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Google Professional-Cloud-Security-Engineer Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Supporting Compliance Requirements	11%	- Audit and assessment 1. Security assessment frameworks 2. Evidence collection and reporting - Regulatory compliance 1. Controls for GDPR, HIPAA, PCI DSS, ISO 27001 2. Shared responsibility model
Topic 2: Managing Operations	19%	- Security automation and governance 1. Binary Authorization and supply chain security 2. Infrastructure as Code security 3. Policy enforcement and compliance monitoring - Security monitoring and logging 1. Cloud Audit Logs and logging configuration 2. Threat detection and response 3. Security Command Center (SCC)
Topic 3: Ensuring Data Protection	23%	- Encryption implementation 1. Encryption at rest (CMEK, Google-managed keys) 2. Key management and rotation 3. Data loss prevention (DLP) - Data classification and lifecycle 1. Sensitive data discovery and classification 2. Retention and deletion policies
Topic 4: Configuring Access	25%	- Implementing access management 1. User and group management 2. Service accounts and key management 3. Deny policies and conditional access - Designing access control 1. IAM roles, permissions, and policies 2. Identity federation and workload identity 3. Resource hierarchy and organization policies
Topic 5: Configuring Network Security	20%	- Perimeter security 1. Cloud NGFW rules and policies 2. Identity-Aware Proxy (IAP) 3. VPC design and private access - Secure communication 1. Load balancer security 2. Encryption in transit 3. Certificate management

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Google Cloud Certified - Professional Cloud Security Engineer Exam Professional-Cloud-Security-Engineer Prüfungsfragen mit Lösungen (Q258-Q263):

258. Frage
An employer wants to track how bonus compensations have changed over time to identify employee outliers and correct earning disparities. This task must be performed without exposing the sensitive compensation data for any individual and must be reversible to identify the outlier.
Which Cloud Data Loss Prevention API technique should you use to accomplish this?

A. Redaction
B. CryptoHashConfig
C. Generalization
D. CryptoReplaceFfxFpeConfig

Antwort: D

Begründung:
De-identifying sensitive data
Cloud Data Loss Prevention (DLP) can de-identify sensitive data in text content, including text stored in container structures such as tables. De-identification is the process of removing identifying information from data. The API detects sensitive data such as personally identifiable information (PII), and then uses a de-identification transformation to mask, delete, or otherwise obscure the data. For example, de-identification techniques can include any of the following:
Masking sensitive data by partially or fully replacing characters with a symbol, such as an asterisk (*) or hash (#).
Replacing each instance of sensitive data with a token, or surrogate, string.
Encrypting and replacing sensitive data using a randomly generated or pre-determined key.
When you de-identify data using the CryptoReplaceFfxFpeConfig or CryptoDeterministicConfig infoType transformations, you can re-identify that data, as long as you have the CryptoKey used to originally de-identify the data.
https://cloud.google.com/dlp/docs/deidentify-sensitive-data

259. Frage
You discovered that sensitive personally identifiable information (PII) is being ingested to your Google Cloud environment in the daily ETL process from an on-premises environment to your BigQuery datasets. You need to redact this data to obfuscate the PII, but need to re-identify it for data analytics purposes. Which components should you use in your solution? (Choose two.)

A. Secret Manager
B. Cloud Data Loss Prevention with cryptographic hashing
C. Cloud Data Loss Prevention with automatic text redaction
D. Cloud Key Management Service
E. Cloud Data Loss Prevention with deterministic encryption using AES-SIV

Antwort: D,E

Begründung:
Explanation
B: you need KMS to store the CryptoKey
https://cloud.google.com/dlp/docs/reference/rest/v2/projects.deidentifyTemplates#crypt E: for the de-identity you need to use CryptoReplaceFfxFpeConfig or CryptoDeterministicConfig
https://cloud.google.com/dlp/docs/reference/rest/v2/projects.deidentifyTemplates#cryptodeterministicconfig
https://cloud.google.com/dlp/docs/deidentify-sensitive-data

260. Frage
A customer implements Cloud Identity-Aware Proxy for their ERP system hosted on Compute Engine. Their security team wants to add a security layer so that the ERP systems only accept traffic from Cloud Identity- Aware Proxy.
What should the customer do to meet these requirements?

