20220375.pdf (2.17 MB)
Internal network monitoring with DNN and network tomography for in-vehicle networks
conference contribution
posted on 2023-06-10, 04:59 authored by Amani Mohammad A IbraheemAmani Mohammad A Ibraheem, Zhengguo ShengZhengguo Sheng, George ParisisGeorge Parisis, Jianshan Zhou, Daxin TianWith the advancements in Internet-of-Things (IoTs), particularly in Internet-of-Vehicles (IoVs), the vehicle becomes more vulnerable to more attack types caused by connecting the vehicle to the outside world. Moreover, the shift towards automotive Ethernet exposes the vehicle to IP-based attacks similar to attacks on computer networks. Most of such attacks tamper with the internal network components in order to gain control or disable some (or all) of the vehicle’s functions. To this end, in this work, we study two in-vehicle network monitoring approaches based on network tomography. The first approach relies purely on deep neural network (DNN) and we call it DNN-based tomography approach, while the second was proposed in a previous work and it uses algebraic network tomography with deep neural network, we call this one DNN-based algebraic approach. We evaluated the inference performance of both approaches using simulations and found that the DNNbased algebraic tomography approach outperforms DNN-based tomography approach with less inference error of about 4.5µs.
History
Publication status
- Published
File Version
- Accepted version
Journal
IEEE International Conference on Unmanned SystemsISSN
2771-7372Publisher
IEEEExternal DOI
Event name
2022 5th IEEE International Conference on Unmanned SystemsEvent location
Guangzhou, ChinaEvent type
conferenceEvent date
October 28-30 2022ISBN
9781665484565Department affiliated with
- Informatics Publications
Notes
© 20XX IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksFull text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2022-10-03First Open Access (FOA) Date
2022-10-03First Compliant Deposit (FCD) Date
2022-10-03Usage metrics
Categories
No categories selectedLicence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC