312-40 Exam Dumps : EC-Council Certified Cloud Security Engineer (CCSE)

To handle the collection, transformation, and loading of user behavior data into Amazon S3, AWS Kinesis Data Firehose is the suitable service. Here’s how it works:

Data Collection: Kinesis Data Firehose collects streaming data in real-time from various sources, including web applications that track user interactions.

Data Transformation: It can transform incoming streaming data using AWS Lambda, which can include converting data into zip files if necessary1.

Loading to Amazon S3: After transformation, Kinesis Data Firehose automatically loads the data into Amazon S3, handling massive volumes efficiently and reliably1.

Real-time Processing: The service allows for the real-time processing of data, which is essential for capturing dynamic user behavior data.

References:AWS Kinesis Data Firehose is designed to capture, transform, and load streaming data into AWS data stores for near real-time analytics with existing business intelligence tools and dashboards1. It’s a fully managed service that scales automatically to match the throughput of your data and requires no ongoing administration. It can also batch, compress, and encrypt the data before loading, reducing the amount of storage used at the destination and increasing security1.

When dealing with a security incident in an AWS environment, it’s crucial to handle forensic evidence in a way that complies with data privacy laws. The initial step to avoid legal implications when moving data between AWS regions for analysis is to create an evidence volume from the snapshot of the compromised EC2 instances.

Snapshot Creation: Take a snapshot of the compromised EC2 instance’s EBS volume. This snapshot captures the state of the volume at a point in time and serves as forensic evidence.

Evidence Volume Creation: Create a new EBS volume from the snapshot within the same AWS region to avoid cross-regional data transfer issues.

Forensic Workstation Provisioning: Provision a forensic workstation within the same region where the evidence volume is located.

Evidence Volume Attachment: Attach the newly created evidence volume to the forensic workstation for analysis.

References:Creating an evidence volume from a snapshot is a recommended practice in AWS forensics. It ensures that the integrity of the data is maintained and that the evidence is handled in compliance with legal requirements12. This approach allows for the preservation, acquisition, and analysis of data without violating data privacy laws that may apply when transferring data across regions12.

Security Command Center: Google Cloud’s Security Command Center is designed to provide centralized visibility into the security state of cloud resources1.

Native Scanners: It includes native scanners that assess the security state of virtual machines, containers, networks, and storage, along with identity and access management policies1.

Security Health Analytics: Security Health Analytics is a native scanner within the Security Command Center. It automatically scans your Google Cloud resources to help identify misconfigurations and compliance issues with Google security best practices2.

Functionality: Security Health Analytics can detect various misconfigurations and vulnerabilities, such as open storage buckets, instances without SSL/TLS, and resources without an enabled Web UI, which aligns with Tara Reid’s requirements2.

Exclusion of Other Options: The other options listed do not serve as native scanners within the Security Command Center for the purposes described in the question1.

References:

Google Cloud’s documentation on Security Command Center1.

Medium article on Google Cloud’s free vulnerability scanning with Security Command Center2.