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FBI Ramps Up Next Generation ID Roll-Out
EFF.org - 10/24/2011
NextGov.com is reporting that the FBI will begin rolling out its Next Generation Identification (NGI) facial
recognition service as early as this January.  Once NGI is fully deployed and once each of its approximately
100 million records also includes photographs, it will become trivially easy to find and track Americans.

As we detailed in an
earlier post, NGI expands the FBI’s IAFIS criminal and civil fingerprint database to include
multimodal biometric identifiers such as iris scans, palm prints, photos, and voice data. The Bureau is
planning to introduce each of these capabilities in
phases (pdf, p.4) over the next two and a half years,
starting with facial recognition in four states—Michigan, Washington, Florida, and North Carolina—this winter.

Why Should We Be Worried?

Despite the
FBI’s claims to the contrary, NGI will result in a massive expansion of government data collection
for both criminal and noncriminal purposes. IAFIS is already the largest biometric database in the world—it
includes
70 million subjects in the criminal master file and more than 31 million civil fingerprints. Even if there
are duplicate entries or some overlap between civil and criminal records, the combined number of records
covers close to
1/3 the population of the United States. When NGI allows photographs and other biometric
identifiers to be linked to each of those records, all easily searchable through sophisticated search tools, it will
have an unprecedented impact on Americans' privacy interests.

Although IAFIS currently includes some photos, they have so far been limited specifically to mug shots linked
to individual criminal records. However, according to a
2008 Privacy Impact Assessment for NGI’s Interstate
Photo System, NGI will allow unlimited submission of photos and types of photos. Photos won’t be limited to
frontal mug shots but may be taken from other angles and may include close-ups of scars, marks and tattoos.
NGI will allow all levels of law enforcement, correctional facilities, and criminal justice agencies at the local,
state, federal and even international level to submit and access photos, and will allow them to submit photos
in bulk. Once the photos are in the database, they can be found easily using facial recognition and text-based
searches for distinguishing characteristics.

The new NGI database will also allow law enforcement to submit public and private security camera photos
that may or may not be linked to a specific person’s record. This means that anyone could end up in the
database—even if they’re not involved in a crime— by just happening to be in the wrong place at the wrong
time or by, for example, engaging in political protest activities in areas like
Lower Manhattan that are rife with
security cameras.

The biggest change in NGI will be the addition of non-criminal photos. If you apply for any type of job that
requires fingerprinting or a background check, your potential employer could require you to submit a photo to
the FBI. And, as the 2008 PIA notes, “expanding the photo capability within the NGI [Interstate Photo System]
will also expand the searchable photos that are currently maintained in the repository.” Although noncriminal
information is ostensibly kept separate from criminal, all the data will be in the NGI system, and presumably it
would not be difficult to search all the data at once. The FBI does not say whether there is any way to ever
have your photo removed from the database.

Technological Advancements Support Even Greater Tracking Capabilities

According to an FBI
presentation on facial recognition and identification initiatives (pdf, p.5) at a biometrics
conference last year, one of the FBI’s goals for NGI is to be able to track people as they move from one
location to another. Recent advancements in camera and surveillance technology over the last few years will
support this goal. For example, in a
National Institute of Justice presentation (pdf, p.17) at the same 2010
biometrics conference, the agency discussed a new 3D binocular and camera that allows realtime facial
acquisition and recognition at 1000 meters. The tool wirelessly transmits images to a server, which searches
them against a photo database and identifies the photo's subject. As of 2010, these binoculars were already
in field-testing with the Los Angeles Sheriff’s Department. Presumably, the backend technology for these
binoculars could be incorporated into other tools like
body-mounted video cameras or the MORIS (Mobile
Offender Recognition and Information System) iPhone add-on that some police officers are already using.
Private security cameras and the cameras already in use by police departments have also advanced. They
are more capable of capturing the details and facial features necessary to support facial recognition-based
searches, and the software supporting them allows photo manipulation that can improve the chances of
panorama photo of lots of megapixel images stitched together (like those taken by security cameras), allows
anyone viewing the photo to drill down to see and tag faces from even the largest crowd photos. And image
enhancement software, already in use by some local law enforcement, can adjust photos "
taken in the wild"
(pdf, p.10) so they work better with facial recognition searches.

Cameras are also being incorporated into more and more devices that are capable of tracking Americans and
can provide that data to law enforcement. For example, one of the largest manufacturers of highway toll
collection systems recently
filed a patent application to incorporate cameras into the transponder that sits on
the dashboard in your car. This manufacturer's transponders are already in 22 million cars, and law
enforcement
already uses this data to track subjects. While a patent application does not mean the company
is currently manufacturing or trying to sell the devices, it certainly shows they're interested.

Data Sharing and Publicly-Available Information Will Supplement the FBI's Database

Data sharing between the FBI and other government agencies and the repurposing of photographs taken for
noncriminal activities will further support the FBI's ability to track people as they move from one location to
another. At least 31 states have already started using some form of facial recognition with their
DMV photos,
generally to stop fraud and identity theft, and the Bureau has already
worked with North Carolina, one of the
four states in the NGI pilot program, to track criminals using the state’s DMV records. The Department of
Justice
came under fire earlier this year for populating the NGI database with non-criminal data from the
Department of Homeland Security through the
Secure Communities program and could be considering doing
the same with facial-recognition ready DMV photos. Even if the FBI does not incorporate DMV photos en
masse directly into NGI, the fact that most states allow law enforcement access to these records combined
with the new expansion of the FBI's own photo database, may make this point moot.

Commercial sites like Facebook that collect data and include facial recognition capabilities could also become
a honeypot for the government. The FBI’s
2008 Privacy Impact Assessment stated that the NGI/IAFIS photo
database does not collect information from “commercial data aggregators,” however, the PIA acknowledges
this information could be collected and added to the database by other NGI users like state and local law
enforcement agencies. Further, the FBI's
2010 facial recognition presentation (pdf, p.5) notes another goal of
NGI is to “Identify[ ] subjects in public datasets.” If Facebook falls into the FBI’s category of a public dataset, it
may have almost as much revealing information as a commercial data aggregator.

The Problem of False Positives in Large Data Sets

As the FBI's facial recognition database gets larger and as more agencies at every level of government rely
on facial recognition to identify people, false positives—someone being misidentified as the perpetrator of a
crime—will become a big problem. As
this 2009 report (pdf) by Helen Nissenbaum and Lucas Introna notes,
facial recognition

performs rather poorly in more complex attempts to identify individuals who do not voluntarily self-identify . . .
Specifically, the “face in the crowd” scenario, in which a face is picked out from a crowd in an uncontrolled
environment, is unlikely to become an operational reality for the foreseeable future.

(p. 3). The researchers go on to note that this is not necessarily because the technology is not good enough
but because "there is not enough information (or variation) in faces to discriminate over large populations." (p.
47) In layman's terms, this means that because so many people in the world look alike, the probability that any
facial recognition system will regularly misidentify people becomes much higher as the data set (the
population of people you are checking against) gets larger. German Federal Data Protection Commissioner
Peter Schaar has noted false positives in facial recognition systems pose a large problem for democratic
societies. "[I]n the event of a genuine hunt, [they] render innocent people suspects for a time, create a need
for justification on their part and make further checks by the authorities unavoidable.”(p.37)

It appears it will take a few years for the FBI to bring NGI up to its full potential. In the meantime, we will
continue to monitor this troubling trend.

Attached Documents
FBI 2010 Facial Recognition Initiatives Presentation
National Institute of Justice 2010 Biometrics Presentation
FBI 2010 NGI Overview Presentation