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A Lightweight Attribute-Based Access Control Scheme for Intelligent Transportation System With Full Privacy Protection

  • IEEE Sensors Journal
  • IEEE Sensors Council
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Abstract

The Intelligent Transportation System (ITS) provides more possibilities for the realization of smart cities by integrating the Internet of Things (IoT) and cloud computing. However, how to ensure security of IoT data stored in the cloud has become one of the biggest challenges at present. As a promising solution for realizing fine-grained access control, Ciphertext-Policy Attribute-Based Encryption (CP-ABE) can be used to ensure data security. However, the traditional CP-ABE schemes may leak privacy of ITS users. Moreover, due to their high computational overheads, the current privacy-preserving techniques are not suitable for IoT lightweight devices. To fill this gap, this article presents ABE-FPP, a lightweight attribute-based access control scheme with full privacy protection (FPP), which can achieve full privacy protection in the three key stages (i.e., key generation, access control, and partial decryption), while reducing consumption overhead on the user side. Specifically, to protect privacy during key generation, a lightweight two-party secure computing protocol between the user and the authority is designed to generate secret keys; to protect privacy during the access control policy setting, we present an efficient policy hidden strategy, which only reveals attribute names and efficiently hides attribute values; to protect privacy during partial decryption, we propose a hybrid authentication method that does not need to submit attribute values to the cloud. Moreover, to achieve lightweight computation for IoT devices, online/offline encryption and outsourced decryption are employed in ABE-FPP. Finally, formal security proofs show that our scheme is secure in the standard model. The asymptotic complexity analyses and experimental results demonstrate that the presented scheme achieves higher computation efficiency than the state-of-the-art ones.

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Publication details

DOI
10.1109/jsen.2020.3030688
OpenAlex
W3184605950
Document type
article
Language
EN
Source
IEEE Sensors Journal
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