A financial organization implements a new AI-based fraud detection system to flag suspicious transactions. A security analyst discovers that it occasionally blocks legitimate transactions. Which of the following is the best recommendation?
Answer(s): A
False positives occur when the AI model lacks sufficient or representative training data. Retraining the model with more diverse and recent transaction patterns improves accuracy, reducing the chance of legitimate transactions being incorrectly flagged.
Which of the following technologies is used in deepfake?
Deepfakes are primarily created using GANs, where two neural networks (a generator and a discriminator) compete to produce highly realistic synthetic media, such as manipulated videos or images.
During the selection of a machine learning (ML)-based threat classification model, a cybersecurity administrator verifies that label distribution is highly unbalanced. Which of the following processing techniques should the engineer use to balance the model?
Answer(s): B
When label distribution is highly unbalanced, data augmentation generates additional synthetic samples for the underrepresented classes. This balances the dataset, improving the ML model’s ability to classify threats accurately across all categories.
A healthcare organization plans to deploy a chatbot for appointment scheduling and patient records. Which of the following is the first step a security administrator should take?
Answer(s): C
Before deploying an AI chatbot that will handle sensitive healthcare data, the first step is to conduct a risk assessment. This identifies potential threats, compliance requirements (such as HIPAA), and security gaps, ensuring proper controls are planned before implementation.
Which of the following helps in managing potential security issues related to model training?
The NIST AI RMF provides structured guidance for identifying, assessing, and managing risks specific to AI systems, including those arising during model training. It addresses issues like bias, security, and data integrity, making it the best framework for managing training-related security concerns.
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