DAS is capable of rapidly blending and analyzing realtime data gathered from roughly 3,000 civic closed-circuit cameras, 911 call recordings, license plate readers, dozens of radiation sensors distributed around the city, as well as historical crime reports. Now the NYPD can now do things like track a vehicle and instantly determine nearly everywhere it’s been for the past few days or weeks; instantly access a suspect’s arrest record, and all the 911 calls related to a particular crime; map criminal history to geospatially and chronologically reveal crime patterns; and verify whether a radiation alarm was triggered by components of a dirty bomb or a harmless medical isotope.
Big blue & Big Data
Last year, IBM raised the Big Data-crime prevention bar by acquiring i2, a UK-based security firm with more than 4,500 customers in scores of countries. Law enforcement agencies and corporate security departments use i2 software to identify fraudulent or improper activity within their logs of operational data.
The i2 Intelligence Analysis package provides law enforcement, defense, government agencies and private sector corporations the ability to harness new intelligence instantly so officials can identify, investigate, predict, prevent and disrupt criminal, terrorist, and fraudulent activities.
Until recently, Big Data was mined mostly for commercial marketing purposes. Amazon, for instance, pushes realtime purchasing suggestions to customers based on music, books or other merchandise that customer has recently browsed or purchased. Data mining will soon evolve to location-based marketing, which targets consumers based on their present location, notifying them on mobile devices of deals in their immediate area.
University researchers in Israel think Big Data mining can be used to predict the location of criminals and terrorists. Like everyone else, criminals (including terrorists) leave digital traces with much of what they do, whether sending or receiving e-mails, making and receiving calls on cell phones, or from credit card transactions. This data can be mined. Engineers at Tel Aviv University are using digital traces to catch criminals and bolster homeland security against the threat of terrorism.
A team of Israeli-based industrial engineers is developing high-powered context-based search algorithms to analyze digital data on-the-fly. The researchers say the new algorithms give investigators the ability to process new pieces of information instantly.
The data used in this work comes from the mobile device and telecom domain. “Even in the age of Big Data, it is extremely hard to discover patterns within the data that bubble up suspicious behaviors,” says Aviv Gruber, lead author of a recent paper describing the Israeli work. Still, patterns found in mobile usage may imply suspicious behavior.
The algorithm works like a computerized Sherlock Holmes. It takes distinct pieces of information like phone calls, e-mails, or credit purchases and reduces them to a set of random variables. The researchers say all of these communications are actually pieces of one long message waiting to be decoded. In a single telephone call, for example, there are several variables to consider—the call recipient, length and caller location. Once all this is known, the algorithm assesses patterns of crime to predict future movements and creates a probability map displaying the possible locations of the person or group of interest.
“The outcome is used in realtime to track the likely location of criminals on-the-move,” Gruber says.
Probable location information may be advantageous in cases where authorities may have just one chance at apprehension. The location of highest probability is the best bet. Zones of lower probability can be ruled out and attention can be focused in increasingly specific areas.
Connecting future dots
Gruber says in the future the Israeli scheme could be used for investigative activities such as pedophile traps. The Internet has given pedophiles a new arena to pursue deviant behavior. Gruber says the Israeli algorithm can be used to automatically track the digital patterns pedophiles leave.
Big Data leads down other roads. Becnel believes soon we’ll develop new ways to connect the dots with the information we already have.
“Imagine the ability to instantly take a security camera photograph from a bank robbery and match it using a facial recognition algorithm to a photograph in an out-of-state motor vehicle database, and then to link that person’s name to a mobile phone from a private-sector marketing database,” Becnel says. An affidavit for a warrant could then be automatically generated, electronically signed and forwarded to a judge. Once granted, investigators could use a code to enter an encrypted portal to the telephone service provider and get GPS coordinates that lead right to the suspect.