A. Make sure that the ERP system can validate the identity headers in the HTTP requests.
B. Make sure that the ERP system can validate the JWT assertion in the HTTP requests.
C. Make sure that the ERP system can validate the x-forwarded-for headers in the HTTP requests.
D. Make sure that the ERP system can validate the user's unique identifier headers in the HTTP requests.

Antwort: B

Begründung:
Explanation
Use Cryptographic Verification If there is a risk of IAP being turned off or bypassed, your app can check to make sure the identity information it receives is valid. This uses a third web request header added by IAP, called X-Goog-IAP-JWT-Assertion. The value of the header is a cryptographically signed object that also contains the user identity data. Your application can verify the digital signature and use the data provided in this object to be certain that it was provided by IAP without alteration.

261. Frage
Last week, a company deployed a new App Engine application that writes logs to BigQuery. No other workloads are running in the project. You need to validate that all data written to BigQuery was done using the App Engine Default Service Account.
What should you do?

A. 1. Go to the IAM section on the project.
2. Validate that the App Engine Default Service Account is the only account that has a role that can write to BigQuery.
B. 1. In BigQuery, select the related dataset.
2. Make sure the App Engine Default Service Account is the only account that can write to the dataset.
C. 1. Use StackDriver Logging and filter on BigQuery Insert Jobs.
2. Click on the email address in line with the App Engine Default Service Account in the authentication field.
3. Click Hide Matching Entries.
4. Make sure the resulting list is empty.
D. 1. Use StackDriver Logging and filter on BigQuery Insert Jobs.
2. Click on the email address in line with the App Engine Default Service Account in the authentication field.
3. Click Show Matching Entries.
4. Make sure the resulting list is empty.

Antwort: C

Begründung:
To validate that all data written to BigQuery was done using the App Engine Default Service Account, you can use StackDriver Logging (now known as Cloud Logging) to filter and inspect the logs for BigQuery insert jobs. By hiding the entries matching the App Engine Default Service Account, you can ensure that no other service account has written to BigQuery if the resulting list is empty.
Steps:
Open Cloud Logging: Navigate to Cloud Logging in the Google Cloud Console.
Filter Logs: Apply a filter to display logs for BigQuery insert jobs.
Inspect Entries: Click on the email address that corresponds to the App Engine Default Service Account in the authentication field.
Hide Matching Entries: Select the option to hide matching entries.
Validate: Check if the resulting list is empty, confirming that no other service account has performed write operations to BigQuery.
Reference:
Google Cloud Logging
Monitoring BigQuery logs

262. Frage
You are a Cloud Identity administrator for your organization. In your Google Cloud environment groups are used to manage user permissions. Each application team has a dedicated group Your team is responsible for creating these groups and the application teams can manage the team members on their own through the Google Cloud console. You must ensure that the application teams can only add users from within your organization to their groups.
What should you do?

A. Export the Cloud Identity logs to BigQuery Configure an alert for external members added to groups Have the alert trigger a Cloud Function instance that removes the external members from the group.
B. Change the configuration of the relevant groups in the Google Workspace Admin console to prevent external users from being added to the group.
C. Set an Identity and Access Management (1AM) policy that includes a condition that restricts group membership to user principals that belong to your organization.
D. Define an Identity and Access Management (IAM) deny policy that denies the assignment of principals that are outside your organization to the groups in scope.

Antwort: B

Begründung:
To ensure that application teams can only add users from within your organization to their groups, you need to configure the group settings in the Google Workspace Admin console. Here are the steps:
* Access Google Workspace Admin Console:
* Go to the Google Workspace Admin console.
* Navigate to the Groups section.
* Configure Group Settings:
* Select the relevant groups used by the application teams.
* Go to the group settings and set the group to only allow members from your domain.
* This prevents external users from being added to these groups.
* Apply and Save Changes:
* Apply the changes to ensure that only users from within your organization can be added to these groups.
* Verify Configuration:
* Test the configuration by attempting to add an external user to the group and verifying that it is not allowed.
Benefits:
* Security: Prevents unauthorized access by ensuring that only internal users can be added to groups.
* Compliance: Helps in adhering to organizational policies regarding user access and management.
References
* Google Workspace Admin Help: Groups

263. Frage
......

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