Review and Update Data Retention Policies: Ensure your data retention policies are regularly reviewed and updated in compliance with the latest regulations and best practices. Automatically delete data that is no longer needed to reduce exposure.

Implement Data Integrity Checks: Beyond backups, ensure that data integrity is maintained by using hash functions and digital signatures. Regularly audit data to detect and correct any unauthorized changes.

Use Immutable Storage for Critical Data: Adopt immutable storage solutions where data, once written, cannot be altered or deleted. This provides strong protection against ransomware attacks and unauthorized modifications.

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.

Learn more in our detailed guides to:

Data Protection Technologies and Practices to Protect Your Data

Protecting organizational data requires more than one security tool or policy. Effective data protection is built from multiple layers that help you identify sensitive information, control who can access it, prevent accidental or malicious exposure, recover from disruptions, and securely remove data when it is no longer needed. The following technologies and practices are commonly used together to create a strong data protection strategy.

Data Discovery

Before an organization can protect its data, it must first understand what data it has, where that data resides, who has access to it, and how it moves across systems. This process is known as data discovery. It is especially important for identifying sensitive or regulated information such as personally identifiable information, financial data, health records, intellectual property, credentials, contracts, and confidential business documents.

Data discovery helps organizations reduce blind spots. Once data is discovered, security teams can classify it, apply the correct protection controls, monitor access, and ensure compliance with internal policies and external regulations:

  • Inventory: The first step in data discovery is creating an accurate inventory of the data held across the organization. This includes structured data, such as databases and CRM records, as well as unstructured data, such as emails, documents, spreadsheets, images, PDFs, chat exports, and files stored in cloud collaboration platforms.
  • Classification: After inventorying the data, organizations classify it based on sensitivity, business value, regulatory requirements, and risk. Common classification levels include public, internal, confidential, restricted, and highly sensitive. For example, marketing materials may be classified as public, while customer payment details or employee records would be classified as highly sensitive. 
  • Data mapping: This step identifies where data is stored, how it moves, and which systems or users interact with it. This includes tracking data flows between applications, databases, cloud services, third-party vendors, APIs, backups, and reporting tools. For example, customer data may begin in a website form, move into a CRM system, sync with an email marketing platform, and then be exported into a BI dashboard. 
  • Automated discovery tools: Manual data discovery is difficult to maintain at scale. Automated data discovery tools help by scanning systems for sensitive information and identifying patterns such as credit card numbers, national identification numbers, health information, legal documents, source code, credentials, or confidential keywords.

Data Loss Prevention

Data Loss Prevention, or DLP, refers to technologies and processes that help prevent sensitive information from being accidentally leaked, intentionally stolen, or accessed by unauthorized users. DLP tools monitor data in three major states: data at rest, data in motion, and data in use.

Data at rest includes files stored on servers, endpoints, databases, or cloud storage. Data in motion includes information being sent through email, web uploads, messaging platforms, APIs, or file transfers. Data in use includes data being copied, printed, downloaded, pasted, screenshotted, or transferred to removable devices.

DLP is commonly used to protect personal data, financial records, intellectual property, legal documents, trade secrets, and regulated information:

  • DLP policies: These define how sensitive data should be handled. They specify what types of data need protection, who is allowed to access or share them, where the data can be stored, and what actions should be blocked, allowed, logged, or escalated. For example, a DLP policy might block employees from emailing customer credit card numbers outside the company.
  • Monitoring and alerts: DLP systems continuously monitor activity across endpoints, networks, email systems, cloud applications, and storage platforms. They can detect suspicious actions such as bulk downloads, unusual file transfers, unauthorized sharing, attempts to copy sensitive files to USB drives, or uploads to unmanaged web services. When a potential violation occurs, the DLP system can generate alerts for security teams, notify the user, create an audit log, or trigger an automated response. 
  • Remediation: Depending on the severity of the event and the policy involved, remediation may include blocking an email, encrypting an attachment, quarantining a file, removing public sharing permissions, revoking access, disabling an account, or notifying security administrators.

Storage with Built-In Data Protection

Storage systems are a critical part of data protection because they hold the organization’s most important information. Modern storage platforms often include built-in features that help maintain data availability, integrity, confidentiality, and resilience. These features may be available in on-premises storage arrays, cloud storage services, network-attached storage, object storage, and enterprise file systems.

