@inproceedings{44826b1eabe642f68b4611f063137fee,
title = "SACC: Secure-Cooperative Adaptive Cruise Control for Unmanned Vehicles",
abstract = "With the development of autonomous driving, the data security of the collaboration between vehicles plays a more important role. The research of auto drive systems is still in its infancy, this paper shows that the security mechanisms either depend on hardware or introduce high latency. This paper proposes a novel data protection strategy for efficient coordination across vehicle systems. Our design is based on an observation that the security demand in different phases varies. Specifically, for the external system, this paper proposes an information security scheme with a fine-grained attribute selection mechanism, which has the flexibility of encryption attribute selection. For the internal system, this paper proposes a dual-channel RSA encryption scheme that makes the control information transmission more robust and saves encryption delay. Experimental results illustrate that both security and low latency can be ensured with the proposed SACC.",
keywords = "Attribute-based Encryption, CACC, Data Security, Unmanned Vehicles",
author = "Wen Ran and Changlong Li and Sha, \{Edwin H.M.\}",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.; 7th International Workshop on Knowledge Graph Management and Applications, KGMA 2024, 6th International Workshop on Semi-structured Big Data Management and Applications, SemiBDMA 2024, 1st International Workshop on Mobile Applications and Data Management, MADM 2024, 1st International Workshop on Artificial Intelligence in Education and Educational Data Mining, AIEDM 2024 and 1st International Workshop on Spatio-Temporal Big Data Management, STBDM 2024 held in conjunction with APWeb-WAIM 2024 ; Conference date: 30-08-2024 Through 01-09-2024",
year = "2025",
doi = "10.1007/978-981-96-0055-7\_13",
language = "英语",
isbn = "9789819600540",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "151--162",
editor = "Wenjie Zhang and Anthony Tung and Zhonglong Zheng and Zhengyi Yang and Xiaoyang Wang and Hongjie Guo",
booktitle = "Web and Big Data. APWeb-WAIM 2024 International Workshops - KGMA 2024, SemiBDMA 2024, MADM 2024, AIEDM 2024 and STBDM 2024, Proceedings",
address = "德国",
}