Although machine learning security research is still in its early stages, it’s clear that input possibilities without barriers increase threats. You don’t need to touch a keyboard anymore to fool a machine learning system. Software security expert Balázs Kiss touches upon a few points in this new field and gives advice on the basic protection measures.
Just like software in general, machine learning systems are vulnerable. “On the one hand, they’re pretty much like newborn babies that rely entirely on their parents to learn how the world works – including ‘backdoors’ such as fairy tales, or Santa Claus,” says security expert Balázs Kiss from Cydrill, a company specialized in software security. “On the other hand, machine learning systems are like old cats with poor eyesight – when a mouse learns how the cat hunts, it can easily avoid being seen and caught.”
Things don’t look good, according to Kiss. “Machine learning security is becoming a critical topic.” He points out that most software developers and experts in machine learning are unaware of the attack techniques. “Not even those that have been known to the software security community for a long time. Neither do they know about the corresponding best practices. This should change.”
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