1. Understanding-ML-Model-Access-Techniques-and-Implications (2)

Understanding ML Model Access: Techniques and Implications.

Adversarial Techniques. Strategic Data Manipulation.

Visualizing Adversarial Techniques. This slide showcases a detailed illustration of how adversarial techniques can be used to bypass an AI-powered spam filter. The cyberpunk-inspired visual depicts the strategic manipulation of input data to evade detection, highlighting the vulnerabilities of machine learning systems when faced with carefully crafted adversarial attacks..

Avoiding Detection. Identify Weaknesses. Analyze the target ML model to uncover its vulnerabilities and blind spots that can be exploited through adversarial techniques.. Modify Input Data Strategically alter input data in subtle ways to bypass the model's detection mechanisms, such as slightly tweaking email content to evade spam filters. Test and Iterate Continuously test the modified inputs against the ML model, refining the adversarial techniques until the desired level of evasion is achieved.

Detection Avoidance Example. In a real-world scenario, an attacker could leverage adversarial techniques to bypass an ML-based spam filter by slightly modifying the content of an email, such as rephrasing sentences or changing the tone, while preserving the original meaning..