Countermeasures for backdoor attacks of deep learning systems

A computer program product for training countermeasures for a backdoor attack on a neural network model, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein an execution of the program instructions by a computer processor cause a computing device to:

• receive definitions of a maximum learning rate and a minimum learning rate to train the deep learning model against backdoor attacks;
• initialize the subject model to run a learning process using the minimum learning rate;
• cycle the learning process of the deep learning model through the maximum learning rate and the minimum learning rate;
• and
• interleave the cycling of the learning process using a first data set of clean data and a second data set of poisoned data until a threshold value of defense is reached.

A computing server configured to train countermeasures against a backdoor attack on a neural network model, comprising:

• a computer processor operating a backdoor model countermeasure training engine;
• and
• a memory coupled to the computer processor, the memory storing instructions to cause the computer processor to perform acts comprising:
• defining a maximum learning rate and a minimum learning rate to train the deep learning model against backdoor attacks;
• initializing the subject model to run a learning process using the minimum learning rate;
• cycling the learning process of the deep learning model through the maximum learning rate and the minimum learning rate;
• and
• interleaving the cycling of the learning process using a first data set of clean data and a second data set of poisoned data until a threshold value of defense is reached.