08 December 2020 Department of Computer Science , Faculty , News Media , Systems & Networking , Security

When your robot vacuum cleaner does its work around the house, beware that it could pick up private conversations along with the dust and dirt. Computer scientists from NUS have demonstrated that it is indeed possible to spy on private conversations using a common robot vacuum cleaner and its built-in Light Detection and Ranging (Lidar) sensor.

The novel method, called LidarPhone, repurposes the Lidar sensor that a robot vacuum cleaner normally uses for navigating around a home into a laser-based microphone to eavesdrop on private conversations.

The research team, led by Assistant Professor Jun Han from NUS Computer Science, and his doctoral student Mr Sriram Sami, managed to recover speech data with high accuracy. NUS students, Mr Dai Yimin and Mr Sean Tan Rui Xiang, as well as Assistant Professor Nirupam Roy from the University of Maryland, also contributed to this work.

Mr Sami shared, “The proliferation of smart devices – including smart speakers and smart security cameras – has increased the avenues for hackers to snoop on our private moments. Our method shows it is now possible to gather sensitive data just by using something as innocuous as a household robot vacuum cleaner. Our work demonstrates the urgent need to find practical solutions to prevent such malicious attacks.”'

The core of the LidarPhone attack method is the Lidar sensor, a device which fires out an invisible scanning laser, and creates a map of its surroundings. By reflecting lasers off common objects such as a dustbin or a takeaway bag located near a person’s computer speaker or television soundbar, the attacker could obtain information about the original sound that made the objects’ surfaces vibrate. Using applied signal processing and deep learning algorithms, speech could be recovered from the audio data, and sensitive information could potentially be obtained.

AZO Robotics, 8 December 2020

South China Morning Post, 8 December 2020

CNA, 7 December 2020

TODAYOnline, 7 December 2020

Mothership.sg, 7 December 2020

Futurity, 7 December 2020

NUS News, 7 December 2020

Forbes, 22 November 2020