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NEW QUESTION: 1
Sie haben 200 Computer, auf denen Windows 10 ausgeführt wird. Die Computer sind mit Microsoft Azure Active Directory (Azure AD) verbunden und bei Microsoft Intune registriert.
Sie müssen ein Intune-Gerätekonfigurationsprofil konfigurieren, um die folgenden Anforderungen zu erfüllen:
* Verhindern Sie, dass Microsoft Office-Anwendungen untergeordnete Prozesse starten.
* Benutzer daran hindern, Dateien über FTP zu übertragen.
Welche zwei Einstellungen sollten Sie im Endpoint Protection konfigurieren? Um zu antworten, wählen Sie die entsprechenden Einstellungen im Antwortbereich.
HINWEIS: Jede richtige Auswahl ist einen Punkt wert.

Verweise:
https://docs.microsoft.com/en-us/intune/endpoint-protection-windows-10
Answer:
Explanation:

NEW QUESTION: 2
ヘルスケアサービスプロバイダーは、Xシリーズクラスターを実装しています。現在、約200人の顧客がおり、年間30％の成長を遂げています。 200TBのストレージが使用されています。医療保険の相互運用性と説明責任に関する法律（HIPAA）の規制では、すべての患者データを7年間保持することが義務付けられています。彼らは、75％の使用率を超えないように、すべてのゲノムシーケンスデータをN +3保護で保存したいと考えています。
推奨する最小の初期構成は何ですか？
A. 6つのX400ノード。 4TBドライブ
B. 13個のX400ノード。 1TBドライブ
C. 7つのX400ノード。 1TBドライブ
D. 13X200ノード; 3TBドライブ
Answer: B

NEW QUESTION: 3
A security team at an e-commerce company wants to define an automatic incident response process for fraudulent credit card usage attempts. The team targets a 10-minute or faster response time for such incidents. The fraudulent card list is updated every 60 seconds. The e- commerce servers log the transaction details in near-real time. Which option should you recommend to the security team?
A. Use AutoML to automatically build models based on the fraudulent credit card lists.
B. Define a log-based metric for each fraudulent credit card, and set a Stackdriver alert for these metrics.
C. Create a new logging export with a filter to match the transaction and a sink pointing to a Cloud Pub/Sub topic.
D. Maintain a log ingestion exclusion filter based on the fraudulent credit card lists.
Answer: C
Explanation:
A is not correct because creating a metric for every credit card will not scale well.
B is not correct because it will exclude the transactions that are relevant to the security team.
C is not correct because while we could use AutoML to build models, this solution is incomplete without deploying and running the model, as well as wiring them up with some consumer service.
D is correct because this will capture the important events and pass them to Pub/Sub which in turn can send the message to a consumer service like a chat notification webhook.
https://cloud.google.com/logging/docs/export/configure_export_v2