This is the model used for assigning likelihood to a source.  The image on the left shows the method for locating a cellphone on network.  The method is based on signal travel time.  The image on the right shows two observers measuring the arrival time of information. The measurements are combined to generate a likelihood for each potential so...

This is the model used for assigning likelihood to a source.  The image on the left shows the method for locating a cellphone on network.  The method is based on signal travel time.  The image on the right shows two observers measuring the arrival time of information. The measurements are combined to generate a likelihood for each potential source. (Credit: EPFL)

Pinto explained that the triangulation method used for a cell phone user has been applied to networks with nodes under this algorithm. Considering the system to be monitored as an interconnection of lot of nodes, around 15 to 20 percent nodes are to be monitored.  The best connected nodes can be the point of observation and monitoring to achieve the best required results. The algorithm works by fast-tracking the route taken by the information to arrive back at its original source.  A key factor is using the time at which the data is passed from sender to recipient, to help investigators follow the path as directly as possible and eliminate false trails. Pinto's team also tested the algorithm on a known data maze to see if the tool could pinpoint the individuals behind the September 11 attacks on the United States.  They used two of the suspected Al Qaeda members as nodes and tried to predict the leader. Based on the network of messages exchanged, the researchers identified Mohamed Atta, the hijacker of American Airlines Flight 11, as one of the leaders.  Pinto claims that "by reconstructing the message exchange inside the 9/11 terrorist network extracted from publicly released news, our system spit out the names of three potential suspects, one of whom was found to be the mastermind of the attacks."