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Entropy-based privacy against profiling of user mobility
dc.contributor.author | Rodriguez Carrion, Alicia |
dc.contributor.author | Rebollo Monedero, David |
dc.contributor.author | Fornés Guardia, Jordi |
dc.contributor.author | Campo Vazquez, Celeste |
dc.contributor.author | García Rubio, Carlos |
dc.contributor.author | Parra Arnau, Javier |
dc.contributor.author | Das, Sajal K |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria Telemàtica |
dc.date.accessioned | 2016-01-18T13:15:52Z |
dc.date.available | 2016-01-18T13:15:52Z |
dc.date.issued | 2015-06-01 |
dc.identifier.citation | Rodriguez, A., Rebollo-Monedero, D., Fornés, J., Campo, C., García, C., Parra-Arnau, J., Das, S. Entropy-based privacy against profiling of user mobility. "Entropy: international and interdisciplinary journal of entropy and information studies", 01 Juny 2015, vol. 17, núm. 6, p. 3913-3946. |
dc.identifier.issn | 1099-4300 |
dc.identifier.uri | http://hdl.handle.net/2117/81607 |
dc.description.abstract | Location-based services (LBSs) flood mobile phones nowadays, but their use poses an evident privacy risk. The locations accompanying the LBS queries can be exploited by the LBS provider to build the user profile of visited locations, which might disclose sensitive data, such as work or home locations. The classic concept of entropy is widely used to evaluate privacy in these scenarios, where the information is represented as a sequence of independent samples of categorized data. However, since the LBS queries might be sent very frequently, location profiles can be improved by adding temporal dependencies, thus becoming mobility profiles, where location samples are not independent anymore and might disclose the user's mobility patterns. Since the time dimension is factored in, the classic entropy concept falls short of evaluating the real privacy level, which depends also on the time component. Therefore, we propose to extend the entropy-based privacy metric to the use of the entropy rate to evaluate mobility profiles. Then, two perturbative mechanisms are considered to preserve locations and mobility profiles under gradual utility constraints. We further use the proposed privacy metric and compare it to classic ones to evaluate both synthetic and real mobility profiles when the perturbative methods proposed are applied. The results prove the usefulness of the proposed metric for mobility profiles and the need for tailoring the perturbative methods to the features of mobility profiles in order to improve privacy without completely loosing utility. |
dc.format.extent | 34 p. |
dc.language.iso | eng |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject | Àrees temàtiques de la UPC::Enginyeria de la telecomunicació |
dc.subject.lcsh | Location-based services |
dc.subject.other | location-based services (LBSs) |
dc.subject.other | entropy |
dc.subject.other | privacy |
dc.subject.other | perturbative methods |
dc.subject.other | location history |
dc.subject.other | location privacy |
dc.subject.other | information-theory |
dc.subject.other | services |
dc.subject.other | systems |
dc.subject.other | model |
dc.subject.other | web |
dc.subject.other | suppression |
dc.subject.other | obfuscation |
dc.subject.other | protection |
dc.subject.other | patterns |
dc.title | Entropy-based privacy against profiling of user mobility |
dc.type | Article |
dc.subject.lemac | Comunicacions mòbils, Sistemes de |
dc.contributor.group | Universitat Politècnica de Catalunya. ISG - Grup de Seguretat de la Informació |
dc.identifier.doi | 10.3390/e17063913 |
dc.rights.access | Open Access |
local.identifier.drac | 16844818 |
dc.description.version | Postprint (published version) |
local.citation.author | Rodriguez, A.; Rebollo-Monedero, D.; Fornés, J.; Campo, C.; García, C.; Parra-Arnau, J.; Das, S. |
local.citation.publicationName | Entropy: international and interdisciplinary journal of entropy and information studies |
local.citation.volume | 17 |
local.citation.number | 6 |
local.citation.startingPage | 3913 |
local.citation.endingPage | 3946 |
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