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.
While often used interchangeably, these terms have distinct meanings related to safeguarding data:
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.
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:
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.
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 security measures must be tailored to the different states of data:
Data security measures must also consider the different types of data:
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.
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.
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.
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.
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.
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.
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:
Trellix offers a comprehensive suite of data security solutions, including:
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.