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FRAUD DETECTION FROM TAXIS’ DRIVING BEHAVIORS
ABSTRACT:
Taxi is a major transportation in the urban area, offering great benefits and convenience to our
daily life. However, one of the major business fraud in taxis is the charging fraud, specifically
overcharging for the actual distance. In practice, it is hard for us to always monitor taxis and
detect such fraud. Due to the Global Positioning System (GPS) embedded in taxis, we can collect
the GPS reports fromthe taxis’ locations, and thus, it is possible for us to retrieve their traces.
Intuitively, we can utilize such information to construct taxis’ trajectories, compute the actual
service distance on the citymap, and detect fraudulent behaviors.However, in practice, due to the
extremely limited reports, notable location errors, complex city map, and road networks, our task
to detect taxi fraud faces significant challenges, and the previous methods cannot work well. In
this paper, we have a critical and interesting observation that fraudulent taxis always play a
secret trick, i.e., modifying the taximeter to a smaller scale. As a result, it not only makes the
service distance larger but also makes the reported taxi speed larger. Fortunately, the speed
information collected from the GPS reports is accurate. Hence, we utilize the speed information
to design a system, which is called the Speed-based Fraud Detection System (SFDS), to model
taxi behaviors and detect taxi fraud. Our method is robust to the location errors and independent
of the map information and road networks. At the same time, the experiments on real-life data
sets confirm that our method has better accuracy, scalability, andmore efficient computation,

2. compared with the previous related methods. Finally, interesting findings of our work and
discussions on potential issues are provided in this paper for future city transportation and human
behavior research.