Government Computer News has an excellent story this week on the problems of watch lists and the challenges associated with migrating to biometric-based identification technologies. From the article:
â€œEvery couple of years, this idea of the â€˜biometric magic bulletâ€™ resurfaces,â€ said Jack Hermansen, chief executive officer of Language Analysis Systems Inc. of Herndon, Va., in an e-mail response.
â€œUsually, it is followed by the sobering realization that identifying individuals is a daunting task requiring an operation dedicated to training, procedures and contingency plans that overwhelm those attempting to envision how to implement such an operation.â€
Hermansen said biometrics gives the intelligence community a false hope that biometric identifiers could solve the problems of finding terrorists.
The article also notes several key drawbacks of biometric technologies, including:
- Biometrics are more difficult to collect than name records. Intelligence collection typically provides name-based information, not biometrics, and it’s difficult to collate the two.
- Biometrics can’t prevent the entry of people you don’t know about (as is the case with name-based watch lists).
These challenges are real, but that’s no reason accept the status quo of named-based watch lists, which have proven to be very flawed in practice, most notably with the aviation no-fly list. The best long-term solution is one that integrates biometric and named-based information, and can appropriately interrelate them in specific applications, consistent with privacy laws and standards.
The article also reveals the existence of a government database for which there are no Google hits as of the date of posting:
One top-secret database the NCTC uses is called the Terrorist Identities Determinant Environment, known as TIDE. It provides a snapshot of everything known about individual terrorists.
A special advantage of TIDE, in contrast to other classified databases, is that it is classified down to the field level, [FBI special agent Michael] Resnick said.
As a result, users can filter out secret or top-secret data fields relating to a person when they distribute a record at the â€œFor Official Use Onlyâ€ level, which is equivalent to the â€œlaw enforcement confidentialâ€ classification level used by state and local agencies.
The ability to segregrate field data should be the norm in intelligence databases. Otherwise, the classification-related challenges of intelligence-sharing with state and local officials will persist.