Built-in data protection does not replace backups or security controls, but it provides an important foundation for preventing data loss and unauthorized access:

    • Redundancy: This protects data by storing multiple copies across different disks, nodes, systems, or locations. If one hardware component fails, another copy can be used to keep the data available. Common redundancy technologies include RAID, erasure coding, mirrored storage, clustered storage systems, and distributed cloud storage. 
    • Error correction: Error correction technologies help detect and repair data corruption. Data can become corrupted due to hardware faults, software bugs, power loss, transmission errors, or disk degradation. Storage systems often use checksums, parity data, integrity scans, and self-healing mechanisms to detect when data has changed unexpectedly.
  • Access controls: Storage systems often include granular access controls that define who can view, modify, delete, share, or administer data. These controls may be based on users, groups, roles, devices, network locations, or security policies. For example, an employee in the finance department may need access to payroll files, while employees in other departments should not be able to open or modify them. 

Backup

Backups are one of the most important data protection practices. A backup is a separate copy of data that can be used to restore information after accidental deletion, corruption, hardware failure, cyberattack, ransomware infection, or disaster.

A strong backup strategy should define what data is backed up, how often backups occur, where backups are stored, how long they are retained, who can access them, and how quickly they can be restored. Backups should also be tested regularly because an untested backup may fail when it is needed most:

  • Local and offsite backups:  Local backups are stored close to the production environment, such as on a local backup server, storage appliance, or nearby data center. They are useful because they can usually be restored quickly. Offsite backups are stored in a separate physical or cloud location. They protect against site-level incidents such as fire, flood, theft, power failure, or regional outage.
  • Incremental and full backups:  A full backup creates a complete copy of all selected data. It is simple to restore from but can require significant storage space and time to complete. An incremental backup captures only the data that has changed since the last backup. This reduces storage consumption and backup time, but restoration may require combining the last full backup with a chain of incremental backups.
  • Backup scheduling: This determines how often backups are created. The right schedule depends on how frequently data changes and how much data loss the organization can tolerate. For critical systems, backups may run continuously or several times per day. 

Snapshots

Snapshots are point-in-time copies of data, systems, or storage volumes. They allow organizations to preserve the state of data at a specific moment and quickly roll back if something goes wrong.

Snapshots are commonly used before software updates, configuration changes, database modifications, and other risky operations. They are also helpful during security incidents because they allow teams to restore systems to a known good state. However, snapshots are not a complete replacement for backups because they may depend on the same storage system and may not protect against all types of failure or compromise:

  • Instant recovery: One of the main advantages of snapshots is fast recovery. Instead of restoring large amounts of data from a traditional backup, administrators can revert a file, volume, virtual machine, or application to a previous state.
  • Versioning: Snapshots provide versioning by preserving multiple historical states of data. This allows administrators to compare changes over time, recover earlier versions of files, or investigate when a problem began. Versioning is particularly useful in environments where files are frequently modified, such as software development, document collaboration, and database management. 
  • Storage efficiency: Many snapshot technologies are storage-efficient because they use copy-on-write or redirect-on-write methods. Instead of copying all data each time, the snapshot stores only the changes made after the snapshot was created. This makes snapshots faster and less storage-intensive than traditional full copies. 

Replication

Replication involves creating and maintaining a copy of data, applications, or systems in another location. Unlike backups, which are often created at scheduled intervals, replication is typically designed to keep another environment closely synchronized with the primary one.

Replication can be synchronous, where data is written to both locations at the same time, or asynchronous, where data is copied after a short delay. Synchronous replication reduces data loss but can require low-latency connections. Asynchronous replication is more flexible across long distances but may result in some data loss if the primary system fails before changes are copied:

  • Failover: This is the process of switching operations from a primary system to a replicated secondary system when the primary system becomes unavailable. This helps maintain business continuity during outages, hardware failures, cyber incidents, or disasters.
  • Failback: This occurs after the primary system has been repaired or restored. During failback, operations are moved back from the secondary environment to the original environment. A well-designed failover and failback process should be tested regularly to ensure that systems, data, applications, and dependencies work as expected.
  • Load balancing: Replication can also support load balancing by distributing traffic or workloads across multiple systems or locations. This can improve performance, reduce pressure on a single system, and increase availability. For example, read replicas of a database can handle reporting or analytics workloads while the primary database handles transactions. 
  • Geographical redundancy: This means storing replicated data in different physical regions. This protects the organization from localized disruptions such as power outages, natural disasters, network failures, or regional cloud service interruptions.

