This Startup Can Find Hidden Cameras In Your Oyo, AirBnB & Hotel Rooms: Find Out How?
With privacy being a myth. Do you also dread that due to increased technology adoption by people, you are being surveilled. Many of us dread while going to some hotel rooms or airbnbs, that we are being recorded or not. This stays in the back o
Have you ever wondered that is there anyway one can find a hidden camera?
A system has been devised by a group of academics which can be used either on a phone or a laptop to identify and locate the Wi-Fi-connected hidden IoT devices in unfamiliar physical spaces.
The goal is to be able to pinpoint such sneaky and surreptitious devices that are increasingly being used to invade our privacy.
In a new paper, Rahul Anand Sharma, Elahe Soltanaghaei, Anthony Rowe, and Vyas Sekar of Carnegie Mellon University said that the system which goes by the name, “Lumos”, is designed with the intent in mind to “visualize their presence using an augmented reality interface”.
The platform works by snuffing and collecting encrypted wireless packets over the air to detect and identify concealed devices.
Not only this, but also the device is capable enough to detect the location of each identified device with respect to the user as they walk around the perimeter of the space.
How Does It Work?
The localization module, for its part, combines signal strength measurements that are available in 802.11 packets (aka Received Signal Strength Indicator or RSSI) with relative user position determined by visual inertial odometry (VIO) information on mobile phones.
The positional tracking, for instance on an Apple’s iOS devices is achieved by means of ARKit, a developer API that makes it possible to build augmented reality experiences by taking advantage of the phone’s camera, CPU, GPU, and motion sensors.
The team said that when a user walks closer to any planted device, the RSSI values increase and decrease when the user walks away.
The spatial measurements of RSSI values as well as their variations to the estimate the location of each device are leveraged by Lumos.
Notably, irrespective of the user’s walking speed IoT devices can be localized by Lumos.
Also incorporated is a fingerprinting module that analyzes the captured 802.11 traffic patterns using a machine learning model to identify the devices based on the MAC addresses.
Spanning across various types, models, and brands across six different environments, Lumos has been evaluated across 44 different IoT devices.
Lumos can identify hidden devices with 95% accuracy and locate them with a median error of 1.5m within 30 minutes in a two-bedroom, 1000 sq.ft. apartment.
That being said, there is a catch. If the attacker leverages techniques like MAC address randomization and sidestep localization by arbitrarily modifying the devices’ transmit power, the detection by Lumos can be evaded.
Pointing out to how the system can even identify unprofiled devices, the researchers said that the “Lumos can potentially generalize across different device brands and models, as long as it has seen at least one device with similar behavior in the training phase”.