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NEW QUESTION: 1
ネットワーク管理者から連絡があります。彼は、ARPスプーフィングまたはポイズニングが自分のネットワークで発生する可能性があることを懸念しています。
それを防ぐために彼ができることは何ですか？ベストアンサーを選択してください。
A. ARPwatchなどのツールを使用して、奇妙なARPアクティビティを監視します。
B. すべてのLANセグメント間でファイアウォールを使用します。
C. 彼のスイッチでポートセキュリティを使用します。
D. すべてのPCで静的IPアドレスのみを使用します。
E. 小規模なネットワークの場合は、静的ARPエントリを使用します。
Answer: A,C,E
NEW QUESTION: 2
Sie haben eine Microsoft Azure SQL-Datenbank.
Die Ausführung einiger Abfragen dauert sehr lange.
Sie müssen feststellen, ob eine der langfristigen Anfragen Benutzer daran hindert, Daten in der Datenbank zu aktualisieren.
Welche Abfrage solltest du ausführen? Wählen Sie zum Beantworten die entsprechenden Optionen im Antwortbereich aus.
HINWEIS: Jede richtige Auswahl ist einen Punkt wert.
Answer:
Explanation:
Explanation
Box 1: sys.dm_tran_locks
sys.dm_tran_locks returns information about currently active lock manager resources in SQL Server 2017.
Each row represents a currently active request to the lock manager for a lock that has been granted or is waiting to be granted.
Box 2: sys.dm_os_waiting_tasks
sys.dm_tran_locks.lock_owner_address is the memory address of the internal data structure that is used to track this request. This column can be joined the with resource_address column in sys.dm_os_waiting_tasks.
References:
https://docs.microsoft.com/en-us/sql/relational-databases/system-dynamic-management-views/sys-dm-tran-locks
NEW QUESTION: 3
In the context of Biometric authentication, what is a quick way to compare the accuracy of devices. In general, the device that have the lowest value would be the most accurate.
Which of the following would be used to compare accuracy of devices?
A. The FER is used
B. the CER is used.
C. the FRR is used
D. the FAR is used
Answer: B
Explanation:
equal error rate or crossover error rate (EER or CER): the rate at which both accept and reject errors are equal. The value of the EER can be easily obtained from the
ROC curve. The EER is a quick way to compare the accuracy of devices with different
ROC curves. In general, the device with the lowest EER is most accurate.
In the context of Biometric Authentication almost all types of detection permit a system's sensitivity to be increased or decreased during an inspection process. If the system's sensitivity is increased, such as in an airport metal detector, the system becomes increasingly selective and has a higher False Reject Rate (FRR).
Conversely, if the sensitivity is decreased, the False Acceptance Rate (FAR) will increase.
Thus, to have a valid measure of the system performance, the CrossOver Error Rate
(CER) is used.
The following are used as performance metrics for biometric systems:
false accept rate or false match rate (FAR or FMR): the probability that the system incorrectly matches the input pattern to a non-matching template in the database. It measures the percent of invalid inputs which are incorrectly accepted. In case of similarity scale, if the person is imposter in real, but the matching score is higher than the threshold, then he is treated as genuine that increase the FAR and hence performance also depends upon the selection of threshold value.
false reject rate or false non-match rate (FRR or FNMR): the probability that the system fails to detect a match between the input pattern and a matching template in the database.
It measures the percent of valid inputs which are incorrectly rejected.
failure to enroll rate (FTE or FER): the rate at which attempts to create a template from an input is unsuccessful. This is most commonly caused by low quality inputs.
failure to capture rate (FTC): Within automatic systems, the probability that the system fails to detect a biometric input when presented correctly.
template capacity: the maximum number of sets of data which can be stored in the system.
Reference(s) used for this question:
KRUTZ, Ronald L. & VINES, Russel D., The CISSP Prep Guide: Mastering the Ten
Domains of Computer Security, 2001, John Wiley & Sons, Page 37
and
Wikipedia at: https://en.wikipedia.org/wiki/Biometrics