In September 2019, the National Institute of Standards and Technology issued its first-ever warning for an attack on a commercial artificial intelligence algorithm.
Security researchers had devised a way to attack a Proofpoint product that uses machine learning to identify spam emails. The system produced email headers that included a “score” of how likely a message was to be spam. But analyzing these scores, along with the contents of messages, made it possible to build a clone of the machine-learning model and craft spam messages that evaded detection.
The vulnerability notice may be the first of many. As AI is used more widely, new opportunities for exploiting weak spots in the technology also are emerging. That’s given rise to companies that probe AI systems for vulnerabilities, with the goal of catching malicious input before it can wreak havoc.
Startup Robust Intelligence is one such company. Over Zoom, Yaron Singer, its cofounder and CEO, demonstrates a program that uses AI to outwit the AI that reads checks, an early application for modern machine learning.
Singer’s program automatically tweaks the intensity of a few pi ..
Support the originator by clicking the read the rest link below.
