CANBERRA, June 21 (Xinhua) -- A team from Australia's peak science agency has developed a world-first technique to protect algorithms against cyber-attacks.
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."
The CSIRO has previously invested 19 million Australian dollars (13.2 million U.S. dollars) in developing artificial intelligence-driven solutions to security, food security and sustainable resources.
Adrian Turner, the chief executive of Data61, said that the development "will spark a new line of machine learning research and ensure the positive use of transformative AI technologies."