@proceedings{nokey,

title = {Mobility Data Anonymization – A Literature Review and an Industry-Driven Survey},

author = {Maximilian Walter and Wasilij Beskorovajnov and Fridtjof Lieberwirth and Jan Sürmeli and Pascal Zwick and Robert Heinrich},

doi = {10.5445/IR/1000162080},

year  = {2023},

date = {2023-09-11},

urldate = {2023-09-11},

abstract = {The transformation of mobility is on the cusp of a significant shift,driven by data-centric technologies in both individual and public transport. However, this data often contains sensitive private data, which can be used, for instance, for tracking a person. Hence, anonymization of this mobility data is important. In this report, we present a structured literature review about anonymization methods in the mobility domain. Based on our findings, we present different anonymization methods and discuss their application scenarios and characteristics for public transport and individual one. Additionally, an industry-driven survey on anonymization methods within public transport, particularly centered around video technologies, is presented. This industry-driven survey, conducted within a video surveillance solutions company, highlights current trends and underscores the necessity for continued research. This report was created within the ANYMOS project.},

howpublished = {Karlsruhe Reports in Informatics; 2023,3},

keywords = {},

pubstate = {published},

tppubtype = {proceedings}

}