What Is Data Security?

Data security is the practice of safeguarding digital information from unauthorized access, accidental loss, theft, modification, manipulation, or corruption throughout its entire lifecycle. As a critical component of an organization's cybersecurity, it aims to ensure data confidentiality, integrity, and availability.

Data security vs. data protection vs. data privacy

While often used interchangeably, these terms have distinct meanings related to safeguarding data:

  • Data Protection: The goal of data security. It encompasses legal, regulatory, and organizational measures to ensure data is handled responsibly and securely.
  • Data Security: The technical measures and processes implemented to protect data from unauthorized access, use, disclosure, disruption, modification, or destruction. Typically, it involves encrypting data, preventing data leakage, managing insider threats, and securing sensitive information at every touchpoint.
  • Data Privacy: Focuses on the legal and ethical guidelines around how individuals' personal information is collected, used, and shared. It includes global regulations, like PIPL and CCPA, that ensure individuals have the right to control their data.

The importance of data security

A strong data security posture protects the data that matters. In the face of evolving threats. It is vital for organizations of all sizes, as it helps to:

Foster Trusted Relationships: Build and maintain trust with customers, vendors, partners, and employees by demonstrating a commitment to ensure their data is handled securely.

Gain a Competitive Edge: Organizations can use data as a valuable business asset effectively and securely to get ahead of the competition.

Maintain Regulatory Compliance: Avoid costly fines and penalties associated with data breaches, failed audits,  and non-compliance with regulations.

What types of sensitive data need to be secured?

Not all data is created equal—some types of information require additional protection due to their sensitivity or the potential consequences of their exposure. These include:

  • Personally Identifiable Information (PII): Data that can be used to identify individuals for theft and fraud, such as names, addresses, phone numbers, social security numbers, and email addresses. This includes customer, vendor, and employee data.
  • Financial Data: Credit card numbers, bank account details, transaction records, and financial statements.
  • Health Information (PHI): Patient data, such as diagnoses, treatment plans, and test results.
  • Intellectual Property (IP): Confidential information that gives an organization a competitive advantage, such as trade secrets, patents, and designs.
  • Business Operations Data: Supply chain details, production processes, vendor relationships, or other information related to business operations. Disrupting or leaking this data could cause significant financial losses.
  • Code and Software Designs: Source code, software designs, patents, and other technical information that is critical to an organization's operations.

Data security core concepts

A robust data security strategy encompasses several core concepts that protect data at all stages of its lifecycle.

What is the Data Lifecycle?

The data lifecycle refers to the journey data takes from its initial creation to its eventual deletion. A comprehensive data security plan ensures that every phase is covered. 

  • Creation: Data is created and stored.
  • Storage: Data is stored in various locations, such as databases, file systems, and cloud storage.
  • Use: Data is accessed, edited, and updated by authorized users.
  • Sharing: Data is shared with other individuals or organizations.
  • Deletion: Data is deleted or archived when it is no longer needed.

Find and Classify Sensitive Information: Identify and categorize data based on its sensitivity, regulatory requirements, and value to the organization.

Monitor and Control How Data is Shared: Track how data is accessed and shared to ensure data is only shared with authorized individuals and systems.

Limit Access to Data: Using encryption to ensure data access is restricted to authorized users, creating permissions and controls to restrict sensitive data sharing.

Detect Data Anomalies: Monitor data for unusual access patterns or activities (i.e., unusual login times or data transfers) that may indicate a security breach or data leak.

Automate response actions: Trigger automated responses to mitigate the impact of data security incidents.

Deliver Detailed Reporting: Provide detailed reports, forensics, and audit trails to demonstrate compliance with regulations and investigate security incidents. 

Broad Coverage Protection: Protect data as it is created, shared, and stored, regardless of its location, whether it's on-premises, in the cloud, or on network shared drives.

Data in motion vs. data at rest vs. data in use

Data security measures must be tailored to the different states of data:

  • Data in Motion: Data actively moving through networks, including transferring between devices, sent through emails, or shared over the web.
  • Data at Rest: Data stored in repositories on endpoints, network file servers, databases, cloud storage, etc.
  • Data in Use: Data in use for active editing, saving, or printing by preventing unauthorized actions that could result in leakage.

Unstructured vs. structured data

Data security measures must also consider the different types of data:

  • Structured data is highly organized in a predefined format, like a database table, that makes it easily searchable. Security strategies for structured data involve database activity monitoring and strict access controls.
  • Unstructured data lacks a predefined format, such as including emails, documents, and images. Because it lacks a consistent format, it is challenging to protect, and often, advanced DLP solutions are utilized.

Top data security threat vectors

Data is at risk from a variety of threat vectors, each requiring its own set of protections:

Endpoints: Personal computers, laptops, and servers that have access to and store sensitive data. Data Loss Prevention endpoint security solutions and data encryption protect endpoints.

Email & Web: Email and web applications that are used to share and access data. Endpoint DLP and/or Network DLP solutions can stop sensitive information from being shared over email and the web.

Network Storage: Network-accessible storage repositories that store data for individuals or multiple users. DLP and encryption tools help secure network storage.

Databases: Databases that store sensitive information, such as customer data, financial records, and health records. Database activity monitoring tracks user access and other unusual activity that may indicate a breach. DLP tools can also be applied to stop data exfiltration from databases.

Cloud Applications: Cloud-based applications that store and process data, such as SaaS applications and cloud storage services. CASB technology, which integrates with DLP tools, extends protection into the cloud.

