Countering IoT enabled Covert Surveillance : Commercial Solutions for Hidden Device Discovery

Small Internet-connected devices like GPS trackers, mini cameras and item finders (such as Air
Tag and Tile) are being used by perpetrators of domestic and interpersonal abuse to monitor and
harass the victim-survivors. This misuse of digital services or products for surveillance and
stalking falls under the larger phenomenon of technology-facilitated interpersonal abuse.
Survivors of such abuse are often subject to anxiety and a fear of technology. Growing reports of
surveillance using hidden devices have led to many commercial solutions for detecting such
devices. In this project, we aim to investigate the availability and limitations of existing commercial
solutions for detecting hidden connected devices. In addition, we are interested in overcoming
the challenges and building a novel solution that is safe and usable for survivors of technology
abuse. We envision that this project's outcomes would benefit researchers, survivors of
technology abuse, and stakeholders supporting survivors, including frontline support services like
law enforcement and women's refuges/charities like Respect.
To achieve our objectives, we designed two studies: a Systemization of Knowledge and a
Feasibility study. The 'Systemisation of Knowledge' study aims to map the commercial solutions
for hidden device discovery in the UK. The solution space includes three types of products:
physical devices, mobile apps and private investigative services. The study will evaluate the
usability and functionality of a representative sample of these solutions using an observation
study and user interviews. We plan to recruit participants for the observation study, where they
will use these solutions to detect hidden devices planted in a controlled room. The participants
will then be interviewed to learn some insights about the usability of these solutions. We plan to
recruit participants who are experts in using radio frequency equipment, in addition to people
working with frontline support services. Furthermore, we plan to interview representatives from
private investigative services to understand their practices and the type of devices used.
Most hidden devices are often embedded with wireless capabilities like Wi-Fi and Bluetooth Low
Energy (BLE) to transmit the sensed data over the Internet. These capabilities allow the wireless
network to be monitored to identify any active transmissions over a short period to help detect
and locate the devices. The Feasibility study aims to investigate the challenges and limitations of
utilising Signal Intelligence (SIGINT) based solutions for detecting and localising hidden IoT
devices. SIGINT extracts signal characteristics like modulation, protocol, and radio frequency
(RF) fingerprints from unknown RF signals. RF Fingerprinting (RFF) refers to identifying individual
RF transmitters using the unique non-linear characteristics of RF circuitry impacting the
transmitted signal. The reliance on physical (PHY) layer properties enables such a solution to
work across a wide range of electromagnetic RF spectrum. However, to be an effective solution,
we must overcome the challenges of working in a congested and noisy environment characteristic
of a typical IoT ecosystem.