IBM C1000-162 Exam With Confidence Using Practice Dumps

Behavioral rule test parameters in QRadar SIEM are crucial for configuring how anomaly detection functions within rules. Here's a breakdown of each parameter:

Season: This is the most important parameter. It defines the historical time period used to establish a baseline of "normal" behavior. Consider the nature of the traffic you're monitoring when choosing a season:

Network traffic with human interaction: A season of 1 week might be appropriate.

Daily patterns: A season of 24 hours would be more suitable.

Current traffic level: Represents the current value of the property being monitored by the rule (e.g., number of login failures, bandwidth usage, etc.).

Predicted value: This is an estimation of what the traffic level "should" be, based on the established season and historical trends.

How the Parameters Work Together

Behavioral rules primarily identify deviations between the Current traffic level and the Predicted value within the context of the defined Season. Significant discrepancies can trigger alerts.

References

IBM Security QRadar Documentation - Anomaly Detection Rules: ( ). Search for "behavioral rule test parameter options" within the relevant documentation for QRadar SIEM V7.5.

Challenges in Search Performance: When dealing with large volumes of data in QRadar, searches can become slow if the data is not indexed properly. To improve search performance, specific property types can be utilized.

Property Types Overview:

Tabled Properties: Refer to data stored in tabular format but do not inherently improve search performance.

Indexed Properties: Properties that have an index created for them, significantly speeding up search operations by allowing quick lookups.

Stored Properties: Simply refers to properties that are stored but not necessarily indexed.

Common Properties: General properties used across various rules and searches but do not improve search performance specifically.

Importance of Indexed Properties: Indexed properties are specifically designed to enhance search performance by creating an index that allows QRadar to quickly locate the data without scanning the entire dataset.

Reference Confirmation: According to IBM QRadar documentation, using indexed properties is the recommended approach to reduce data volume searched and to shorten search times, making them the best choice for improving search performance.

References:

IBM QRadar documentation on optimizing search performance highlights the use of indexed properties to enhance search efficiency.

Custom Properties: QRadar allows you to extract custom properties from raw log and flow data, enriching your analysis capabilities.

Supported Expression Types:

Regex (Regular Expressions): Powerful patterns for extracting specific strings or values from textual data.

JSON (JavaScript Object Notation): Extracts values from structured JSON data within events and flows.

Unsupported Types:

XLS: Excel spreadsheet format. QRadar isn't designed to parse spreadsheets directly.

YAML: A data serialization language. QRadar's extraction is more focused on data within events and flows rather than standalone configuration files.

HTML: Markup language used for web pages. Event data is unlikely to be solely in HTML format.

References:

IBM QRadar Documentation - Custom Property Expression Types: