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NEW QUESTION: 1
A security administrator at a company which implements key escrow and symmetric encryption only, needs to decrypt an employee's file. The employee refuses to provide the decryption key to the file. Which of the following can the administrator do to decrypt the file?
A. Use the employee's private key
B. Use the recovery agent
C. Use the CA private key
D. Retrieve the encryption key
Answer: D
Explanation:
Explanation/Reference:
Explanation:
Key escrow addresses the possibility that a third party may need to access keys. Under the conditions of key escrow, the keys needed to encrypt/decrypt data are held in an escrow account and made available if that third party requests them. The third party in question is generally the government, but it could also be an employer if an employee's private messages have been called into question.
NEW QUESTION: 2
You are evaluating a Python NumPy array that contains six data points defined as follows:
data = [10, 20, 30, 40, 50, 60]
You must generate the following output by using the k-fold algorithm implantation in the Python Scikit-learn machine learning library:
train: [10 40 50 60], test: [20 30]
train: [20 30 40 60], test: [10 50]
train: [10 20 30 50], test: [40 60]
You need to implement a cross-validation to generate the output.
How should you complete the code segment? To answer, select the appropriate code segment in the dialog box in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: k-fold
Box 2: 3
K-Folds cross-validator provides train/test indices to split data in train/test sets. Split dataset into k consecutive folds (without shuffling by default).
The parameter n_splits ( int, default=3) is the number of folds. Must be at least 2.
Box 3: data
Example: Example:
>>>
>>> from sklearn.model_selection import KFold
>>> X = np.array([[1, 2], [3, 4], [1, 2], [3, 4]])
>>> y = np.array([1, 2, 3, 4])
>>> kf = KFold(n_splits=2)
>>> kf.get_n_splits(X)
2
>>> print(kf)
KFold(n_splits=2, random_state=None, shuffle=False)
>>> for train_index, test_index in kf.split(X):
print("TRAIN:", train_index, "TEST:", test_index)
X_train, X_test = X[train_index], X[test_index]
y_train, y_test = y[train_index], y[test_index]
TRAIN: [2 3] TEST: [0 1]
TRAIN: [0 1] TEST: [2 3]
References:
https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.KFold.html
NEW QUESTION: 3
Scenario: A Citrix Engineer is designing a multi-server Provisioning Services solution. The solution must be highly available and minimize the risk of vDisk inconsistency.
Which configuration can the engineer implement to meet the needs of this design?
A. Create the Provisioning Services vDisk Store on a configured, single Distributed File System (DFS) namespace.
B. Configure a separate local vDisk Store on each Provisioning Services server and use rsync for Windows to replicate the vDisks.
C. Configure a separate local vDisk Store on two Provisioning Services servers on different sites and use the export/import feature to replicate the vDisks.
D. Configure a vDisk Store on a Common Internet File System (CIFS) share on a Network Attached Storage (NAS) for each Provisioning Services server.
Answer: D
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