Rutgers University researchers have developed a WiFi-based system for detecting dangerous objects that is faster and less expensive than scanners seen in airports and other venues.
A new study from University of Chicago and University of California, Santa Barbara researchers finds that external attackers can use inexpensive technology to turn these ambient signals into motion detectors, monitoring activity inside a building without being detected themselves.
With only a small, commercially available Wi-Fi receiver, an attacker from outside the target site can measure the strength of signals emitted from connected devices and monitor a site remotely for motion, sensing whether a room is occupied.
Researchers have developed a new way to detect whether a room is occupied by humans or not: by analyzing the effect of their movement on ambient radio signals using a convolutional neural network.
A radar device the size of a Wi-Fi router could help continuously monitor Parkinson’s disease in patients from afar as they go about their lives at home. By using radio waves to track the gait of Parkinson’s patients, the device should help doctors assess the effectiveness of medications, see how the disease is progressing, and create better treatment plans.
Parkinson’s disease is a chronic, progressive brain disorder that affects motor function, causing tremors, impaired balance, and the risk of falls and injuries. There is no cure for it and patients rely on medications to control symptoms.
Espressif ESP-WIFI-CSI software relies on the disturbance in the force WiFi signals between one or more ESP32 boards and a router to detect whether humans are present in a room, or even indoor positioning, providing a cost-effective solution since no sensors are needed.
Channel state information (CSI) leverages carrier signal strength, amplitude, phase, and signal delay indicators to reveal the signal scattering, reflection, and power attenuation phenomena that occur with the carrier as the transmission distance changes. This
Researchers Spin up Terrifying Hacker Drone That Can ‘See Through Walls’ With Wifi https://gizmodo.com/drone-see-through-walls-wifi-wi-peep-waterloo-research-1849744061
Using a $20 off-the-shelf drone, researchers at the University of Waterloo in Ontario have created what is effectively an airborne scanning device that can triangulate the location of every WiFi-connected device in your house. Researchers say their device exploits security deficiencies in IEEE 802.11-a longstanding wireless protocol for local access networks that has a history of problems with data interception and eavesdropping. The program deploys what is known as a “time-of-flight” technique (ToF), which uses a data manipulation trick to measure the physical distance between a signal and an object.
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9 Comments
Tomi Engdahl says:
Researchers Use WiFi to Count the Number of Individuals in a Crowd
https://blog.hackster.io/researchers-use-wifi-to-count-the-number-of-individuals-in-a-crowd-ec67d182621f
Tomi Engdahl says:
Detecting Bombs and Weapons with WiFi
https://www.designnews.com/electronics-test/detecting-bombs-and-weapons-wifi/21821247859822?ADTRK=UBM&elq_mid=6575&elq_cid=876648
Rutgers University researchers have developed a WiFi-based system for detecting dangerous objects that is faster and less expensive than scanners seen in airports and other venues.
Tomi Engdahl says:
New Tech Uses WiFi to Read Your Inner Emotions – Accurately, and From Afar
https://bigthink.com/robby-berman/new-tech-can-accurately-read-the-emotions-you-may-be-hiding
Researchers at MIT have developed a system that can read a person’s emotions, even hidden ones, at a distance.
Tomi Engdahl says:
How hackers could use Wi-Fi to track you inside your home
https://techxplore.com/news/2019-11-hackers-wi-fi-track-home.html
A new study from University of Chicago and University of California, Santa Barbara researchers finds that external attackers can use inexpensive technology to turn these ambient signals into motion detectors, monitoring activity inside a building without being detected themselves.
With only a small, commercially available Wi-Fi receiver, an attacker from outside the target site can measure the strength of signals emitted from connected devices and monitor a site remotely for motion, sensing whether a room is occupied.
Tomi Engdahl says:
Researchers have developed a new way to detect whether a room is occupied by humans or not: by analyzing the effect of their movement on ambient radio signals using a convolutional neural network.
Researchers Train a Neural Network to Detect Human Occupancy by Sniffing Ambient Wi-Fi Signals
https://www.hackster.io/news/researchers-train-a-neural-network-to-detect-human-occupancy-by-sniffing-ambient-wi-fi-signals-21127327da3b
By monitoring the Wi-Fi signals in a room, and passing the data through a convolutional neural network, human presence can be detected.
Tomi Engdahl says:
Wi-Fi devices set to become object sensors by 2024 under planned 802.11bf standard
Security and privacy still left to fix, preferably before launch
https://www.theregister.com/2021/03/31/wifi_devices_monitoring/
Tomi Engdahl says:
Monitoring Parkinson’s Patients at Home Could Improve Disease Management Device uses low-power radio waves to assess walking speeds
https://spectrum.ieee.org/radar-device-could-monitor-parkinson-s-at-home
A radar device the size of a Wi-Fi router could help continuously monitor Parkinson’s disease in patients from afar as they go about their lives at home. By using radio waves to track the gait of Parkinson’s patients, the device should help doctors assess the effectiveness of medications, see how the disease is progressing, and create better treatment plans.
Parkinson’s disease is a chronic, progressive brain disorder that affects motor function, causing tremors, impaired balance, and the risk of falls and injuries. There is no cure for it and patients rely on medications to control symptoms.
Tomi Engdahl says:
ESP-WIFI-CSI detects humans with WiFi signals only, no sensor needed
https://www.cnx-software.com/2022/08/08/esp-wifi-csi-detects-humans-with-wifi-signals-only-no-sensor-needed/
Espressif ESP-WIFI-CSI software relies on the disturbance in the force WiFi signals between one or more ESP32 boards and a router to detect whether humans are present in a room, or even indoor positioning, providing a cost-effective solution since no sensors are needed.
Channel state information (CSI) leverages carrier signal strength, amplitude, phase, and signal delay indicators to reveal the signal scattering, reflection, and power attenuation phenomena that occur with the carrier as the transmission distance changes. This
Tomi Engdahl says:
Researchers Spin up Terrifying Hacker Drone That Can ‘See Through Walls’ With Wifi
https://gizmodo.com/drone-see-through-walls-wifi-wi-peep-waterloo-research-1849744061
Using a $20 off-the-shelf drone, researchers at the University of Waterloo in Ontario have created what is effectively an airborne scanning device that can triangulate the location of every WiFi-connected device in your house. Researchers say their device exploits security deficiencies in IEEE 802.11-a longstanding wireless protocol for local access networks that has a history of problems with data interception and eavesdropping. The program deploys what is known as a “time-of-flight” technique (ToF), which uses a data manipulation trick to measure the physical distance between a signal and an object.