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New Aussie “vaccine” to prevent disastrous effects of cyber-attacks: top scientists

The history of exposing machine learning algorithms to the world shows how easy it is to ‘pollute’ the data. Here’s an idea from Australia to protect them…:

Researchers from Data61, the data and digital arm of the Commonwealth Scientific and Industrial Research Organisation (CSIRO), said on Thursday that the “vaccine” is a significant advancement in machine learning research.

Algorithms can perform given tasks such as diagnose diseases from x-rays and identify spam emails but are vulnerable to adversarial attacks, a form of cyber-attack whereby malicious data causes them to malfunction.

Richard Nock, leader of the machine learning group at Data61, said that adversarial attacks work by adding a layer of noise over malicious data that deceives an algorithm into misclassifying it.

“Adversarial attacks have proven capable of tricking a machine learning model into incorrectly labelling a traffic stop sign as speed sign, which could have disastrous effects in the real world,” he said in a media release.

“Our new techniques prevent adversarial attacks using a process similar to vaccination.

“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.”


Original article here

Peter Glock
Over 30 years of designing, building and managing telecoms and IT services. Primarily working with large enterprise and professional services businesses in Asia, North America, continental Europe and the UK. Information security professional, secret physics nerd.

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