Question: In the context of automated attacks, how does machine learning contribute to the improvement of attack precision and reducing false positives?

Answer:

Machine learning algorithms can analyze patterns and behaviors, improving attack precision and reducing false positives in automated attacks in the context of web security.

MCQ: In the context of automated attacks, how does machine learning contribute to the improvement of attack precision and reducing false positives?

A. Precision and false positives are not relevant to machine learning.
B. Machine learning algorithms can analyze patterns and behaviors, improving attack precision and reducing false positives in automated attacks.
C. Automation and precision are unrelated concepts.
D. Machine learning is limited to reconnaissance.

Correct Answer: A. Precision and false positives are not relevant to machine learning.

Explanation:

Machine learning algorithms can analyze patterns and behaviors, improving attack precision and reducing false positives in automated attacks in the context of web security.