Catching
the IMSI-catchers: SeaGlass brings transparency to cell phone surveillance
University of Washington
Modern cell phones are vulnerable to attacks from rogue cellular
transmitters called IMSI-catchers -- surveillance devices that can precisely
locate mobile phones, eavesdrop on conversations or send spam.
Recent leaks and public records requests have revealed that law
enforcement in many U.S. cities have used the surveillance devices to locate
suspects or hunt for illegal activity.
But despite extensive public debate about their use and privacy
implications, little is known about how comprehensively International Mobile
Subscriber Identity- (IMSI) catchers -- also known as cell-site simulators or
Stingrays -- are being used by governments, hackers or criminals in any given
city.
University of Washington security researchers have developed a
new system called SeaGlass to detect anomalies in the cellular landscape that
can indicate where and when these surveillance devices are being used.
The new system is described in a paper to be published in June 2017 in Proceedings on Privacy Enhancing Technologies.
"Up until now the use of IMSI-catchers around the world has
been shrouded in mystery, and this lack of concrete information is a barrier to
informed public discussion," said co-lead author Peter Ney, a doctoral student
at the Allen School of Computer Science & Engineering at the UW.
"Having additional, independent and credible sources of
information on cell-site simulators is critical to understanding how -- and how
responsibly -- they are being used."
During a two-month deployment in which SeaGlass sensors were
installed in 15 ridesharing vehicles in Seattle and Milwaukee, researchers
identified dozens of anomalies that were consistent with patterns one might
expect from cell-site simulators.
However, researchers cautioned, without corroborating evidence
from public records requests or other documentation about where cell-site
simulators are being used -- or suspicious activity seen over a longer period
of time -- they cannot definitively say the signals came from IMSI-catchers.
"In this space there's a lot of speculation, so we want to
be careful about our conclusions. We did find weird and interesting patterns at
certain locations that match what we would expect to see from a cell-site
simulator, but that's as much as we can say from an initial pilot study,"
co-lead author Ian Smith, a former Allen School research scientist.
"But we think that SeaGlass is a promising technology that
-- with wider deployment -- can be used to help empower citizens and
communities to monitor this type of surveillance."
Cell-site simulators work by pretending to be a legitimate cell
tower that a phone would normally communicate with, and tricking the phone into
sending back identifying information about its location and how it is communicating.
The portable surveillance devices now range in size from a
walkie-talkie to a suitcase, and in price from several thousand to hundreds of
thousands of dollars.
Law enforcement teams in the U.S. have used the technology to
locate people of interest, to find equipment used in the commission of crimes
and even to collect massive amounts of cell phone data from airplanes.
Even less is known about how spies or cyber criminals are deploying them worldwide, especially as models become more affordable or able to be built in a hacker's garage.
Even less is known about how spies or cyber criminals are deploying them worldwide, especially as models become more affordable or able to be built in a hacker's garage.
To catch these IMSI-catchers in the act, SeaGlass uses sensors
built from off-the-shelf parts that can be installed in vehicles -- ideally
ones that drive long hours and to many parts of a city, such as ridesharing vehicles
or other fleets.
The sensors pick up signals broadcast from the existing cell
tower network, which remain fairly constant. Then SeaGlass aggregates that data
over time to create a baseline map of "normal" cell tower behavior.
The team from the UW Security and Privacy Research Lab developed
algorithms and other methods to detect irregularities in the cellular network
that can expose the presence of a simulator.
These include a strong signal in an odd spot or at an odd
frequency that has never been there before, "temporary" towers that
disappear after a short time and signal configurations that are different from
what a carrier would normally transmit.
Allen School doctoral student and co-author Gabriel Cadamuro
built statistical models to help find anomalies in the data. The team's survey
approach differs from existing apps that attempt to detect attacks from a
cell-site simulator on an individual's phone.
"We're looking at the whole cellular landscape and
pinpointing discrepancies in data, while the apps for the most part are
guessing at how a cell-site simulator would act with a phone," said Ney.
Co-author and Allen School professor Tadayoshi Kohno added,
"We've demonstrated that SeaGlass is effective in detecting these
irregularities and narrowing the universe of things people might want to
investigate further."
For instance, around an immigration services building south of
Seattle run by the U.S. Department of Homeland Security, SeaGlass detected a
cell tower that transmitted on six different frequencies over the two-month
period.
That was notable because 96 percent of all other base cell
towers broadcast on a single channel, and the other 4 percent only used two or
three channels.
The team also detected an odd signal near the Seattle-Tacoma
International airport with suspicious properties that were markedly different
from those normally used by network providers.
Those patterns would make sense if a mimicking cell-site
simulator were operating in those areas, the researchers said, but further
investigation would be necessary to definitively reach that conclusion.
"This issue is bigger than one team of researchers,"
said Smith. "We're eager to push this out into the community and find
partners who can crowdsource more data collection and begin to connect the dots
in meaningful ways."
Find the report
online at: https://s3.amazonaws.com/seaglass-web/SeaGlass___PETS_2017.pdf