Prosecutorial misconduct and police adoption of face recognition technology are dangerous, and the ACLU has been pushing to halt both. Until that happens, prosecutors must give defendants full access to information about the algorithm used against them in places where face recognition technology has already been deployed. This includes the underlying model, training data, computer code, explanatory documentation, and any other results from which the final, reported result was chosen. Any validation studies should also be available as well as the opportunity to question the people who use and created the system.
One of the biggest shortcomings of traditional user ID and password logins is that passwords can be easily compromised, potentially costing organizations millions of dollars. Brute-force attacks are also a real threat, as bad actors can use automated password cracking tools to guess various combinations of usernames and passwords until they find the right sequence. Although locking an account after a certain number of incorrect login attempts can help protect an organization, hackers have numerous other methods for system access. This is why multifactor authentication is so important, as it can help reduce security risks.
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The way data is recorded differs among fingerprint and facial recognition technology. Fingerprint recognition involves physical touch, whereas facial recognition is touchless, involving high safety and anti-pandemic reasonable precautions.
There are certain factors to consider when hunting for competent fingerprint recognition or facial recognition technology. To begin, ensure that the product you select is trustworthy and has a strong service record. Next, make certain the system is simple to use and fulfills your demands. Finally, ensure that the company provides exceptional customer support in the event that you have any concerns or issues.
I would then build a biometric outline of everyone's face from these pictures. With recent advances in facial recognition software, I would then be able to match any image, found anywhere, of those 2.5 billion people to their identity with a high degree of certainty.
Now, with a data center, supercomputer, 2.5 billion facial profiles, facial recognition software, access to almost every smartphone on the planet, access to every internet-connected surveillance camera, and additional surveillance cameras in the sky and on the ground, my God's Eye would be complete and I would still have change left from my $50 billion.
For one thing it's very hard to differentiate between a face of a chimp and a face of a human. These facial recognition techniques work on the assumption that what is in front of them is actually a real human face. Hence in many of them you can bypass the security by placing a high definition photograph in front of the camera.
We are not yet at the point where we can take pictures of people on the street with our smartphones, identify them, and gain access to information about them. However, this reality may not be too far off and we can only imagine what that will do to our interactions, relationships, and how we conduct our lives. For one thing, this will exacerbate the economic and social divide between those who have access to the technology and those who do not. It will also make surveillance and facial recognition seem ordinary. If the use of this technology is normalized, no one will question it and put constraints around what it can be used for and by whom.
Of all biometric technologies, facial recognition most closely mimics how people identify others: by scrutinizing their face. What is an effortless skill in humans has proven immensely difficult and expensive to replicate in machines. But through a convergence of factors in the past few years, facial recognition has become a viable and increasingly accurate technology.
Digital images have become pervasive, through the proliferation of surveillance cameras, camera-equipped smart phones, and inexpensive high-quality digital cameras. Cheap data storage has led to massive online databases of images of identified individuals, such as licensed drivers, passport holders, employee IDs and convicted criminals. Individuals have embraced online photo sharing and photo tagging on platforms such as Facebook, Instagram, Picasa and Flickr. There have also been significant improvements in facial recognition technology, including advancements in analyzing images and extracting data.
Some security applications of facial recognition technology are undoubtedly beneficial, such as authentication of employees allowed to access nuclear plant facilities, for example. At the same time, facial recognition holds implications for privacy and for societal values in general. Some commentatorsFootnote 1 have even concluded that facial recognition technology could spell the end of anonymity.
In 2010, the U.S National Institute of Standards and Technology testedFootnote 2 various facial recognition systems and found that the best algorithm correctly recognized 92 percent of unknown individuals from a database of 1.6 million criminal records.
A 2011 studyFootnote 3 from Carnegie Mellon University showed that facial recognition technology could be used to identify individuals in the real world from personal online images. Researchers were able to identify strangers and find their personal information using facial recognition software and social media profiles.
The day after the June 2011 hockey riot in Vancouver, the Insurance Corporation of British Columbia (ICBC) offered to help police identify rioters by running facial recognition software on images from the riot and comparing suspects to images in its drivers licence database. The BC Privacy Commissioner ruled that while ICBC can use the technology to detect and prevent driver's licence fraud, the corporation cannot use its database to help police identify riot suspects because this is a different purpose, of which customers were not notifiedFootnote 7.
In Australia, facial recognition is used in conjunction with fingerprinting at borders to identify fraudulent visa applicantsFootnote 11. Australian immigration officials are also using facial recognition in efforts to address visa fraud and illegal workersFootnote 12. This is part of a national campaign to crack down on identity theft and the use of false identities to facilitate crime.
Facial recognition is used in many Canadian casinos in order to detect known criminals and cheats. Also, as part of voluntary self-exclusion programs in several provinces, including Ontario and British Columbia, facial recognition is used in province-run casinos to keep out individuals who have asked casinos to deny them entry in order to stave off gambling addictions, for example.
Cameras in Ontario casinos run facial recognition software on individuals entering the building and compare images with a database of self-identified gamblers who ask to be placed on a no-gambling list. The program is entirely voluntary and works to recognize only individuals who have provided explicit consent. The Ontario Privacy Commissioner approvedFootnote 14 the program because of its privacy-enhancing design. Images which do not have a match with the gambler database are discarded. Also, the gambler database is secured using biometric encryption, whereby information specific to an individual can only be unlocked when that individual is physically present.
Facial recognition technology is increasingly a part of security measures at large sporting events. At the China Olympics in 2008, all those entering the main stadium underwent identity checks at facial recognition checkpointsFootnote 20. Facial recognition was also used in London for the 2012 Olympic Games to keep watch for identified suspects. At the 2014 Soccer World Cup, Brazilian police planFootnote 21 to use style glasses with facial recognition capabilities to scan the crowd and identify potential troublemakers.
To date, the use of facial recognition technology by Canadian federal government departments and agencies has been limited. At the time of publishing this research report, the OPC has not received any complaints under the Privacy Act involving facial recognition. However, we have addressed the issue in the context of the Privacy Impact Assessment (PIA) process.
As facial recognition technology is further developed, opportunities to incorporate it into federal surveillance programs could increase. For example facial recognition technology could be added to existing video surveillance systems, such as those used by the RCMP on Parliament Hill, the Canadian Air Transport Security Authority in airports, and by the Canadian Border Services Agency at all border crossings. The OPC continues to encourage federal institutions to consult with us about their plans to use facial recognition technologies in the future.
Generally speaking, any federal institution collecting personal information can only do so if the information relates directly to an operating program or activity of the institution. The OPC would encourage any institution contemplating the use of facial recognition to ensure that it can clearly justify the prospective privacy intrusion. To guide this analysis, institutions can use the following four-part test:
Another privacy challenge is the storage of facial image information in databases and the need for strict access controls. Of particular concern in the sharing of information with other agencies and governments, including law enforcement, with the risk of government tracking and surveillance without appropriate authorization, safeguards or oversight. Moreover, federal government departments and agencies should implement and respect strict retention policies and dispose of the information once it is no longer required.
On mobile devices, the challenge has been to have a high-quality camera and a powerful processor capable of carrying out the complex algorithms needed for facial recognition while limiting power consumption. With technological advancements, these issues are being solved. 2ff7e9595c
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