Abstract
Sharing economic data is paramount for improving quality and developing more efficient ways to produce statistics, and making better economic decisions. The economic data is of great importance to the corporations and governments, and they must be protected against the outsiders. Unfortunately, in an economic administration system, a few users may be malicious, or they are at high risk to leak information to the outsiders. Therefore, the economic data must also be protected against these users. The traditional broadcast encryption can provide protected data sharing among honest users. However, it is not efficient when most of the users are honest, and only a small amount of users are malicious. The traditional method is not cost effective, and does not fit to the situation where the set of malicious users dynamically changes either. Meanwhile, in traditional broadcast encryption, the authorized users’ identities need to be sent with the ciphertext. The valid users’ anonymity is not provided. To solve these problems, in this work, we present a novel cryptographic primitive, i.e. ID-based Dynamic Exclusive Broadcast Encryption (IBDEBE), and based on a hybrid framework (the combination of the exponent-inversion framework and the commutative-blinding framework) we propose an IBDEBE scheme with constant-size private keys and ciphertexts. The IBDEBE scheme is proved to be semi-adaptively semantically secure in the random oracle model. By applying the IBDEBE scheme, a secure economic data sharing protocol is devised, which is efficient and flexible in dynamic honest user groups, and it provides good security properties, i.e. source authenticity, data integrity protection, data access control, resistance to collusion attack and anonymity. We evaluate the performance of our solution with experiments and the results show good computation efficiency.
Keywords
Bibtex
@article{WANG:FGCS2019, title = "Secure and flexible economic data sharing protocol based on ID-based dynamic exclusive broadcast encryption in economic system", journal = "Future Generation Computer Systems", volume = "99", pages = "177 - 185", year = "2019", issn = "0167-739X", doi = "https://doi.org/10.1016/j.future.2018.11.013", url = "http://www.sciencedirect.com/science/article/pii/S0167739X18316145", author = "Xiaofen Wang and Hong-Ning Dai and Ke Zhang", }
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