Firewalls

Firewalls protect data by controlling network traffic between trusted and untrusted environments. They act as a security barrier between internal systems, cloud environments, remote users, applications, and the public internet.

Firewalls can enforce rules based on IP addresses, ports, protocols, users, applications, device posture, or traffic behavior. Modern firewalls often include advanced features such as deep packet inspection, intrusion prevention, malware filtering, encrypted traffic inspection, and application-aware controls:

  • Intrusion detection and prevention: Many modern firewalls include Intrusion Detection System and Intrusion Prevention System capabilities, often referred to as IDS and IPS. These features inspect traffic for known attack patterns, suspicious behavior, exploit attempts, malware communication, scanning activity, and policy violations. An IDS detects and alerts security teams about suspicious activity, while an IPS can actively block or disrupt malicious traffic. 
  • Application control: This allows firewalls to identify and manage traffic based on the application being used, rather than only the port or protocol. This is important because many applications use standard web traffic, making them harder to control with traditional firewall rules alone. For example, an organization may allow business-approved cloud storage while blocking personal file-sharing services. 
  • Traffic monitoring: Firewalls provide visibility into traffic entering, leaving, and moving within an organization’s network. This monitoring helps security teams identify unusual patterns, such as large outbound transfers, communication with known malicious domains, repeated failed connection attempts, or traffic from unexpected locations.

Authentication and Authorization

Authentication and authorization ensure that only the right people, devices, and services can access data. Authentication verifies identity, while authorization determines what that verified identity is allowed to do.

Together, these controls help prevent unauthorized access, reduce insider risk, limit the damage caused by compromised accounts, and support compliance requirements. Strong authentication and authorization should apply across applications, cloud services, databases, storage systems, endpoints, and administrative tools:

  • Multi-factor authentication: MFA strengthens login security by requiring users to provide more than one form of verification. These factors usually include something the user knows, such as a password; something the user has, such as a mobile authenticator app or hardware security key; and something the user is, such as a fingerprint or facial recognition.
  • Role-based access control: RBAC assigns permissions based on a user’s job role. Instead of assigning permissions individually to every user, administrators define roles such as finance manager, HR specialist, system administrator, developer, or sales representative. Each role receives the access required to perform its responsibilities.
  • Identity and access management: IAM, systems centralize the management of users, groups, roles, permissions, authentication methods, and access policies. IAM platforms often integrate with single sign-on, MFA, directory services, cloud platforms, SaaS applications, and privileged access management tools.

Encryption

Encryption protects data by converting readable information into unreadable ciphertext. Only authorized parties with the correct key can decrypt and read the original information. Encryption is used to protect data at rest, such as files, databases, disks, and backups, and data in transit, such as web traffic, emails, API calls, and file transfers. Even if an attacker gains access to encrypted data, they cannot easily use it without the encryption keys.

Types of encryption include:

  • Symmetric encryption: Uses the same key to encrypt and decrypt data. It is fast and efficient, making it well-suited for encrypting large amounts of data such as files, databases, disks, and backup archives.
  • Asymmetric encryption: Also known as public-key encryption, uses two mathematically related keys: a public key and a private key. The public key can be shared, while the private key must remain secret.
  • End-to-end encryption: Protects data from the sender to the intended recipient. The data is encrypted before it leaves the sender’s device and can only be decrypted by the recipient. Intermediaries, such as service providers, network operators, or cloud platforms, cannot read the encrypted content.

Endpoint Protection

Endpoints include laptops, desktops, smartphones, tablets, servers, and other devices that connect to organizational systems. Because endpoints are used directly by employees and often operate outside traditional network boundaries, they are frequent targets for phishing, malware, ransomware, credential theft, and unauthorized access.

