%0 Conference Proceedings
%T Privacy-Preserving IDS for In-Vehicle Networks with Local Differential Privacy
%+ Fraunhofer Institute for Secure Information Technology [Darmstadt] (Fraunhofer SIT)
%+ Technische Universität Darmstadt - Technical University of Darmstadt (TU Darmstadt)
%A Kreutzer, Michael
%A Simo, Hervais
%A Franke, Peter
%Z Part 2: Selected Student Papers
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 15th IFIP International Summer School on Privacy and Identity Management (Privacy and Identity)
%C Maribor, Slovenia
%Y Michael Friedewald
%Y Stefan Schiffner
%Y Stephan Krenn
%I Springer International Publishing
%3 Privacy and Identity Management
%V AICT-619
%P 58-77
%8 2020-09-21
%D 2020
%R 10.1007/978-3-030-72465-8_4
%K In-Vehicle Networks
%K Privacy
%K Data protection
%K Cybersecurity
%Z Computer Science [cs]Conference papers
%X Intrusion Detection Systems (IDS) for In-Vehicle Networks routinely collect and transfer data about attacks to remote servers. However, the analysis of such data enables the inference of sensitive details about the driver’s identity and daily routine, violating privacy expectations. In this work, we explore the possibilities of applying Local Differential Privacy to In-Vehicle Network data and propose a new privacy-preserving IDS for In-Vehicle Networks. We have designed and conducted various experiments, with promising results, showing that useful information about detected attacks can be inferred from anonymized CAN Bus logs, while preserving privacy.
%G English
%Z TC 9
%Z TC 11
%Z WG 9.2
%Z WG 9.6
%Z WG 11.7
%Z WG 11.6
%2 https://inria.hal.science/hal-03703761/document
%2 https://inria.hal.science/hal-03703761/file/498598_1_En_4_Chapter.pdf
%L hal-03703761
%U https://inria.hal.science/hal-03703761
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC9
%~ IFIP-TC11
%~ IFIP-WG9-2
%~ IFIP-WG9-6
%~ IFIP-WG11-7
%~ IFIP-WG11-6
%~ IFIP-AICT-619
%~ IFIP-PRIVACY-AND-IDENTITY