Killing One Bird with Two Stones: Model Extraction and Attribute Inference Attacks against BERT-based APIs

Understand

The collection and availability of big data, combined with advances in pre-trained models (e.g., BERT, XLNET, etc), have revolutionized the predictive performance of modern natural language processing tasks, ranging from text classification to text generation.

• This allows corporations to provide machine learning as a service (MLaaS) by encapsulating fine-tuned BERT-based models as APIs.
• However, BERT-based APIs have exhibited a series of security and privacy vulnerabilities.
• For example, prior work has exploited the security issues of the BERT-based APIs through the adversarial examples crafted by the extracted model.