Endpoint protection technologies help secure these devices, monitor activity, enforce policies, and respond to threats. Modern endpoint security often includes antivirus, anti-malware, endpoint detection and response, device management, encryption, patching, and remote wipe capabilities:

  • Antivirus and anti-malware: These tools detect, block, quarantine, and remove malicious software. These tools protect against threats such as viruses, worms, trojans, ransomware, spyware, keyloggers, and malicious scripts. Traditional antivirus tools rely heavily on known signatures, while modern solutions often use behavioral analysis, machine learning, reputation scoring, and threat intelligence.
  • Device management: Allows organizations to control and secure endpoints from a central platform. Mobile Device Management, or MDM, and Unified Endpoint Management, or UEM, tools can enforce security settings, require encryption, manage applications, restrict risky configurations, monitor compliance, and remotely lock or wipe lost devices.
  • Patch management: The process of identifying, testing, deploying, and verifying software updates. These updates often fix security vulnerabilities that attackers could exploit. A strong patch management program covers operating systems, browsers, productivity tools, servers, databases, firmware, third-party applications, and security tools. 

Data Erasure

Data erasure is the secure and permanent removal of data from systems, storage media, applications, backups, and devices. It is necessary when data reaches the end of its retention period, employees leave the organization, devices are retired, storage media is reused, or sensitive information is no longer needed.

Simply deleting a file is usually not enough because deleted data may still be recoverable from storage media. Secure data erasure ensures that information cannot be reconstructed or accessed later:

  • Secure erasure methods: Traditional hard drives may be overwritten with new data, degaussed using a strong magnetic field, or physically destroyed. Solid-state drives require different methods because wear leveling can make simple overwriting unreliable. For SSDs and modern storage systems, organizations may use cryptographic erasure, secure erase commands, vendor-approved sanitization tools, or physical destruction.
  • Data destruction policies: A data destruction policy defines when and how data should be securely erased. It should specify retention periods, responsible teams, approval workflows, erasure methods, documentation requirements, and exceptions for legal holds or investigations.
  • Certification and auditing: These provide evidence that data erasure was completed properly. For highly sensitive information or regulated industries, organizations may require certificates of destruction or detailed erasure reports that include the device identifier, method used, date, responsible party, and verification result. Audits help confirm that data destruction procedures are followed consistently and remain aligned with legal, regulatory, and contractual requirements. 

Disaster Recovery

Disaster recovery is the process of preparing for and recovering from major events that disrupt systems, applications, infrastructure, or data availability. These events may include cyberattacks, ransomware, hardware failures, cloud outages, natural disasters, power failures, human error, or facility damage.

A disaster recovery strategy focuses on restoring critical systems and data quickly enough to maintain business continuity. It should be closely aligned with backup, replication, incident response, business continuity, and risk management programs:

  • Business impact analysis: An BIA identifies the organization’s most critical processes, systems, applications, and data. It evaluates how disruptions would affect operations, revenue, customers, employees, compliance obligations, and reputation. The BIA helps determine recovery priorities and defines key recovery metrics such as Recovery Time Objective and Recovery Point Objective. 
  • Disaster recovery plan: Documents the steps required to restore systems and data after a disruption. It should include recovery procedures, roles and responsibilities, communication plans, escalation paths, vendor contacts, backup and replication details, system dependencies, and decision-making authority.
  • Testing and maintenance: Disaster recovery plans must be tested regularly to confirm that they work. Testing may include tabletop exercises, backup restoration tests, failover simulations, full disaster recovery drills, and application-level recovery validation. Maintenance is equally important because systems, teams, vendors, applications, and business priorities change over time.

Related content: Read our guide to data protection impact assessment

Critical 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.

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.

Related content: Read our guide to data protection impact assessment

Minimize 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.

Be Open with 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.

Here are some important trends driving the evolution of data protection.

Data Portability and Data Sovereignty

Data portability is an important requirement for many modern IT organizations. It means the ability to move data between different environments and software applications. Very often, data portability means the ability to move data between on-premises data centers and the public cloud, and between different cloud providers.

Data portability also has legal implications—when data is stored in different countries, it is subject to different laws and regulations. This is known as data sovereignty.

Related content: Read our guide to Data sovereignty

Traditionally, data was not portable and it required huge efforts to migrate large datasets to another environment. Cloud data migration was also extremely difficult, in the early days of cloud computing. New technical methods are developing to make migration easier, and thus make data more portable.

