Sep 24, 2024 · Abstract. Model extraction aims to steal a functionally similar copy from a machine learning as a service (MLaaS) API with minimal overhead, typically for ...
Sep 27, 2024 · In this article, we'll review common attack strategies and dive into the latest defense mechanisms for shielding machine learning systems against adversarial ...
Sep 24, 2024 · This article investigates machine learning (ML) security, focusing on threats and attacks against ML. We have created a threat model for ML to illustrate ...
Best Practices in Machine Learning Model Security - CyberMatters
cybermatters.info › AI Cybersecurity
Sep 23, 2024 · Discover essential strategies for protecting your machine learning models. I'll guide you through machine learning model security best practices to ...
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Sep 30, 2024 · The watermark detection process aims to discern whether the suspected model has used watermarked data from a victim model for training. Report issue for ...
Sep 26, 2024 · Effective defense strategies include adversarial training, robust data validation, frequent retraining, algorithmic transparency, and restricted access to model.
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1 day ago · The proposed work aims to present a systematic review of primary studies that focuses on providing an efficient and robust framework against adversarial attacks ...
Sep 15, 2024 · ML model extraction attack arises when an adversary obtains black-box access to some target model f and at- tempts to learn a modeî f that closely approximates ...
Sep 18, 2024 · To protect the intellectual property of model owners, we propose an effective defense method against model stealing attacks with the localized stochastic ...
6 days ago · AI threat detection enhances traditional security by identifying sophisticated threats in real-time, helping organizations stay ahead of cybercriminals.
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