Isaca ISACA Advanced in AI Security Management (AAISM) Exam AAISM Question # 50 Topic 6 Discussion
AAISM Exam Topic 6 Question 50 Discussion:
Question #: 50
Topic #: 6
An organization decides to use an anomaly-based intrusion detection system (IDS) integrated with a generative adversarial network–enabled AI tool. The integrated tool would MOST effectively detect intrusions by leveraging:
A.
synthetic intrusion data to train the tool’s components
B.
validation data sets to enable highly realistic AI decisions
C.
automated rule creation to increase model performance
D.
classified real intrusion data based on labeled data
AAISM describes GANs as effective for synthetic data generation to augment scarce or imbalanced security datasets. In anomaly IDS contexts, GANs can create realistic synthetic attack traffic and edge-case behaviors that improve detector sensitivity and robustness. While labeled “real” data is valuable, the specific advantage of a GAN-integrated pipeline is the capability to generate adversarially realistic synthetic intrusions for training and stress testing. Automated rules are a signature-based paradigm and do not leverage GAN strengths; validation sets are for evaluation, not primary improvement of anomaly coverage.
[References:• AI Security Management™ (AAISM) Body of Knowledge: Security data engineering; synthetic data via generative models for rare-event detection; adversarial augmentation for IDS.• AI Security Management™ Study Guide: Model robustness with synthetic adversarial examples; training-set enrichment for anomaly detection., ===========]
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