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Cryo Chamber

Tech comes to the aid of crimefighters

Chicago – December 13, 2005 – Tom Muscarello has the gravelly voice and dry wit that conjures up an image of a hardened police detective. And he certainly seems to spend a great deal of his time contemplating the morbid intricacies of the criminal mind.  "Most criminals are creatures of habit," Muscarello said recently, shuffling through data by light of his computer screen.
"Typically, a thief does not just rob once. He will rob a different person every week of the year without fail. He will hit old ladies every Social Security day. It is his job; his occupation." Muscarello, the man who can reel off a criminal profile like a pro, himself has an unusual occupation: He is, in fact, a cyber sleuth.

A veteran DePaul University computer scientist, Muscarello has been working since the mid-1990s on perfecting an artificial intelligence system that is aimed at helping the Chicago Police Department blaze a bold new trial trail in the way it solves serial robberies, rapes and other violent crimes.

And he just might have hit pay dirt.

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The computer system, called the Classification System for Serial Criminal Patterns (CSSCP), is expected to begin live trials at the Chicago Police Department as soon as early 2006.

Developed by Muscarello with DePaul researcher Kamal Dahbur, CSSCP uses pattern-recognition software that acts like a superhuman brain.

The computer system will be able to cull massive amounts of data, pulling out details of individual crimes, such as the assailant’s age, sex, height, location of the crime, weapons and vehicle used, to create a criminal profile that can be compared with others to link several crimes together.

The goal is to help overcome a thorny problem in police work – the fact that detectives can have difficulty linking serial cases.

The system also will have the potential to search through words or phrases in police reports, such a criminal who wears "green military fatigues" or one who says "give it up" every time he robs a bank.

It can work 24 hours a day without human intervention, sorting through thousands of criminal records per second, revealing patterns in seemingly unrelated crimes that a mere mortal could miss.

Cracking serial crimes has long been especially tough for law enforcement since the crimes can occur over a long stretch of time, a widely dispersed area (involving different police districts within a city or separate police departments) and may even have differing criminal patterns in each incident.

In a recent study using three years of Chicago police robbery data (not active cases), the CSSCP system – which uses a computer network particularly suited for this type of inquiry called a Kohonen neural network – detected at least 10 times as many related crimes as a team of detectives with access to the same data.

Muscarello, who started his career as a federal investigator of Medicare fraud, has garnered national attention from law enforcement since the research project was published last year.

He said he had got calls from law enforcement representatives across the globe, even from as far away as Australia – all from officials searching for security solutions.

Still Muscarello cautioned that the new system could enhance, not replace, solid criminal investigations.

And unlike the depiction of cracking serial crimes popular on network television, it takes more to catch a thief than a few taps on a computer keyboard.

Discovering a criminal’s internal script – whether it was a rapist who usually struck young women at night in a certain location or a bank robber who used a trademark phrase – was the genius of the best detective work, Muscarello said.

"We decided to try to build a system that is intelligent enough to do what the best detectives are already doing," said Muscarello, who explored the techniques of six top Chicago detectives during the initial stages of the study.

"We found in our study that all the cases that were linked would eventually be discovered by detectives but our system may be able to accomplish it faster and tie more crimes to one individual so that the guy can be put away for a long time."

Other computerised crime analysis systems exist, but the CSSCP system is distinctive because it can search for patterns without the help of a computer operator or programmer.

The system can give alerts when patterns of criminal activity emerge and could potentially alert law enforcement to begin an investigation of serial crimes long before they are detected in the normal course of an investigation.

Peter Nelson, head of the department of computer science at the University of Illinois at Chicago, said of Muscarello: "It is interesting work. He has made a nice application of artificial intelligence capabilities by applying it to law enforcement."

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