Injecting Trojan horses with Keras Lambda layers
An attacker can choose to bypass the restrictions of a model format and implement an attack that works regardless of the chosen model format. This will involve extensibility APIs that model a development framework offer.
Keras Lambda layers represent one of these. By using a lambda layer, you can quickly implement operations—such as arithmetic operations—applying a specific function (to the output) or any other simple operation that you want to perform on the layer’s output without defining a new custom layer. This can make the model construction process more straightforward and cleaner, especially for simple transformations. Example use cases include custom activation functions, normalization, scaling transformations, etc. For more information, see the following link to the official Keras documentation: https://keras.io/api/layers/core_layers/lambda.
Lambda layers are designed for custom operations, but they...
