Reference : An Intrusion Detection System Against Rogue Master Attacks on gPTP
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
Computational Sciences
http://hdl.handle.net/10993/54718
An Intrusion Detection System Against Rogue Master Attacks on gPTP
English
Buscemi, Alessio mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS) >]
Ponaka, Manasvi mailto [University of Luxembourg > Faculty of Science, Technology and Medecine (FSTM) > >]
Fotouhi, Mahdi mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS) >]
Koebel, Christian mailto [Honda R&D (Germany)]
Jomrich, Florian mailto [Honda R&D (Germany)]
Engel, Thomas mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS) >]
Jul-2023
IEEE Vehicular Technology Conference (VTC2023-Spring), Florence 20-23 June 2023
Buscemi, Alessio mailto
Ponaka, Manasvi mailto
Fotouhi, Mahdi mailto
Koebel, Christian mailto
Jomrich, Florian mailto
Engel, Thomas mailto
Yes
No
International
IEEE Vehicular Technology Conference (VTC2023-Spring)
from 20-06-2023 to 23-06-2023
Florence
Italy
[en] Time Sensitive Networking ; Cybersecurity ; Connected Vehicles ; Automotive Ethernet
[en] Due to the promise of deterministic Ethernet networking, Time Sensitive Network (TSN) standards are gaining popularity in the vehicle on-board networks sector. Among these, Generalized Precision Time Protocol (gPTP) allows network devices to be synchronized with a greater degree of precision than other synchronization protocols, such as Network Time Protocol (NTP). However, gPTP was developed without security measures, making it susceptible to a variety of attacks. Adding security controls is the initial step in securing the protocol. However, due to current gPTP design limitations, this countermeasure is insufficient to protect against all types of threats. In this paper, we present a novel supervised Machine Learning (ML)-based pipeline for the detection of high-risk rogue master attacks.
FnR, Honda R&D
Researchers ; Professionals ; General public
http://hdl.handle.net/10993/54718
FnR ; FNR15381341 > Thomas Engel > SETICA > Securing Time Critical Traffic In (Next Gen) Automotive Networks > 01/06/2021 > 31/05/2024 > 2020

File(s) associated to this reference

Fulltext file(s):

FileCommentaryVersionSizeAccess
Open access
IDS_gPTP.pdfAuthor preprint331.03 kBView/Open

Bookmark and Share SFX Query

All documents in ORBilu are protected by a user license.