Which of the following describes the mam difference between supervised and unsupervised machine-learning algorithms that are used in cybersecurity applications?

Which of the following describes the mam difference between supervised and unsupervised machine-learning algorithms that are used in cybersecurity applications?
A . Supervised algorithms can be used to block attacks, while unsupervised algorithms cannot.
B . Supervised algorithms require security analyst feedback, while unsupervised algorithms do not.
C . Unsupervised algorithms are not suitable for IDS systems, white supervised algorithms are
D . Unsupervised algorithms produce more false positives. Than supervised algorithms.

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Answer: B

Explanation:

Supervised and unsupervised machine-learning algorithms are two types of machine-learning methods that are used in cybersecurity applications. Machine learning is a branch of artificial intelligence that enables systems to learn from data and improve their performance without explicit programming.

Supervised machine-learning algorithms are trained on labeled data, which means that each data point has a known outcome or class. Supervised algorithms learn to map input data to output data by finding patterns or rules from the training data. Supervised algorithms require security analyst feedback to provide labels for the data and evaluate the accuracy of the algorithm’s predictions. Examples of supervised machine-learning algorithms are classification and regression.

Unsupervised machine-learning algorithms are trained on unlabeled data, which means that each data point has no known outcome or class. Unsupervised algorithms learn to discover hidden structures or patterns from the data without any guidance or feedback. Unsupervised algorithms do not require security analyst feedback, as they do not rely on predefined labels or outcomes. Examples of unsupervised machine-learning algorithms are clustering and anomaly detection.

Reference: What is Machine Learning? | IBM Supervised Learning | Machine Learning Crash Course | Google Developers Unsupervised Learning | Machine Learning Crash Course | Google Developers