Eunomia: Anonymous and Secure Vehicular Digital Forensics Based on Blockchain

被引:30
作者
Li, Meng [1 ,2 ]
Chen, Yifei [1 ,2 ]
Lal, Chhagan [3 ]
Conti, Mauro [4 ]
Alazab, Mamoun [5 ]
Hu, Donghui [1 ,2 ]
机构
[1] Hefei Univ Technol, Sch Comp Sci & Informat Engn, Key Lab Knowledge Engn Big Data, Minist Educ, Hefei 230009, Anhui, Peoples R China
[2] Hefei Univ Technol, Anhui Prov Key Lab Ind Safety & Emergency Technol, Intelligent Interconnected Syst Lab Anhui Prov, Minist Educ, Hefei 230009, Anhui, Peoples R China
[3] Delft Univ Technol, Delft, Netherlands
[4] Univ Padua, Dept Math, I-35131 Padua, Italy
[5] Charles Darwin Univ, Coll Engn IT & Environm, Casuarina, NT 0810, Australia
基金
欧盟地平线“2020”; 中国国家自然科学基金;
关键词
Vehicular networks; digital forensics; privacy; security; blockchain;
D O I
10.1109/TDSC.2021.3130583
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Vehicular Digital Forensics (VDF) is essential to enable liability cognizance of accidents and fight against crimes. Ensuring the authority to timely gather, analyze, and trace data promotes vehicular investigations. However, adversaries crave the identity of the data provider/user, damage the evidence, violate evidence jurisdiction, and leak evidence. Therefore, protecting privacy and evidence accountability while guaranteeing access control and traceability in VDF is no easy task. To address the above-mentioned issues, we propose Eunomia: an anonymous and secure VDF scheme based on blockchain. It preserves privacy with decentralized anonymous credentials without trusted third parties. Vehicular data and evidence are uploaded by data providers to the blockchain and stored in distributed data storage. Each investigation is modeled as a finite state machine with state transitions being executed by smart contracts. Eunomia achieves fine-grained evidence access control via ciphertext-policy attribute-based encryption and Bulletproofs. A user must hold specific attributes and a temporary-and-unexpired token/warrant to retrieve data from the blockchain. Finally, a secret key is embedded into data to trace the traitor if any evidence breach happens. We use a formal analysis to demonstrate the strong privacy and security properties of Eunomia. Moreover, we build a prototype in a WiFi-based Ethereum test network to evaluate its performance.
引用
收藏
页码:225 / 241
页数:17
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