Address Analysis (Global)
High-quality technical overview of Address Analysis in the context of blockchain security.
Types of attacks include: 1. Evasion: Modifying data at test time (e.g., FGSM). 2. Poisoning: Injecting bad data during training. 3. Model Extraction: Stealing the model's parameters by querying its API. 4. Inversion: Reconstructing sensitive training data from model outputs.
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🧒 Explique como se eu tivesse 5 anos
Imagine a smart camera that recognizes cats. An adversarial attack is like showing it a picture of a cat but wearing a special pair of glasses that are so subtly patterns that the camera thinks the cat is actually a toaster, even though it still looks like a cat to you.
🤓 Expert Deep Dive
The core of many evasion attacks lies in 'Gradient-based' techniques. By calculating the gradient of the loss function with respect to the input, an attacker can find the minimal perturbation needed to push the input across the model's decision boundary. This 'perturbation vector' is often scaled so that it is imperceptible to human senses but mathematically significant to the model. A critical challenge is 'Attack Transferability', where an attack crafted for one model architecture often succeeds against another, even if the training data is different.