000K  utf8
1100  $c2023
1500  ger
2050  urn:nbn:de:hbz:465-20230331-145610-7
2051  10.17185/duepublico/78099
3000  Waltereit, Martin
3010  Matković, Viktor
3010  Weis, Torben
3010  Zdankin, Peter
4000  Privatsphäre dreht am Rad$dWas Räder verraten können  [Waltereit, Martin]
4209  In diesem Artikel zeigen wir, wie und wo Daten im Auto abgegriffen werden können und demonstrieren anschließend, wie aus scheinbar harmlosen Daten überraschende Informationen gewonnen werden können.
4209  In this article, we show how driver behavior can be assessed using wheel speeds only. In addition, we show that the vehicle’s location can also be derived from its wheel speeds. Wheel speeds can be read easily from the vehicle’s CAN bus and acceleration information as well as the distances and turns traveled can then be calculated from them.We have developed algorithms that can use this data both to assess driving behavior and to reconstruct the likely traveled route on a map. This has privacy implications, since seemingly harmless data can be used to reveal sensitive information about drivers. For example, if we combine the results of the algorithms with the names and locations of vehicle owners, we can tell from both who was driving the car. Furthermore, it is likely that the location of the vehicle in the evening is the owner’s home. Thus, drivers may unintentionally reveal more information about themselves than they intended when sharing their vehicle data.
4950  https://doi.org/10.17185/duepublico/78099$xR$3Volltext$534
4950  https://nbn-resolving.org/urn:nbn:de:hbz:465-20230331-145610-7$xR$3Volltext$534
4961  https://duepublico2.uni-due.de/receive/duepublico_mods_00078099
5051  000