Data security challenges

While securing data is essential, it's not without its challenges that tools have to address:

Insider Risk: Malicious or negligent employees or contractors can expose sensitive data.

  • Accidental Exposure: Misconfigurations or human error, such as sending confidential information to the wrong recipient, can lead to data being accidentally exposed to unauthorized users. 
  • Intentional Data Leakage: Employees or external actors may intentionally leak data for personal gain or to harm the organization.
  • Misconfigurations: Security misconfigurations can create vulnerabilities that attackers can exploit to access data.

Ransomware: Malicious actors can encrypt data and hold it hostage until a ransom is paid.

Zero Trust Security Model: As the name suggests, zero trust assumes that no one inside or outside the organization is trustworthy, requiring continuous verification at every access point, making it difficult to implement and scale.

Data Expansion: The increasing volume and complexity of data make it challenging to track and protect everything. Solutions must scale with the data. 

Complexity of Compliance: Organizations must comply with a growing number of data privacy laws and regulations, making it difficult to manage.

Data security compliance & regulations

Organizations must comply with a multitude of privacy laws and regulations, each with specific requirements for data handling and security.

Data security best practices are often aligned with common data frameworks, such as:

ISO/IEC 27001: The international standard for information security management systems is a framework to help organizations establish, implement, operate, monitor, review, maintain, and continually improve information security management systems.

NIST: The National Institute of Standards and Technology provides guidance on data security and privacy.

SOX: The Sarbanes-Oxley Act of 2002 requires publicly traded companies to implement internal controls over financial reporting, including data security.

Global Consumer Privacy Laws: These laws, such as GDPR (General Data Protection Regulation), PIPL (Personal Information Protection Law), and CCPA (California Consumer Privacy Act), protect individuals' personal information.

Data security solutions

Organizations can leverage various data security solutions to protect their data, including:

Data Security Platform: A comprehensive platform that provides a centralized view of data security risks and controls.

Data Loss Prevention (DLP): Solutions that prevent sensitive data from leaving the organization's control.

Data Encryption: Encrypts data both at rest and in transit to ensure that it remains secure, even if intercepted.

  • Key Management: Controls who has access to the keys needed to decrypt sensitive data.

Data Access Governance: Ensures only authorized individuals can access sensitive data, which is granted on a need-to-know basis.

Insider Risk Management: Detects and responds to potential data leaks from within the organization.

Database Security: Finds and protects sensitive information within databases from unauthorized access, while ensuring the health and security of the supported database platforms.

Data Discovery and Classification: The process of identifying, exploring, and understanding an organization's sensitive and proprietary information to categorize it based on its relevance, confidentiality, and other characteristics.

Data security best practices

  1. Identify all data that needs to be protected: Conduct thorough discovery to identify sensitive structured and unstructured data across information storage.
  2. Document compliance and regulatory requirements: Ensure data is classified and labeled according to applicable regulations while preparing for reporting and auditing processes.
  3. Limit data access: Restrict access to sensitive data to only authorized individuals.
  4. Secure data storage in all locations: Implement strong security measures, such as encryption, to protect data stored on devices, external media, and file shares.
  5. Train employees and users: Educate users about data security policies and offer coaching in real time to prevent accidental data leaks.
  6. Patch and update databases: Keep all databases updated and protected from vulnerabilities.
  7. Develop an incident response plan: Create and practice incident management processes including breach reporting.
  8. Monitor real-time events: Continuously monitor data security activities to detect suspicious behavior.

Trellix's approach to data security

Protecting the Data That Matters Most

Trellix is committed to helping organizations safeguard sensitive and proprietary information shared across endpoints, networks, email, the web, cloud storage, and within databases. Our comprehensive approach focuses on three key areas:

  • Discover: Identify and classify sensitive data across various data sources.
  • Protect: Implement robust security measures to prevent unauthorized access, use, disclosure, disruption, modification, or destruction of data.
  • Respond & Report: Detect and respond to data security incidents, investigate breaches, and provide detailed reporting and auditing capabilities to demonstrate compliance.

Trellix data security solutions

Trellix offers a comprehensive suite of data security solutions, including:

  • Trellix Data Loss Prevention (DLP): Stop intentional and accidental data loss on endpoints through email, via the web, and across networks.
    • Endpoint Complete: Protect workstations and servers from data leaks.
    • Device Control: Block unauthorized device installations. (included in Endpoint Complete)
    • Network Prevent: Stop data leaks over networks, email, and the web.
    • Network Monitor: Real-time scanning and analysis of network data.
    • Discover: Scan and classify across all network-accessible locations.
  • Trellix Data Encryption: Protect data on enterprise and removable devices from unauthorized access.
    • Drive Encryption: Pre-boot user-authenticated full disk encryption for devices.
    • Native Drive Encryption: Protect device data by centralizing BitLocker and Apple FileVault management.
    • File & Removable Media Protection: Protection for data on devices such as USBs, hard drives, in files and folders, including network files
  • Trellix Database Security: Find and protect sensitive information in databases while maintaining performance and managing access.
    • Vulnerability Manager: Find databases and the sensitive information they contain.
    • Virtual Patching: Protect databases from known and unknown vulnerabilities.
    • Database Activity Monitoring: Monitor, log, and control database access.

By leveraging Trellix Data Security solutions, organizations can effectively protect their data, comply with regulations, and mitigate risks.

Find and protect the data that matters. Explore how Trellix Data Security can help protect against insider risk in this self-guided online tour.

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