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Adaptively secure efficient broadcast encryption with constant-size secret key and ciphertext

  • Liqing Chen
  • Jiguo LiEmail author
  • Yichen Zhang
Methodologies and Application

Abstract

In those broadcast application scenarios with a great quantity of receivers, e.g., the data access control system in cloud storage service, the single sender is apt to become the efficiency bottleneck of the system, because the computation and storage overhead of the sender will grow rapidly with the amount of qualified receivers. In order to overcome this problem, we first introduce the novel conception of complete binary identity tree which is adopted to manage the qualified receivers. Then we design the prune-merge algorithm to further optimize the structure of the tree and cut down the amount of receivers. The algorithm effectively reduces the computation and storage cost of the trusted authority in the system. Subsequently, in virtue of composite-order bilinear groups, we bring forward an efficient public key broadcast encryption scheme combined its application to the system of data access control in cloud storage service. Compared with the existing schemes, the lengths of system public parameters, secret key and ciphertext in our scheme are all constant. In addition, the number of secret keys in our scheme increases logarithmically with the maximum amount of receivers, while the numbers of secret keys in the existing schemes increase linearly with the maximum amount of receivers. Furthermore, the proposed scheme is proved to guarantee adaptive security under general subgroup decision assumption in the standard model. The performance analysis manifests that our scheme is feasible for those broadcast applications with fixed senders.

Keywords

Broadcast encryption Public key broadcast encryption Data access control Cloud storage service Adaptive security Standard model 

Notes

Acknowledgements

This study was funded by the National Natural Science Foundation of China (U1736112, 61772009, 61672207), Jiangsu Provincial Natural Science Foundation of China (BK20161511), Jiangsu Key Laboratory of Big Data Security and Intelligent Processing, NJUPT, and the Project of Scientific Research Innovation for College Graduate Student of Jiangsu Province (KYZZ15_0151).

Compliance with ethical standards

Conflict of interest

All authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.College of Computer and InformationHohai UniversityNanjingChina
  2. 2.College of Mathematics and InformaticsFujian Normal UniversityFuzhouChina
  3. 3.Faculty of Computer and Software EngineeringHuaiyin Institute of TechnologyHuai’anChina
  4. 4.State Key Laboratory of CryptologyBeijingChina

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