At Black Hat USA 2020, McAfee researchers showed how they were able to successfully trick a facial-recognition system into misclassifying one individual as an entirely different person.

Researchers say that an attacker would be able to stealthily force price fluctuations in the service of profit, chaos, or both, by deploying high-wattage IoT botnets in a strategic manner.

Researchers studied 100 open-source automation programs developed with legacy languages and discovered several vulnerabilities, including flaws that could allow hackers to control or disrupt a robot.

Researchers from BGU and NUS developed a method to detect connected, vulnerable IoT models before they are compromised by monitoring the data traffic from each smart home device.

Over the next three years, the project aims to research, develop, and demonstrate a real-time, advanced, building-resilient platform through multi-layer prevention and adaption mechanisms.

The researchers report that is it possible to extract private information from collage images of meeting participants posted on Instagram and Twitter.

Researchers at the National University of Singapore published a technique that locates the image areas where changes can best disrupt image-recognition algorithms, without being noticed by humans.

Cybersecurity researchers found that if attackers could monitor the data uploaded by internet protocol (IP) security cameras, they could predict if people were at home.

The researchers trained a deep neural network to predict the location of drone operators, using only the path of the drones, which does not require additional sensors.

A team of academics has described this week a method that can help identify when Facebook app developers surreptitiously share user data with third-parties.