AAISM · Question #128
An organization decides to use an anomaly-based intrusion detection system (IDS) integrated with a generative adversarial network (GAN)璭nabled AI tool. The integrated tool would MOST effectively detec
The correct answer is D. Synthetic intrusion data to train the tool's components. A GAN's core value in this integration is its ability to generate realistic synthetic intrusion data. The generator creates synthetic attack traffic and the discriminator learns to distinguish it from normal traffic, producing a robust training dataset that includes rare or novel
Question
An organization decides to use an anomaly-based intrusion detection system (IDS) integrated with a generative adversarial network (GAN)璭nabled AI tool. The integrated tool would MOST effectively detect intrusions by leveraging:
Options
- AValidation data sets to enable highly realistic AI decisions
- BClassified real intrusion data based on labeled data
- CAutomated rule creation to increase model performance
- DSynthetic intrusion data to train the tool's components
How the community answered
(31 responses)- A3% (1)
- B3% (1)
- C10% (3)
- D84% (26)
Explanation
A GAN's core value in this integration is its ability to generate realistic synthetic intrusion data. The generator creates synthetic attack traffic and the discriminator learns to distinguish it from normal traffic, producing a robust training dataset that includes rare or novel attack patterns without requiring real incident data. This enables the anomaly-based IDS to detect deviations from normal baselines more accurately. Option A (validation datasets) concerns evaluation, not GAN-specific generation. Option B (labeled data) describes supervised learning, not the GAN mechanism. Option C (automated rule creation) is a signature-based concept unrelated to how GANs function.
Topics
Community Discussion
No community discussion yet for this question.