Skip to main content

2024 | OriginalPaper | Buchkapitel

User Interaction Data in Apps: Comparing Policy Claims to Implementations

verfasst von : Feiyang Tang, Bjarte M. Østvold

Erschienen in: Privacy and Identity Management. Sharing in a Digital World

Verlag: Springer Nature Switzerland

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

As mobile app usage continues to rise, so does the generation of extensive user interaction data, which includes actions such as swiping, zooming, or the time spent on a screen. Apps often collect a large amount of this data and claim to anonymize it, yet concerns arise regarding the adequacy of these measures. In many cases, the so-called anonymized data still has the potential to profile and, in some instances, re-identify individual users. This situation is compounded by a lack of transparency, leading to potential breaches of user trust.
Our work investigates the gap between privacy policies and actual app behavior, focusing on the collection and handling of user interaction data. We analyzed the top 100 apps across diverse categories using static analysis methods to evaluate the alignment between policy claims and implemented data collection techniques. Our findings highlight the lack of transparency in data collection and the associated risk of re-identification, raising concerns about user privacy and trust. This study emphasizes the importance of clear communication and enhanced transparency in privacy practices for mobile app development.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Anhänge
Nur mit Berechtigung zugänglich
Fußnoten
2
The German Google Play Store was selected for its adherence to the GDPR, ensuring that the apps included in the study would have well-constructed privacy policies. https://​play.​google.​com/​store/​apps?​hl=​en_​US &​gl=​DE.
 
Literatur
1.
Zurück zum Zitat Avdiienko, V., et al.: Mining apps for abnormal usage of sensitive data. In: The 37th IEEE International Conference on Software Engineering, vol. 1, pp. 426–436. IEEE (2015) Avdiienko, V., et al.: Mining apps for abnormal usage of sensitive data. In: The 37th IEEE International Conference on Software Engineering, vol. 1, pp. 426–436. IEEE (2015)
2.
Zurück zum Zitat Creţu, A.M., Monti, F., Marrone, S., Dong, X., Bronstein, M., de Montjoye, Y.A.: Interaction data are identifiable even across long periods of time. Nat. Commun. 13(1), 313 (2022)CrossRef Creţu, A.M., Monti, F., Marrone, S., Dong, X., Bronstein, M., de Montjoye, Y.A.: Interaction data are identifiable even across long periods of time. Nat. Commun. 13(1), 313 (2022)CrossRef
3.
Zurück zum Zitat Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: Bert: pre-training of deep bidirectional transformers for language understanding (2019) Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: Bert: pre-training of deep bidirectional transformers for language understanding (2019)
4.
Zurück zum Zitat Enck, W., et al.: TaintDroid: an information-flow tracking system for realtime privacy monitoring on smartphones. ACM Trans. Comput. Syst. (TOCS) 32(2), 1–29 (2014)CrossRef Enck, W., et al.: TaintDroid: an information-flow tracking system for realtime privacy monitoring on smartphones. ACM Trans. Comput. Syst. (TOCS) 32(2), 1–29 (2014)CrossRef
5.
Zurück zum Zitat Grünewald, E., Pallas, F.: TILT: a GDPR-aligned transparency information language and toolkit for practical privacy engineering. In: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, pp. 636–646 (2021) Grünewald, E., Pallas, F.: TILT: a GDPR-aligned transparency information language and toolkit for practical privacy engineering. In: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, pp. 636–646 (2021)
6.
Zurück zum Zitat Leiva, L.A., Arapakis, I., Iordanou, C.: My mouse, my rules: privacy issues of behavioral user profiling via mouse tracking. In: Proceedings of the 2021 Conference on Human Information Interaction and Retrieval, pp. 51–61 (2021) Leiva, L.A., Arapakis, I., Iordanou, C.: My mouse, my rules: privacy issues of behavioral user profiling via mouse tracking. In: Proceedings of the 2021 Conference on Human Information Interaction and Retrieval, pp. 51–61 (2021)
8.
Zurück zum Zitat Qu, Z., Rastogi, V., Zhang, X., Chen, Y., Zhu, T., Chen, Z.: AutoCog: measuring the description-to-permission fidelity in android applications. In: Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, pp. 1354–1365 (2014) Qu, Z., Rastogi, V., Zhang, X., Chen, Y., Zhu, T., Chen, Z.: AutoCog: measuring the description-to-permission fidelity in android applications. In: Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, pp. 1354–1365 (2014)
9.
Zurück zum Zitat Ravichander, A., Black, A.W., Norton, T., Wilson, S., Sadeh, N.: Breaking down walls of text: how can NLP benefit consumer privacy? In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, vol. 1 (2021) Ravichander, A., Black, A.W., Norton, T., Wilson, S., Sadeh, N.: Breaking down walls of text: how can NLP benefit consumer privacy? In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, vol. 1 (2021)
13.
Zurück zum Zitat Tesfay, W.B., Hofmann, P., Nakamura, T., Kiyomoto, S., Serna, J.: PrivacyGuide: towards an implementation of the EU GDPR on internet privacy policy evaluation. In: Proceedings of the Fourth ACM International Workshop on Security and Privacy Analytics, IWSPA 2018, pp. 15–21 (2018) Tesfay, W.B., Hofmann, P., Nakamura, T., Kiyomoto, S., Serna, J.: PrivacyGuide: towards an implementation of the EU GDPR on internet privacy policy evaluation. In: Proceedings of the Fourth ACM International Workshop on Security and Privacy Analytics, IWSPA 2018, pp. 15–21 (2018)
14.
Zurück zum Zitat Zhang, X., Wang, X., Slavin, R., Breaux, T., Niu, J.: How does misconfiguration of analytic services compromise mobile privacy? In: Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering, pp. 1572–1583 (2020) Zhang, X., Wang, X., Slavin, R., Breaux, T., Niu, J.: How does misconfiguration of analytic services compromise mobile privacy? In: Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering, pp. 1572–1583 (2020)
15.
Zurück zum Zitat Zimmeck, S., Goldstein, R., Baraka, D.: PrivacyFlash pro: automating privacy policy generation for mobile apps. In: NDSS (2021) Zimmeck, S., Goldstein, R., Baraka, D.: PrivacyFlash pro: automating privacy policy generation for mobile apps. In: NDSS (2021)
16.
Zurück zum Zitat Zimmeck, S., et al.: MAPS: scaling privacy compliance analysis to a million apps. Proc. Priv. Enhanc. Tech. 2019, 66 (2019) Zimmeck, S., et al.: MAPS: scaling privacy compliance analysis to a million apps. Proc. Priv. Enhanc. Tech. 2019, 66 (2019)
Metadaten
Titel
User Interaction Data in Apps: Comparing Policy Claims to Implementations
verfasst von
Feiyang Tang
Bjarte M. Østvold
Copyright-Jahr
2024
DOI
https://doi.org/10.1007/978-3-031-57978-3_5