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| Section | Weight | Objectives |
|---|---|---|
| DSPM Architecture and Deployment | 20% | - Deployment planning and requirements - Architecture overview and components - Integration with cloud and on-prem environments - Installation and configuration |
| Troubleshooting and Maintenance | 10% | - Log analysis and error resolution - Backup and recovery procedures - Upgrade and patch management - System health monitoring |
| Data Discovery and Classification | 25% | - Pattern matching and classification rules - Data register and sensitive data mapping - Compliance framework alignment - Scanner and detector configuration |
| Access Governance and Risk Management | 15% | - Risk scoring and prioritization - Access review and entitlement analysis - Incident handling and remediation - Data access governance policies |
| Administration and Configuration | 20% | - User and role management - System settings and maintenance - Policy creation and enforcement - Controls orchestration |
| Monitoring, Analytics, and Reporting | 10% | - Dashboard creation and customization - Analytics and data visualization - Compliance reporting and audit logs - Alert configuration and monitoring |
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NEW QUESTION # 14
Which of the following is an option to aid the process of reviewing the incidents generated from triggered rules in Controls Orchestration?
Answer: A
Explanation:
The correct answer is B . Forcepoint DSPM Controls Orchestration rules are built around query-driven rule logic. In the rule configuration workflow, administrators select a dataset such as Files , Trustees , or Agent Activities , then configure the rule condition using GQL syntax . This GQL condition defines which records match the rule and therefore which results appear as incidents when the rule is triggered. Forcepoint documentation states that Controls Orchestration rules identify data matching specific criteria and that the Condition field uses GQL syntax to filter the selected dataset.
When reviewing incidents, Forcepoint's Incidents page provides a top-down view of orchestration rules and available match results. Selecting an incident card opens a results preview, and choosing View in the Page displays those matched files in Enterprise Search , where additional review and action options are available.
Enterprise Search is specifically designed to narrow scanned-file results using GetVisibility Query Language
, and Forcepoint notes that GQL filtering helps reduce the result set to a more manageable subset for analysis and action.
Timestamp, Risk type, and keyword filtering may be useful in other contexts, but the documented advanced review mechanism for these results is GQL-based filtering. References/topics: Controls Orchestration, Incidents, Enterprise Search, GQL Filtering, Rule Match Review .
NEW QUESTION # 15
What is the primary function of a detector in Forcepoint DSPM?
Answer: C
Explanation:
A detector in Forcepoint DSPM is a rule-based classification component used during scanning to identify files whose content or path matches defined detection logic. The correct answer is B because detectors are designed to locate specific patterns, words, or expressions and then contribute to classification/tagging outcomes. Forcepoint describes Detector Groups in AI Mesh as components where "detectors assess both the file path and its contents using rule-based logic, such as regular expressions and keywords," returning a match when the content fits the defined patterns.
This is distinct from AI classifiers, which infer sensitive-data meaning from broader semantic or machine- learning signals. Detectors are the more deterministic mechanism: they look for defined indicators such as a keyword, phrase, regular expression, or path element. Forcepoint release notes also describe detector functionality as allowing content or path search when creating a detector, including an example where adding the word Archive to a detector can tag files located in an Archive folder.
The other options confuse detectors with unrelated platform functions. Detectors do not create credential tags specifically, optimize network throughput, block files for speed, or increase storage capacity. References
/topics: Detectors, Pattern Matching, AI Mesh, Classification Tags, Content and Path Search .
NEW QUESTION # 16
When creating a Security Posture Policy in Forcepoint DSPM, which field uses a GQL query to identify the data asset?
Answer: B
Explanation:
The correct answer is C. Data Mapping . In Forcepoint DSPM, Security Posture Policies are used to define and govern critical business data assets, often referred to as crown-jewel data. Each policy represents a managed data asset associated with a department, owner, and query-based definition. The Data Mapping field is where the administrator enters or edits the GQL query that identifies which files or records belong to that data asset. Forcepoint's documentation explicitly lists Asset Name , Department , Data Owner , and Data Mapping as required Security Posture Policy details, and defines Data Mapping as "a GQL query used to identify the data asset within the DSPM database." This distinction matters because Asset Name is only the business label, Department assigns responsibility to a business unit, and Data Owner identifies the person or group accountable for monitoring and compliance.
The actual technical selection logic is contained in Data Mapping , where GQL can match data across sources such as SMB and SharePoint using query criteria like source and path. References/topics: Policy Center, Data Register, Security Posture Policies, Data Mapping, GQL, Data Asset Inventory .
NEW QUESTION # 17
Which of the following are steps in creating a data classification and handling policy? Select four.
Answer: A,B,C,E
Explanation:
The correct selections are A, C, D, and E . A data classification and handling policy is a governance artifact that defines how data assets are categorized, owned, protected, reviewed, and aligned to legal or regulatory requirements. In Forcepoint DSPM, this sits within Policy Center and Compliance Hub , which are designed to support data classification, policy creation, security-control implementation, compliance, and risk reduction. Forcepoint states that Policy Center streamlines policy creation and prompts organizational representatives to provide information needed to build a governance framework aligned to organizational goals.
Specifying asset requirements maps to Data Mapping, where organizations define Data Asset Inventory fields and metadata such as retention period, business owner, regulatory scope, review status, and project name. Incorporating industry-specific regulations is required because departmental policy design must reflect obligations such as GDPR, HIPAA, and PCI DSS. Defining classification levels aligns to Taxonomy, where sensitivity levels such as Confidential, General Business, Public, and Highly Confidential are configured. Outlining roles and responsibilities aligns to assigning policy owners, department heads, representatives, and accountable stakeholders. Network traffic protocols are not a core step in creating a data classification and handling policy; they belong to network architecture or transport-control design, not data governance policy creation.
NEW QUESTION # 18
Which of the following utilizes artificial intelligence and machine learning when data is scanned?
Answer: B
Explanation:
The correct answer is D. Detectors . In Forcepoint DSPM, detectors are scan-time classification components that can contribute to the broader AI Mesh , now represented in the UI as the Classification Model .
Forcepoint describes the Classification Model as the mechanism that combines detection signals from keyword lists, regex patterns, machine-learning models, and topic classifiers into a pipeline that assigns classification tags such as Confidential , Internal , or Public . It also identifies Detector Groups as nodes that assess file paths and file contents using rule-based logic, including regular expressions and keywords.
This makes detectors the best answer among the listed options because they operate during scanning and feed classification outcomes. Forcepoint's detector documentation states that content detectors analyze file content to detect and categorize documents, and further notes that when a detector group is selected, the detector becomes part of the AI Mesh and contributes to classification results.
The other choices are not the primary AI/ML scan-time component. Patterns are regular-expression rules.
Data mapping defines Data Asset Inventory metadata fields. Compliance Hub manages governance policy artifacts, policy acceptance, reviews, and audit trail functions. References/topics: Detectors, AI Mesh, Classification Model, Content Detectors, Scan Classification Pipeline .
NEW QUESTION # 19
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