A related issue is portability of data within clouds. Cloud service providers tend to have proprietary data formats, templates, and storage engines. This makes it difficult to move data from one cloud to another, and creates vendor lock in. Increasingly, organizations are looking for standardized ways of storing and managing data, to make it portable across clouds.

Learn more in our detailed guides about:

Mobile Data Protection

Mobile device protection refers to measures designed to protect sensitive information stored on laptops, smartphones, tablets, wearables and other portable devices. A fundamental aspect of mobile device security is preventing unauthorized users from accessing your corporate network. In the modern IT environment, this is a critical aspect of network security.

There are many mobile data security tools, designed to protect mobile devices and data by identifying threats, creating backups, and preventing threats on the endpoint from reaching the corporate network. IT staff use mobile data security software to enable secure mobile access to networks and systems.

Common capabilities of mobile data security solutions include:

  • Enforcing communication via secure channels
  • Performing strong identity verification to ensure devices are not compromised
  • Limiting the use of third-party software and browsing to unsafe websites
  • Encrypting data on the device to protect against device compromise and theft
  • Perform regular audits of endpoints to discover threats and security issues
  • Monitoring for threats on the device
  • Setting up secure gateways that can allow remote devices to connect securely to the network

Ransomware

Ransomware is a rising cybersecurity threat, which is a top security priority for almost all organizations. Ransomware is a type of malware that encrypts user data and demands a ransom in order to release it. New types of ransomware send the data to attackers before encrypting it, allowing the attackers to extort the organization, threatening to make its sensitive information public.

Backups are an effective defense against ransomware—if an organization has a recent copy of its data, it can restore it and regain access to the data. However, ransomware can spread across a network over a long period of time, without encrypting files yet. At this stage ransomware can infect any connected system, including backups. When ransomware spreads to backups, it is “game over” for data protection strategies, because it becomes impossible to restore the encrypted data.

There are multiple strategies for preventing ransomware and in particular, preventing it from spreading to backups:

  • The simplest strategy is to use the old 3-2-1 backup rule, keeping three copies of the data on two storage media, one of which is off premises.
  • Security vendors have advanced technologies that can detect ransomware at its early stages, or in the worst case, block encryption processes as they begin.
  • Storage vendors are offering immutable storage, which ensures that data cannot be modified after it is stored. Learn how Cloudian secure storage can help protect your backups from ransomware.

Related content:
Read our guide to ransomware data recovery
Read our guide to data security

Copy Data Management (CDM)

Large organizations have multiple datasets stored in different locations, and many of them may duplicate data between them.

Duplicate data creates multiple problems—it increases storage costs, creates inconsistencies and operational issues, and can also result in security and compliance challenges. Typically, not all copies of the data will be secured in the same way. It is no use securing a dataset and ensuring it is compliant, when the data is duplicated in another unknown location.

CDM is a type of solution that detects duplicate data and helps manage it, comparing similar data and allowing administrators to delete unused copies.

Disaster Recovery as a Service

Disaster recovery as a service (DRaaS) is a managed service that gives an organization a cloud-based remote disaster recovery site.

Traditionally, setting up a secondary data center was extremely complex and involved massive costs, and was only relevant for large enterprises. With DRaaS, any size organization can replicate its local systems to the cloud, and easily restore operations in case of a disaster.

DRaaS services leverage public cloud infrastructure, making it possible to store multiple copies of infrastructure and data across multiple geographical locations, to increase resiliency.

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.

Learn More About Data Protection and Privacy

Keeping Up with Data Protection Regulations

Data Availability: Ensuring the Continued Functioning of Business Operations

How You Can Maintain Secure Data Storage

Data Encryption: An Introduction

Continuous Data Protection

GDPR Data Protection

S3 Object Lock — Protecting Data for Ransomware Threats and Compliance

Office 365 Data Protection. It is Essential

Secure Data Storage

Data Encryption

See Additional Guides on Key Data Breach Topics

Together with our content partners, we have authored in-depth guides on several other topics that can also be useful as you explore the world of data breaches.

Data Architecture

Authored by Instaclustr

Ransomware Protection

Authored by N2WS

Data Leakage

Authored by BlueVoyant

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