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    Xie Yong, Hu Qiuyan, Li Renfa, Xie Guoqi, Xiao Fu. An Optimized Over-the-Air Software Update Framework Based on Uptane for Automobiles[J]. Journal of Computer Research and Development. DOI: 10.7544/issn1000-1239.202330874
    Citation: Xie Yong, Hu Qiuyan, Li Renfa, Xie Guoqi, Xiao Fu. An Optimized Over-the-Air Software Update Framework Based on Uptane for Automobiles[J]. Journal of Computer Research and Development. DOI: 10.7544/issn1000-1239.202330874

    An Optimized Over-the-Air Software Update Framework Based on Uptane for Automobiles

    • Autonomous driving, connected vehicles, electrification of the powertrain, and shared mobility lead to the rapid increasing of the complexity of automotive electronic system, and the functional safety and cyber-security problems of the automotive electronic system cause a serial of recalls frequently, which is resulting in a huge economic loss and user experience decline of the original equipment manufacturer (OEM). The over-the-air (OTA) update technology uses wireless network to achieve remote update of software and firmware in scenarios such as automatic driving function update, on-board software update and on-board safety system upgrade, thus avoiding the adverse impact of recall, but how to guarantee the cyber-security and efficient implementation of the OTA processes is a key problem needing to be resolved by auto industry. The opensource Uptane framework is an industry reference specification for OTA, but it has some cyber-security vulnerabilities and brings too large system overhead for its current reference implementation. By choosing efficient hash and signature algorithms and introducing a new verification mechanism based on alliance chain, an optimized Uptane framework is proposed with reduced resource and time overhead and increased cyber-security. The prototype implementation verifies the cyber-security of the optimized Uptane framework, and by comparing with the original Uptane framework, the memory consumption and delay overhead of the optimized Uptane framework are reduced by 6.9% and 28.6%, respectively.
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