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of arrest to the card s arrival at CJIS for identification The backlog grew to a peak of nearly 3 million cards In essence, the criminal master file had grown far too large and the demand for civil and criminal searches had increased such that the criminal master file could not be easily searched As 3 explains, technology, incorporating computer and biometric advances, came to the rescue For many years, processing fingerprint cards was largely a manual, labor-intensive process In 1963, the FBI began a partnership with the then National Bureau of Standards to begin automation of the fingerprint search process Studies to establish the feasibility of minutiae matching were begun and development contracts awarded for prototype fingerprint reading hardware Throughout the 1960s and 1970s, analyses, studies, prototyping, and engineering development continued with initial automated processing introduced by the FBI in October 1979 In August 1995, the Boston Police Department and the FBI began to experiment with electronic submission of fingerprints and return of criminal history records Other states, including California, South Carolina, and West Virginia, soon established similar pilot programs, thus laying the foundation for a comprehensive IAFIS approach IAFIS represents a significant technological breakthrough for public safety because it can compare the submitted fingerprint images against its huge database of fingerprints and respond with an average search time of 68 minutes The IAFIS program mission statement summarizes this capability by explaining that its mission is to provide complete and accurate responses within two hours to criminal fingerprint search requests and twenty-four [hours] for civil fingerprint search requests when such requests are submitted electronically to the FBI The response produces a criminal history of the person, if one exists, which includes a record of the person s serious offenses on file at the federal level Even if the person fingerprinted provides a false name or alias identification documents, IAFIS will make a positive identification about 99 percent of the time by matching fingerprints, which a person cannot so easily change or alter In practical terms, IAFIS s accurate fingerprint-based identification, combined with its quick response time, means that law enforcement holding a suspect is more likely to know the suspect s true identity and criminal status while he or she is still in custody Prior to IAFIS, paper-based fingerprint searches took too long to complete, meaning that law enforcement all too often received a suspect s identity and criminal history information too late For example, pre-IAFIS, police in Richmond, Virginia, arrest John Doe for burglary Doe is booked and his fingerprints are taken, but because of the 143-day backlog, he appears before a magistrate and posts bail before the fingerprint search is completed Only after Doe absconds do police learn that Doe s fingerprints matched the FBI s holdings for career criminal Richard Roe, wanted on murder charges in Idaho With IAFIS, police learn this vital information within two hours of Doe/Roe s arrest for burglary This process is sometimes referred to as a National Agency Check (NAC) CJIS runs the fingerprint record it receives against IAFIS, its integrated, automated.

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Figure 5-2

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On the ribbon bar is a Refresh button that will query the server to find existing data sources, dashboards, KPIs, and so forth Clicking this button will populate the lists that show up in the middle area, called the Workspace area, where the Server and Workspace tabs are located If this is a new server, of course, nothing will show up in the lists Once there are existing objects published to the server, they will show up in the lists only after the Refresh button is clicked

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While an in-depth discussion of the technical operation of IAFIS is beyond the scope of this book, a basic explanation of how IAFIS searches a 400 million fingerprint database with an average search time of 68 minutes might be of interest It is no easy task to search within minutes the fingerprints of one person against a database representing the fingerprints of 40 million individuals to determine whether there is a match This type of search is known as identification or a one-to-many (1:N) search IAFIS tries to resolve this dilemma by subdividing the database (the criminal master file) to be searched so that only the relevant portion of it must be searched This subdivision is done by using a multi-stage classification process of binning Binning is the selection of potential matches based on information intrinsic to the fingerprint that can be readily detected Specifically, each fingerprint comprises various types of ridge patterns, traditionally classified according to the Henry system, named for Sir Edward R Henry IAFIS uses the classifications of left loop, right loop, arch (to include tented arch), and whorl The ten fingerprints of a person can then be classified accordingly Ensemble matching is then performed With ensemble matching, a set of independent samples (fingerprints taken from a person s 10 fingers) is collected from each person being identified and this set of 10 is binned as a group, and then matched against corresponding sets in the database The net effect in many cases is to further reduce the number of potential matches to be considered This also reduces the probability of a false match (also known as a false positive), and reduces the processing time required to search the data set, thereby improving system responsiveness For example, with IAFIS, binning produces a filter rate that can reduce 40 million records to less than 1 million records for most searches6.

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