Question: In the context of automated attacks, how does machine learning assist in evading detection by learning and adapting to the unique characteristics of intrusion detection systems (IDS)?
Answer:
Machine learning algorithms can learn from
MCQ: In the context of automated attacks, how does machine learning assist in evading detection by learning and adapting to the unique characteristics of intrusion detection systems (IDS)?
Correct Answer:
A. Evading IDS is not relevant to machine learning.
Explanation:
Machine learning algorithms can learn from
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Related Questions
- 1. How does machine learning contribute to the automation of attacks by improving the ability to identify and exploit logical vulnerabilities in web applications?
- 2. Why is the integration of machine learning with automated attacks crucial for adapting to emerging threats and zero-day vulnerabilities in real-time?
- 3. What is the primary legal concern associated with automated attacks in web security?
- 4. Why is the use of automated attacks without proper authorization ethically problematic?
- 5. In the context of ethical considerations, why is responsible disclosure important after discovering vulnerabilities through automated testing?
- 6. What role does transparency play in the ethical handling of automated attacks and vulnerabilities?
- 7. From a legal perspective, what defines the line between ethical security research and illegal activities in the context of automated attacks?
- 8. What is the primary purpose of responsible disclosure in the context of automated attacks?
- 9. How can adherence to ethical standards in automated attacks contribute to the overall improvement of web security?
- 10. What potential harm can be caused by automated attacks conducted without adherence to ethical standards?
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