Refer to scenario & answer the question

Faster response with automated triage & handling of common incidents.

Refer to scenario & answer the question

Behavioral monitoring and analysis

Refer Scenario & Answer the question

Behavioral anomaly detection using unsupervised learning

Your AI-powered threat hunting tool struggles with zero-day exploits. What’s the best approach?

Use unsupervised learning for anomaly detection

AI-based EDR is not performing well against new fileless malware attacks. What is the most effective countermeasure?

Train AI models on memory behavior instead of file signatures

An AI-powered SOC tool is struggling with adversarial examples in network traffic. How can the system be improved?

Implement adversarial training with simulated attack data

Refer to scenario & answer the question

By developing a predictive risk model

An attacker uses AI-generated phishing emails to bypass traditional filters. Which AI-driven defense is most effective?

Natural Language Processing (NLP)-based anomaly detection

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AI in Cybersecurity Day 2 Quiz

10 termsStudBud Administration69 plays

Imported from external platform

Flashcards10 cardsFPractice quizPHost liveL

Questions 10

Answers

1
Attackers poison your AI threat detection model with adversarial examples. What’s the best mitigation strategy?
Ignore low-confidence AI predictions
Use manual log analysis instead of AI
Implement adversarial training
Reduce AI sensitivity to outliers
2
Refer to scenario & answer the question
100% accurate classification of all alerts
Faster response with automated triage & handling of common incidents.
Complete elimination of all security incidents
The ability to fire half of the security team
3
AI-powered deception systems misclassify real threats as benign. What’s the primary cause?
AI lacks context-aware models
Model hyperparameter misconfiguration
Overfitting on training data
Too many adversarial examples in training
4
Refer to scenario & answer the question
Signature-based scanning
File hash verification
Behavioral monitoring and analysis
Email header inspection
5
Refer Scenario & Answer the question
Supervised learning with labeled encrypted data
Rule-based pattern matching on metadata
Behavioral anomaly detection using unsupervised learning
Deep packet inspection with supervised learning
6
Your AI-powered threat hunting tool struggles with zero-day exploits. What’s the best approach?
Rely only on signature-based detection
Reduce dataset size for faster processing
Train AI only on past zero-day attacks
Use unsupervised learning for anomaly detection
7
AI-based EDR is not performing well against new fileless malware attacks. What is the most effective countermeasure?
Train AI models on memory behavior instead of file signatures
Increase manual forensic investigations
Implement a stricter firewall policy
Use AI for detecting only traditional malware
8
An AI-powered SOC tool is struggling with adversarial examples in network traffic. How can the system be improved?
Reduce dataset size for faster training
Use only rule-based detection methods
Disable AI-based detection and rely on manual SOC analysts
Implement adversarial training with simulated attack data
9
Refer to scenario & answer the question
By focusing all resources on the headquarters location
By implementing the same security measures all locations regardless of risk
By relying solely on the CVSS scores of detected vulnerabilities
By developing a predictive risk model
10
An attacker uses AI-generated phishing emails to bypass traditional filters. Which AI-driven defense is most effective?
Sender reputation analysis
Email attachments scanning only
Rule-based filtering
Natural Language Processing (NLP)-based anomaly detection

AI in Cybersecurity Day 2 Quiz Flashcards | StudBud

AI in Cybersecurity Day 2 Quiz

10 termsStudBud Administration69 plays

Imported from external platform

Flashcards10 cardsFPractice quizPHost liveL

Questions 10

Answers

1
Attackers poison your AI threat detection model with adversarial examples. What’s the best mitigation strategy?
Ignore low-confidence AI predictions
Use manual log analysis instead of AI
Implement adversarial training
Reduce AI sensitivity to outliers
2
Refer to scenario & answer the question
100% accurate classification of all alerts
Faster response with automated triage & handling of common incidents.
Complete elimination of all security incidents
The ability to fire half of the security team
3
AI-powered deception systems misclassify real threats as benign. What’s the primary cause?
AI lacks context-aware models
Model hyperparameter misconfiguration
Overfitting on training data
Too many adversarial examples in training
4
Refer to scenario & answer the question
Signature-based scanning
File hash verification
Behavioral monitoring and analysis
Email header inspection
5
Refer Scenario & Answer the question
Supervised learning with labeled encrypted data
Rule-based pattern matching on metadata
Behavioral anomaly detection using unsupervised learning
Deep packet inspection with supervised learning
6
Your AI-powered threat hunting tool struggles with zero-day exploits. What’s the best approach?
Rely only on signature-based detection
Reduce dataset size for faster processing
Train AI only on past zero-day attacks
Use unsupervised learning for anomaly detection
7
AI-based EDR is not performing well against new fileless malware attacks. What is the most effective countermeasure?
Train AI models on memory behavior instead of file signatures
Increase manual forensic investigations
Implement a stricter firewall policy
Use AI for detecting only traditional malware
8
An AI-powered SOC tool is struggling with adversarial examples in network traffic. How can the system be improved?
Reduce dataset size for faster training
Use only rule-based detection methods
Disable AI-based detection and rely on manual SOC analysts
Implement adversarial training with simulated attack data
9
Refer to scenario & answer the question
By focusing all resources on the headquarters location
By implementing the same security measures all locations regardless of risk
By relying solely on the CVSS scores of detected vulnerabilities
By developing a predictive risk model
10
An attacker uses AI-generated phishing emails to bypass traditional filters. Which AI-driven defense is most effective?
Sender reputation analysis
Email attachments scanning only
Rule-based filtering
Natural Language Processing (NLP)-based anomaly detection