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Baselining

Data Protection

Definition

Establishing normal network/application behavior metrics to detect anomalies through continuous monitoring.

Technical Details

Baselining is a process in cybersecurity that involves the collection and analysis of data over time to establish a set of normal behavior metrics for network traffic, application performance, or user activity. This data is used to create a baseline that reflects typical patterns of operation. Advanced analytical techniques, such as machine learning and statistical analysis, can be employed to identify anomalies or deviations from this established norm. Continuous monitoring systems leverage these baselines to trigger alerts when unusual behavior is detected, indicating potential security incidents such as intrusions, malware infections, or unauthorized access.

Practical Usage

In practice, baselining is utilized in various cybersecurity applications, including intrusion detection systems (IDS), network performance monitoring, and user activity monitoring. Organizations implement baselining by collecting extensive logs and metrics from their systems over a defined period, which allows them to fine-tune their security parameters and response strategies. For example, a company might use a baseline of typical network traffic patterns to identify unusual spikes that could indicate a Distributed Denial of Service (DDoS) attack or data exfiltration attempts. Regular updates to the baseline ensure that evolving behaviors and patterns are accurately reflected.

Examples

Related Terms

Anomaly Detection Intrusion Detection System (IDS) Security Information and Event Management (SIEM) User Behavior Analytics (UBA) Threat Hunting
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