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NEW QUESTION: 1
Your company has a Microsoft Azure Active Directory (Azure AD) tenant.
The company uses Microsoft Intune to manage iOS, Android, and Windows 10 devices.
The company plans to purchase 1,000 iOS devices. Each device will be assigned to a specific user.
You need to ensure that the new iOS devices are enrolled automatically in Intune when the assigned user signs in for the first time.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:
Explanation:

Reference:
https://docs.microsoft.com/en-us/intune/device-enrollment-program-enroll-ios

NEW QUESTION: 2
Which FirePOWER preprocessor engine is used to prevent SYN attacks?
A. IP Defragmentation
B. Portscan Detection
C. Inline Normalization
D. Rate-Based Prevention
Answer: D

NEW QUESTION: 3
Machine Learning Specialist는 전 세계 기업의 보안 이벤트를 실시간으로 관리하는 대규모 사이버 보안 회사와 협력하고 있습니다. 사이버 보안 회사는 머신 러닝을 사용하여 데이터가 수집되는 동안 악성 이벤트를 이상 징후로 평가할 수있는 솔루션을 설계하려고 합니다. 이 회사는 또한 나중에 처리하고 분석하기 위해 데이터 레이크에 결과를 저장할 수 있기를 원합니다.
이러한 작업을 수행하는 가장 효율적인 방법은 무엇입니까?
A. 데이터를 수집하고 Amazon S3에 저장합니다. AWS Batch를 AWS Deep Learning AMI와 함께 사용하여 Amazon S3의 데이터에서 TensorFlow를 사용하여 k- 평균 모델을 교육하십시오.
B. Amazon Kinesis Data Firehose를 사용하여 데이터를 수집하고 이상 감지를 위해 Amazon Kinesis Data Analytics Random Cut Forest (RCF)를 사용합니다. 그런 다음 Kinesis Data Firehose를 사용하여 결과를 Amazon S3로 스트리밍 합니다.
C. Amazon EMR을 사용하여 Apache Spark Streaming으로 데이터를 수집하고 k- 수단과 함께 Spark MLlib를 사용하여 이상 감지를 수행합니다. 그런 다음 복제 계수가 3 인 Amazon EMR을 데이터 레이크로 사용하여 Apache Hadoop 분산 파일 시스템 (HDFS)에 결과를 저장합니다.
D. 데이터를 수집하고 Amazon S3에 저장합니다. 요청시 트리거되는 AWS Glue 작업이 새 데이터를 변환하도록 합니다. 그런 다음 Amazon SageMaker 내에 내장 된 RCF (Random Cut Forest) 모델을 사용하여 데이터의 이상을 감지합니다.
Answer: B
Explanation:
https://aws.amazon.com/tw/blogs/machine-learning/use-the-built-in-amazon-sagemaker-random- cut-forest-algorithm-for-anomaly-detection/