Lone Wolf Terrorism (26 page)

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Authors: Jeffrey D. Simon

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The widespread use of CCTV and other video sources can also serve as a deterrent to the lone wolf who is planning an attack. The more he or she knows that there are cameras watching, the less likely it may be that he or she will strike in that area. That does not mean, of course, that lone wolves and other terrorists will not adapt and strike at other targets or try evasive measures to avoid the cameras, but CCTV is still at least one more measure that can be taken to try to reduce the probability of a successful lone wolf terrorist attack.

The Lure of Biometrics

As promising as CCTV is for preventing lone wolf terrorism, biometrics may hold even greater hope for stripping away the anonymity of the lone wolf. Biometrics are the measurable physiological and behavioral characteristics that can be used to identify people. It is based on the principle that certain characteristics of the human body and certain behavioral patterns are unique to an individual. The history of biometrics can be traced back to fourteenth-century China, where merchants used fingerprints as a form of signature to settle business transactions and parents may have used both fingerprints and footprints as a way to differentiate children from one another.
32
In the late-nineteenth century, an anthropologist, Alphonse Bertillon, who was working as a record clerk in a Paris police station, developed
a method for identifying criminals by taking precise measurements of their faces and bodies. This included, among other measurements, the length of the head, middle finger, and left foot. He also took frontal and profile photographs of suspects (i.e., the “mug shot”).
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The Bertillon System, as it became known, was based on the science of anthropometrics and was soon used throughout the world. However, it was eventually replaced by fingerprinting, which proved to be a more accurate measure of identification.
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In 1924, a young J. Edgar Hoover, who had recently been named the director of the Bureau of Investigation, the forerunner of the FBI, created an identification division and introduced one of the first systematic uses of fingerprints to track down and identify criminals throughout the United States.
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For most of the remainder of the century, fingerprints continued to be the main biometrics used by the FBI and other law-enforcement and government agencies around the world.

But a revolution in biometrics was in the making by the dawn of the twenty-first century. Advances in computer technology had allowed for the testing of various biometrics during the latter part of the twentieth century, but it was a combination of domestic and international events affecting the United States that propelled biometrics into the forefront of the public's consciousness. The first event was the 9/11 attacks on the homeland, which made security against terrorism a top priority for the nation. The US Visitor and Immigrant Status Indicator Technology (US-VISIT) program was initiated in 2004, using face recognition to screen photos of visa applicants in order to identify individuals who were previously denied, had their visas revoked, or were seeking multiple visas under different names.
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US-VISIT, which is part of the Department of Homeland Security, operates the Automated Biometric Identification System, known by the acronym IDENT. This system maintains fingerprints, photographs, and biographic information on more than 126 million people and conducts approximately 250,000 biometric transactions each day, averaging ten seconds or less for each transaction.
37

The wars in Afghanistan and Iraq also made biometrics a top
priority for the US government, which led the Department of Defense to deploy its own biometric system in 2004, also known as the Automated Biometric Identification System (ABIS). This system utilized palmprint, face, and iris matching to support US military operations overseas, with data taken from enemy combatants, captured insurgents, and other individuals.
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The FBI, meanwhile, had established the Integrated Automated Fingerprint Identification System (IAFIS) in 1999, facilitating the exchange of information regarding fingerprints of criminals, suspected terrorists, and others.
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By 2011, the first phase of the FBI's Next Generation Identification (NGI) system was being introduced, which improved the accuracy of fingerprint searches and added enhanced processing speed, automation, and searching capabilities.
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“We're finally in a position where we get reliable information, biometrically based fingerprints in a timely fashion that's accessible to the guys that need it,” said William M. Casey, the program manager for the FBI's Biometric Center of Excellence, Criminal Justice Information Services (CJIS) Division, which is located in Clarksburg, West Virginia. “Getting the right information to the right people in a timely fashion is, I think, the whole thing about how information can be useful.”
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An ongoing goal of the US government is to attain interoperability among all the major biometric systems.

The advances that have been taking place in biometrics are truly breathtaking. Fingerprinting, which was the standard-bearer of biometrics for so long, has already been joined, as noted above, by several other physiological biometrics. These include, among others, face recognition, which measures and analyzes the overall structure, shape, and proportions of the face; iris recognition, which scans different points of the iris (the colored elastic and connective tissue that surrounds the pupil); retina scanning, which focuses on the blood vessels at the back of the eye; palmprint matching, which, like fingerprinting, analyzes friction ridge impressions; hand and finger geometry, which measures and analyzes the overall structure, shape, and proportions of the hand; and DNA analysis, which involves taking
and examining samples of DNA from an individual's blood, saliva, hair, and so on. Ear and tattoo recognition are additional physiological biometrics that are emerging.

In addition to physiological biometrics, there are several behavioral biometrics that governments, militaries, law-enforcement agencies, and businesses are using. These include the following: voice recognition, signature recognition (which measures and analyzes the physical activity of signing, such as the stroke order, the pressure applied, and the speed), keystroke analysis (which measures the rhythm, time, and way an individual types on a keyboard), and gait analysis (which examines the way an individual walks).
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The FBI's NGI system, in addition to dealing with fingerprints, is also examining these new biometrics. “NGI is looking out ten years as to what other modality biometrics are out there,” said Stephen G. Fischer Jr., the unit chief for the FBI's CJIS Division's Multimedia Productions Group. “We're kind of still in the beginning stages of that.”
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There are two basic ways that biometrics are currently used. One is for identification of an individual, while the other is for verification. Identification concerns determining who a person is. This involves finding a match for an individual's biometric data in a database containing records of people and their characteristics. For example, there could be a match of fingerprints or of a face, iris, or retina. This is also known as “one-to-many” matching, since one person is being matched against an entire database. (Additionally, there could be searches for multiple characteristics, which are known as “multimodal” biometrics and can improve the accuracy of the match.) Verification concerns determining if a person is actually who he says he is. This involves comparing an individual's biometric data to the previously recorded data for that person to ensure that it is the same person. Verification is mainly used for access control to buildings, computer systems, and other entities or systems that require verifying a particular individual. Verification is also referred to as “one-to-one” matching, since the person is being matched to only one other person in the database.
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The obvious drawback to using biometrics to prevent lone wolf terrorism, or any type of terrorism for that matter, is that a person has to be “enrolled” in a biometric system for it to be effective. In other words, there has to be a database that contains that individual's physiological or behavioral biometric characteristics. Otherwise, an individual who plans to travel to the United States to commit a terrorist attack will not raise a red flag when his or her biometric data is taken at some point before entry into the United States. As noted above, the long wars in Iraq and Afghanistan have yielded biometric data on many of these individuals, providing a safeguard against their trying to enter the United States under false identities.

An example of how biometrics could be used to prevent a lone wolf from emigrating to the United States to carry out an attack can be seen in the case of Mohammed Merah, a Frenchman of Algerian descent, who, in March 2012, launched three separate terrorist attacks in just over a week in France, killing four men and three children before he himself was killed in a shootout with French police. Merah claimed to be a member of al Qaeda, but no evidence supported that claim. (While he may have had some ties to al Qaeda and been under the influence of his brother, who was a radical Islamist, he basically acted alone in the attacks). He had traveled to Afghanistan and Pakistan and, at one point, was arrested by the Afghan police, who turned him over to the US military, which most likely took his fingerprints, iris scan, and facial image before transferring him to the French authorities. Merah was also put on the FBI's “no-fly” list, which contains the names of individuals who are not allowed to fly into, around, or out of the United States because they are deemed to pose a terrorist risk.
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Even if Merah wanted to travel to America under a different name with a false passport, his biometric data would have alerted US authorities to his true identity.

In another case, an individual who had overstayed his visa in the United States attempted to gain employment at a nuclear power plant using a false document under a false identity to prove his legal status to reside and work in this country. The US-VISIT program,
however, was able to use biometrics to determine his true identity, and the man was subsequently arrested.
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While not a terrorist, the case nevertheless illustrates how the true identity of those who seek to work in critical infrastructure areas such as nuclear power plants can be determined through biometrics.

The homegrown lone wolf, however, poses many more problems regarding discovery than the foreign-based terrorist. If the homegrown terrorist has not done anything to put himself or herself on anybody's radar or into any biometric database, then it will be difficult to identify that person as a potential terrorist, criminal, or someone using a false identity. And even if a person is in a biometric database and is found to have lied about his or her identity or is discovered to have been linked to a previous crime, it does not mean that the individual was planning a terrorist attack.

That is why the real promise of biometrics as a tool for preventing lone wolf terrorism lies in the second-generation biometrics that are currently being researched and tested. These biometrics go beyond the first-generation biometrics, such as fingerprints, iris scanning, facial images, and so forth, which are used to identify or verify who a person is. The second-generation biometrics are instead now aimed at predicting
what
a person is likely to do, similar to the goal of the “smart CCTV” cameras. The new biometrics basically try to detect suspicious behavior and gauge an individual's motivation and intent.
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There are several programs underway to develop and test sensors that can predict future human actions. One of the biggest is the Future Attribute Screening Technology (FAST) project being developed by the US Department of Homeland Security (DHS). The project is based on the “theory of malintent.” Malintent is the intent to cause harm. The idea is that someone with malintent “may act strangely, show mannerisms out of the norm, or experience extreme physiological reactions based on the extent, time, and consequences of the event.”
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Although the project is mainly focused on improving airport security, it may be applied to other venues as well, such as
at border crossings or at large public gatherings, including sporting events and conventions.
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Among the types of sensors that are being developed to detect malintent are the following: a remote cardiovascular and respiratory sensor to measure heart rate and respiration; a remote eye tracker that uses a camera and processing software to track the position and gaze of the eyes and measure pupil diameter; thermal cameras that provide detailed information about changes in thermal properties of facial skin and help assess electrodermal activity and measure respiration and eye movements; a high-resolution video camera that, aside from generating highly detailed images of the face and body for image analysis to determine facial features and expressions and body movements, also has an audio system for analyzing human voice for pitch change; and other sensors for pheromones detection.
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The FAST system, and similar ones such as the European Union–funded Automatic Detection of Abnormal Behavior and Threats in Crowded Spaces (ADABTS), has been compared to the movie
Minority Report
, where Tom Cruise enlists the help of “precog mutants” to see into the future to determine who is going to commit a crime. The authorities then make a “pre-crime” arrest. But instead of using “precogs,” FAST, ADABTS, and other systems are automated.
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If all this sounds futuristic, it is. The FAST program is still in the early stages of development, and the DHS has stated that they have no plans yet to deploy the technology publicly.
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That has not stopped its many critics from voicing their opposition to the idea that one can predict hostile behavior by using remote sensors. “I believe that the premise of this approach—that there is an identifiable physiological signature uniquely associated with malicious intent—is mistaken,” said Steven Aftergood, a senior research analyst with the Federation of American Scientists. “To my knowledge, it has not been demonstrated. Without it, the whole thing seems like a charade.”
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Another critic, Stephen Fienberg, a professor of statistics and social science at Carnegie Mellon University, notes that “it's mainly baloney. What evidence do we have coming out of physiology, psychology, or brain
imaging that we can do any of this? Almost all of what I've seen and heard is hype.”
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