Amazon Web Services (AWS) Certified Cloud Practitioner Exam: Which AWS Service for ML-Driven Security Solution?
Question
A financial company with many resources running on AWS would like a machine learning-driven and proactive security solution that would promptly identify security vulnerabilities, particularly flagging suspicious or abnormal data patterns or activity between AWS services.
Which AWS service would best meet this requirement?
Answers
Explanations
Click on the arrows to vote for the correct answer
A. B. C. D.Correct Answer: A.
AWS Detective is a persistent machine learning-driven service that automatically collates log data from all AWS resources.
This log data is then applied into machine learning algorithms to derive data patterns between AWS services and resources, graph theory and statistical analysis.
This information allows the user to proactively visualize their AWS environment from a security standpoint, thereby allowing them to quickly and efficiently conduct security investigations when they occur.
https://docs.aws.amazon.com/detective/latest/adminguide/what-is-detective.htmlOption B is INCORRECT because AWS Macie primarily matches and discovers sensitive data such as personally identifiable information (PII) but does not have the capability to keep track of data behaviors between AWS services to detect anomalies.
Therefore the service does not meet the requirement.
Option C is INCORRECT because AWS Shield is a Distributed Denial of Service (DDoS) protection service that applies to applications running in the AWS environment.
The service does not have machine learning capability to keep track of data behaviors between AWS services.
Option D is INCORRECT because Amazon CloudWatch Anomaly Detection is a machine learning feature limited to Amazon CloudWatch metrics.
It does not extend to all the AWS services, so it does not meet the requirement.
The financial company in this scenario requires a proactive security solution that can identify security vulnerabilities and flag suspicious or abnormal data patterns or activity between AWS services. Among the four options provided, the AWS service that best meets this requirement is AWS Macie.
AWS Detective is a security service that automatically analyzes and investigates security issues across AWS services. It uses machine learning and statistical analysis to identify and visualize security issues, such as network traffic anomalies and potential data breaches. However, it does not specifically focus on identifying abnormal data patterns or activity between AWS services.
AWS Shield is a managed DDoS (Distributed Denial of Service) protection service that safeguards web applications running on AWS against DDoS attacks. It does not address the specific requirements of the financial company in this scenario.
Amazon CloudWatch Anomaly Detection is a machine learning-powered service that detects anomalies in metrics and logs across AWS resources. It automatically identifies unexpected patterns in data and alerts users to potential issues. However, it is not specifically designed to identify abnormal data patterns or activity between AWS services.
AWS Macie, on the other hand, is a fully-managed data security and privacy service that uses machine learning and pattern matching to discover and classify sensitive data stored within AWS. It can also identify suspicious or abnormal data access activity, such as attempts to access sensitive data from an unusual location or at an unusual time. Additionally, it can help the financial company comply with data privacy regulations, such as GDPR and HIPAA, by automatically identifying sensitive data that requires additional security measures.
In summary, AWS Macie is the best option for the financial company's specific requirements as it provides a machine learning-driven and proactive security solution that can identify security vulnerabilities, flag suspicious or abnormal data patterns, and ensure compliance with data privacy regulations.
