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Big Brother Blue seeks biometric anti-terror patents

Tracks eyes, breath, aftershave

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Automatic 'cohort' detection

The filing is based on the idea of identifying members of predetermined "cohorts" - which it defines as "people or objects that share common characteristics or experience." Some objection may be raised that this amounts to profiling. But since the profiling is performed by machines and not humans, the civil-libertarian objections to profiling could be considered to be minimized.

The individual aspects of a person that might be observed are vast. This includes such things as a subject's age, the make and/or model of their vehicle, the color of their hat, breed of their dog, sound of their vehicle's engine, a medical diagnosis, item of clothing, walking, talking, running, what they're eating, or what they buy.

Event-based cohort identifiers include eating, smoking, walking, jogging, walking a dog, carrying bags, carrying a baby, riding a bicycle, how fast a subject is walking - even the "brand of soda purchased by the cohort." Chemical sensors could be used to identify subjects based on such distinguishing characteristics as their perfume, aftershave, scented shampoo, scented lotion, and other smells. Perhaps one cohort might be identified for its infrequent bathing.

Like the previous filing, this one also has elements that could match subjects with a knowledge base of predetermined suspects, such as license plate, face, and voice recognition.

The third patent filing discussed by IW, "Detecting Behavioral Deviations by Measuring Respiratory Patterns in Cohort Groups," has much in common with the first patent - the shifty-eye detector. Unlike the second, it focuses specifically on transportation systems, namely airplanes, trains, and buses, as places where security personnel would want to collar those troublesome "persons of interest."

This patent filing describes video and audio methods of ascertaining respiratory changes by analyzing changes in movement of the rib cage and abdomen to determine such breathing characteristics as regular, deep, shallow, slow, fast, erratic, or abdominal breathing, or breathing from the chest. If irregularities are found, a "risk assessment engine" will judge the level of risk that it associates with those irregularities.

The key to these three IBM patent filings becoming effective methods of apprehending suicidal evildoers, of course, is not only the sensitivity and accuracy of the sensors, but also the quality of the information in the system's knowledge base. And that's the system's Achilles heel.

First, the cohort definitions need to be realistically set and continually monitored. This might be devilishly difficult in practice, especially when needing to be adjusted not only for such environmental factors as weather and time of day, but also for cultural dissimilarities such as the downcast eyes and nervousness of people simply unaccustomed to either flying or the hustle and bustle of urban airports.

In addition, although all three patent filings focus mostly on identifying subjects who stand out in a crowd due to behavioral patterns, there's also the question of the ability of intelligence services to create a thorough, shared, and reasonably up-to-date database of known suspects.

Intelligence agencies are reasonably good at gathering intelligence, but sharing that information in a unified, useful knowledge base has proven more problematic. As Newsweek reported, for example, after the father of Christmas Day's Umar Farouk Abdulmutallab had notified the American embassy in Abuja, Nigeria, of his son's disappearance, the CIA entered him into the National Counterterrorism Center's Terrorist Identities Datamart Environment database - but never told the FBI about him.

In addition, the UK denied Abdulmutallab a visa, but the US authorities never got that information. They never asked. Also, according to Newsweek, the NCTC and CIA's failure to tell the FBI about Abdulmutallab kept him off that agency's Terrorist Screening Center 400,000-name watch list, or the list of 13,000 people who are put through more-thorough airport screening, or the 4,000-name "no fly" list.

The luckless Nigerian crotchbomber is only one example, to be sure, but his slipping through the system is symptomatic of the isolated silos in which security information is stored. Without a centralized knowledge base, no amount of eyeball scanning nor respiratory-pattern monitoring will stop the next determined wannabe aerial assassin. ®

The next step in data security

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