Multi-Level Data Arrangement Algorithm for Can Data Compression

Kim, Yeon-Jin; Zou, Yang; Kim, Young Eun; Chung, Jin-Gyun

doi:10.1007/s12239-020-0144-2

Cited by 9 publications

(12 citation statements)

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“…Fig. 5 shows typical compression ratios achieved by different arrangement levels [24]. As can be seen from the figure, compression ratios usually improve as arrangement levels change from eight bit to two bit.…”

Section: A Message Compression By Vmlda and Encryptionmentioning

confidence: 99%

“…i-th bit of the compressed message length successive CAN frames with the same message identifier do not change rapidly [17]- [24]. In PMDV-based CAN data compression algorithms, the difference value is only transmitted if the difference between the current and preceding CAN messages does not exceed the PMDV.…”

Section: L(•)mentioning

confidence: 99%

“…In the ICANDR algorithm, when CAN data bits are arranged using the byte-level arrangement map shown in Fig. 1, slowly changing data should be placed in the most significant parts of the three signals, while frequently changing data should be placed in the least significant parts [24]. Although different arrangements can result in different compression efficiencies, the ICANDR algorithm does not provide any systematic signal arrangement procedure.…”

Section: B Mlda Algorithmmentioning

confidence: 99%

“…The second class of algorithms uses a compression area selection (CAS) map without using the PMDV [22]- [24]. The size of the CAS map changes depending on the automobile driving conditions, which corresponds to a PMDV change.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, a multi-level data arrangement (MLDA) algorithm was proposed based on the CAS map [24]. While the other compression algorithms in this class use an eightbit signal arrangement, the MLDA algorithm uses a multilevel signal arrangement to increase the compression efficiency.…”

Section: Introductionmentioning

confidence: 99%

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Triple ID Flexible MAC for Can Security Improvement

2021

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The development of automotive-information & communication technology (ICT) convergence has resulted in various vehicle-based electrical/electronic (E/E) systems. An automotive E/E system consists of one or more electronic control units (ECUs), sensors and actuators. As ECUs are growing in popularity, it is necessary to have an efficient communication protocol for in-vehicle networks. Hence, a controller area network (CAN) protocol was developed by Bosch. CAN systems have been successfully applied in many areas, including the automotive industry, due to their high immunity to electrical interference and low cost. However, since the CAN protocol was designed without regard to information security functions, it has many vulnerabilities. With the commercialization of connected/autonomous cars, vehicle-based wireless communication systems have appeared, and are expected to grow in popularity. This increases the number of attack surfaces that can potentially threaten in-vehicle CAN. To combat the vulnerabilities of the CAN protocol, the CAN data field should be encrypted and transmitted with authentication codes. Recently, a method of transmitting authentication codes by modifying the CAN protocol was proposed. However, changing the original CAN protocol can cause serious problems in CAN systems. In this paper, to enhance CAN security, a data compression algorithm is used to reduce the data frame length so that there is space for a message authentication code (MAC) to be contained inside the data field. The proposed algorithm guarantees that all CAN frames are authenticated by a MAC of at least four bytes without any change of the original CAN protocol. Simulations using CAN data from Kia Sorento, Kia Soul, and LS Mtron vehicles show that the proposed algorithm works successfully with only a slight increase in the peak load.

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Section: A Message Compression By Vmlda and Encryptionmentioning

confidence: 99%

Section: L(•)mentioning

confidence: 99%

Section: B Mlda Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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