CSIRO scientists have developed a ‘vaccine’ against attacks on AI

Researchers from Data61, the CSIRO’s data and digital specialist arm, have developed techniques they claim will effectively ‘vaccinate’ algorithms against adversarial attack, meaning it will prevent malevolent actors from hijacking  machine learning.

Dr Richard Nock, Data61 machine learning group leader, explained that algorithms ‘learn’ from the data they are trained on to create a machine learning model that can perform a given task effectively without needing specific instructions, such as making predictions or accurately classifying images and emails.

Those techniques are already in common use to identify spam emails, diagnose diseases from X-rays, predict crop yields and will soon drive our cars.

But adding a layer of noise (i.e. an adversary) over an image, means attackers can deceive machine learning models into misclassifying it.

Dr Nock said adversarial attacks have already tricked a machine learning model into incorrectly interpreting a traffic stop sign as a speed sign – an outcome with potentially disastrous results.

“Our new techniques prevent adversarial attacks using a process similar to vaccination,” he said.

“We implement a weak version of an adversary, such as small modifications or distortion to a collection of images, to create a more ‘difficult’ training data set. When the algorithm is trained on data exposed to a small dose of distortion, the resulting model is more robust and immune to adversarial attacks. ”