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| Section | Objectives |
|---|---|
| Topic 1: Detector Configuration | - Keyword Detectors - Regular Expression Detectors - Detector Testing and Validation - Path Detectors |
| Topic 2: Pattern Matching and Classification | - Custom Pattern Creation - Sensitive Data Identification - Regular Expressions - Classification Policies |
| Topic 3: Controls Orchestration | - Rule Creation and Management - Risk Classification - Incident Investigation - Webhook Configuration |
| Topic 4: Analytics and Dashboards | - Dashboard Customization - Risk Analysis and Reporting - Enterprise Search - Analytic Dashboards |
| Topic 5: Preparing and Deploying Forcepoint DSPM | - DSPM Deployment Architecture - User Management Configuration - Data Source Configuration - Lab Environment Preparation |
| Topic 6: Data Discovery and Scanning | - SMB Data Sources - Scan Configuration - LDAP Integration - Data Visibility and Monitoring |
| Topic 7: Compliance Hub and Data Register | - Departments Configuration - Security Posture Policies - Data Asset Inventory - Metadata Management |
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NEW QUESTION # 42
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 # 43
Which of the following are actions that can be performed from the Enterprise Search page? Select three.
Answer: B,C,E
Explanation:
The correct selections are Revoking user permissions , Exporting reports , and Manually verifying ML classification . The Enterprise Search page is the primary file-level investigation view in Forcepoint DSPM.
It lists scanned and cataloged files, allows filtering through standard filters or GQL, and provides operational actions against the returned results. Forcepoint states that Enterprise Search allows users to filter file data, save frequently used filters, customize columns, and generate meaningful reports. It also provides an EXPORT button that creates a CSV or JSON download of the filtered data.
Revoking permissions is also supported as a data-governance action. Forcepoint documents that administrators can view or modify file permissions and access rights from the file Actions menu, and supporting documentation identifies required permissions for revoke operations in Microsoft repositories.
Manual classification validation is explicitly available from the Enterprise Search hamburger menu.
Forcepoint states that to adjust a file's machine-learning classification, the user selects Manually verify classification , modifies the ML-suggested classification, and saves the change.
The incorrect choices are outside this specific Enterprise Search action set. Moving risky files to a private folder is not the standard named Enterprise Search action in this workflow, and assigned risk is not manually changed from the page. References/topics: Enterprise Search, Exporting Data, Permissions & Access Rights, Manual ML Classification Verification .
NEW QUESTION # 44
Which of the following describes a use case for Forcepoint DSPM pattern matching?
Answer: B
Explanation:
Forcepoint DSPM pattern matching is used to identify defined pieces of information inside scanned content by applying regular expressions. The documented function is discovery and classification: pattern matching identifies particular information in a document by using RegEx that attempts to match file content. This makes identifying personally identifiable information on SharePoint the correct use case. SharePoint is a supported Microsoft data source for scanning, and Forcepoint specifically documents SharePoint Online as a connector used to scan SharePoint accounts and apply classification tags to files containing sensitive data stored in SharePoint.
The key distinction is that pattern matching does not perform remediation actions such as redaction or encryption. Options B and D therefore overstate the capability: Forcepoint DSPM may discover and classify sensitive data that later informs controls, but the pattern itself is not a redaction or encryption engine. Option A is less precise in this context because the question is testing the canonical pattern-matching use case against scanned documents and repositories, while the strongest documented repository example among the choices is SharePoint. Pattern configuration can also assign classification, compliance, and distribution tags when a RegEx is detected, such as GDPR/PII tagging for identifiers. References/topics: Pattern Matching, RegEx, Compliance Tags, SharePoint Scanning, Sensitive Data Classification .
NEW QUESTION # 45
Match the type of detector with its primary function.
Answer:
Explanation:
Explanation:
Path Detectors = Monitor storage locations of sensitive data
Content Detectors = Analyze data within files for sensitive data
Attribute Detectors = Identify meta-data within documents
Forcepoint DSPM separates detector logic into path, content, and attribute-based functions so classification can be driven by where data is stored, what the file contains, and what scan-derived attributes describe the file. Path Detectors evaluate file path information, including directory location, filename, and extension.
Forcepoint describes them as identifying and classifying files based on directory location and file extensions, which aligns with monitoring storage locations where sensitive data resides.
Content Detectors inspect the actual contents of files. Forcepoint states that content detectors analyze file content and categorize based on keywords, phrases, positive and negative terms, or patterns, making them the correct match for analyzing data within files for sensitive data.
Attribute Detectors operate on scan-result attributes rather than raw text content alone. Forcepoint describes them as defining criteria for "critical" and "sensitive" based on attributes in scan results, including ML output or path/content detector hits. This maps most closely to identifying metadata or scan-derived characteristics within documents. References/topics: Detectors, Path Detectors, Content Detectors, Attribute Detectors, AI Mesh, Classification Model .
NEW QUESTION # 46
Which of the following is a key benefit of defining a custom data taxonomy?
Answer: C
Explanation:
The correct answer is D. Enhances data security . In Forcepoint DSPM, taxonomy is the structured classification model used to assign sensitivity meaning to discovered data. Forcepoint describes taxonomy as a machine-learning-based structured classification system that assigns sensitivity levels such as Confidential , General Business , Public , and Highly-Confidential . This classification directly corresponds to the Classification column in scan results, allowing security and governance teams to understand how sensitive a file or data asset is after scanning.
A custom taxonomy improves security because it lets an organisation align DSPM classification labels with its own internal data-handling rules, security protocols, and business language. Forcepoint notes that taxonomy customization ensures data handling aligns with an organisation's security protocols, and that applied tags are visible in the Data Asset Inventory . In the administration taxonomy workflow, Forcepoint also explains that predefined AI Mesh tags can be supplemented with custom tags for pattern matching and detection rules, and those tags can be mapped to data-source taxonomies for label writeback.
The other options describe possible operational goals but not the primary purpose of taxonomy. Taxonomy is not an authentication mechanism, deduplication feature, or storage-reduction tool. References/topics:
Taxonomy, Classification Tags, AI Mesh, Pattern Matching, Data Asset Inventory, Compliance Hub .
NEW QUESTION # 47
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