Security Data Lake
Definition of a Security Data Lake
A security data lake is a centralized repository that stores, processes, and secures large amounts of security-related data in its original format. Unlike traditional databases, a security data lake can store any type of data — structured, semi-structured, or unstructured — from any source without sacrificing fidelity.
This comprehensive data collection enables organizations to leverage AI-driven analytics for intelligent threat detection, investigation, and response while meeting compliance mandates.
Traditional Databases vs Security Data Lakes
Data Lakes are Critical to Cybersecurity
A security data lake centralizes and stores unlimited amounts of an organization's security data in its native format. This approach enables organizations to affordably process vast amounts of data for threat detection, investigation, and response. By combining high-speed search capabilities with long-term storage, security data lakes support everything from rapid threat hunting to advanced analytics and cross-organizational collaboration.
- Intelligent analytics: Enables the use of AI and ML by creating a baseline across data sources to surface anomalies and trends
- Flexible at scale: Easily handles a large amount of data from disparate sources without storage limitations that can adjust based on changing organizational demands
- Enhanced threat detection and investigation: Quickly analyzes large datasets with advanced analytics to detect and identify known and unknown threats that may not be apparent in disparate systems
- Faster incident response: Searches retrospective data at scale to quickly surface contextual insights for pinpointing root causes and taking immediate action
- Data sharing: Enables collaboration with professionals outside the security operations center to improve security posture across the entire organization
- Cost-effective long-term storage: Stores large amounts of security data long-term at a lower cost than traditional solutions to streamline threat hunting and forensic analysis
Key Components of a Security Data Lake
- Data encryption: Preventing unauthorized access by converting data into code using a specific algorithm and key. If an unauthorized user gains access to encrypted data but does not have a key, the user will be unable to read it.
- Access controls and data governance: Restricts data access based on roles. Authentication ensures the person is who they claim to be while authorization determines if the person has the right permissions to access the data.
- Data masking: Replaces sensitive data with fictitious yet realistic values so organizations can use and share it without compromising security.
- Auditing: Ensures data security and integrity by tracking the type of data, the users who can access it, and any changes made to the data.
Anomali’s Security Data Lake
Anomali’s AI-Powered Security and IT Operations Platform is built on a Security Data Lake that dynamically combines high-volume data collection and storage to drive AI-Powered advanced analytics for intelligent threat detection, investigation, and response. This allows security teams to aggregate and store up more than seven years of data to gain retrospective insights in seconds and to achieve compliance goals, at a fraction of the cost of traditional solutions.
