Mobile phone use may be a more accurate identifier of individuals than even their own fingerprints, according to research published on the web site of the scientific journal Nature.

Scientists at MIT and the Université catholique de Louvain in Belgium analyzed 15 months of mobility data for 1.5 million individuals who the same mobile carrier. Their analysis, “Unique in the Crowd: the privacy bounds of human mobility” showed that data from just four, randomly chosen “spatio-temporal points” (for example, mobile device pings to carrier antennas) was enough to uniquely identify 95% of the individuals, based on their pattern of movement. Even with just two randomly chosen points, the researchers say they could uniquely characterize around half of the 1.5 million mobile phone users. The research has profound implications for privacy, suggesting that the use of mobile devices makes it impossible to remain anonymous – even without the use of tracking software.

For their research, they studied anonymized carrier data from a “significant and representative part of the population of a small European country.” In the study, the researchers used sample data collected between April 2006 and June 2007. Each time a user interacted with their mobile phone operator network by initiating or receiving a call or a text message, the location of the connecting antenna was recorded, providing both a spatial and temporal data point.

The dataset contained one trace “T” for each user, while each spatio-temporal points contained the region in which the user was and the time of the interaction. The researchers evaluated the uniqueness of each trace given a set of randomly chosen spatio-temporal points.

The data recorded user interactions with his or her phone – around 114 per month scattered across 6,500 mobile antennas. The data collected was highly effective in identifying individuals by their movements. Just four random points, were enough to uniquely characterize 95% of the users studied. ”

Using a complex mathematical and statistical analysis of that data, the researchers discovered that it is possible to find one formula to express what they call the “uniqueness of human mobility”: e 5 a 2 (nh). Roughly stated, the formula says that the more sparse the data becomes (such as among infrequent users, or in areas with fewer cell towers) the less accurate any individual trace is, and the more data points are needed to uniquely identify an individual.

“We show that the uniqueness of human mobility traces is high, thereby emphasizing the importance of the idiosyncrasy of human movements for individual privacy,” the researchers write. “Indeed, this uniqueness means that little outside information is needed to re-identify the trace of a targeted individual even in a sparse, large-scale, and coarse mobility dataset. Given the amount of information that can be inferred from mobility data, as well as the potentially large number of simply anonymized mobility datasets available, this is a growing concern.”

The privacy of mobile data is an increasing concern for privacy advocates and for lawmakers.

Two bills introduced last week in the House and Senate would require law enforcement to obtain a warrant before affixing a GPS device to a vehicle or collecting mobile geolocation data from third party service providers, Wired reported. And, in December, the U.S. Federal Trade Commission announced new guidelines for implementing the Children’s Online Privacy Protection Act (COPPA). Among other things, the changes expand the list of information that cannot be collected from children without parental consent to include photographs, videos and audio recordings of children and geo-location information.

“Unless you get parental consent, you may not track children and use their information to build massive profiles of online behavior,” said FTC Chairman Leibowitz.

The researchers who conducted the work on human mobility say that their work should further inform such legislation. “These results should inform future thinking in the collection, use, and protection of mobility data. Going forward, the importance of location data will only increase and knowing the bounds of individual’s privacy will be crucial in the design of both future policies and information technologies.”