A Survey on Fingerprinting Technologies for Smartphones Based on Embedded Transducers

Abstract

Smartphones are a vital technology, they improve our social interactions, provide us a great deal of information and bring forth the means to control various emerging technologies, like the numerous IoT devices that are controlled via smartphone apps. In this context, smartphone fingerprinting from sensor characteristics is a topic of high interest not only due to privacy implications or potential use in forensics investigations, but also because of various applications in device authentication. In this work we review existing approaches for smartphone fingerprinting based on internal components, focusing mostly on camera sensors, microphones, loudspeakers and accelerometers. Other sensors, i.e., gyroscopes and magnetometers, are also accounted, but they correspond to a smaller body of works. The output of these transducers, which convert one type of energy into another, e.g., mechanical into electrical, leaks through various channels such as mobile apps and cloud services, while there is little user awareness on the privacy risks. Needless to say, miniature physical imperfections from the manufacturing process make each such transducer unique. One of the main intentions of our study is to rank these sensors according to the accuracy they provide in identifying smartphones and to give a clear overview on the amount of research that each of these components triggered so far. We review the features which can be extracted from each type of data and the classification algorithms that have been used. Last but not least, we also point out publicly available datasets which can serve for future investigations.