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NEW QUESTION: 1
An organizations ability to prevent a security incident In a Software as a Service (SaaS) cloud-com puling environment is MOST dependent on the:
A. configuration and sensitivity of an intrusion detection system (IDS)
B. granularity with which access rights can be configured
C. ability to monitor and analyze system logs
D. ability to implement a web application firewall.
Answer: B
NEW QUESTION: 2
A. Option D
B. Option B
C. Option A
D. Option C
Answer: A
Explanation:
Explanation
Explanation:
t4 q11-1
t4 q11-2
Reference: http://technet.microsoft.com/library/gg610569.aspx
NEW QUESTION: 3
A medical record filing system for a government medical fund is using an Amazon S3 bucket to archive documents related to patients. Every patient visit to a physician creates a new file, which can add up millions of files each month. Collection of these files from each physician is handled via a batch process that runs ever night using AWS Data Pipeline. This is sensitive data, so the data and any associated metadata must be encrypted at rest.
Auditors review some files on a quarterly basis to see whether the records are maintained according to regulations. Auditors must be able to locate any physical file in the S3 bucket for a given date, patient, or physician. Auditors spend a significant amount of time location such files.
What is the most cost- and time-efficient collection methodology in this situation?
A. Use Amazon S3 event notification to populate an Amazon Redshift table with metadata about every file loaded to Amazon S3, and partition them based on the month and year of the file.
B. Use Amazon S3 event notification to populate an Amazon DynamoDB table with metadata about every file loaded to Amazon S3, and partition them based on the month and year of the file.
C. Use Amazon Kinesis to get the data feeds directly from physicians, batch them using a Spark application on Amazon Elastic MapReduce (EMR), and then store them in Amazon S3 with folders separated per physician.
D. Use Amazon API Gateway to get the data feeds directly from physicians, batch them using a Spark application on Amazon Elastic MapReduce (EMR), and then store them in Amazon S3 with folders separated per physician.
Answer: C