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Efficient Anonymous Multi-group Broadcast Encryption

Chapter


Abstract


  • Nowadays, broadcasters must supply diverse content to multiple groups without delay in platforms such as social media and streaming sites. Unfortunately, conventional broadcast encryption schemes are deemed unsuitable for such platforms since they generate an independent ciphertext for each piece of contents and hence the number of headers generated during encryption increases linearly with the size of contents. The increased number of headers will result in wasting a limited network bandwidth, which makes the application impractical. To resolve this issue, multi-channel broadcast encryption was proposed in the literature, which transmits a single header for multiple channels to several groups of viewers at a time. However, the multi-channel broadcast encryption is also impractical because it requires heavy computations, communications, and storage overheads. Moreover, it should also address additional issues, such as receiver privacy (anonymity), static user-set size, and limited encryption. In this work, we aim to tackle this problem by proposing an efficient broadcast encryption scheme, called “anonymous multi-group broadcast encryption”. This primitive achieves faster encryption and decryption, provides smaller sized public parameters, private keys, and ciphertexts. Hence, it solves the aforementioned issues of the multi-channel broadcast encryption. Specifically, the proposed scheme provides provable anonymity and confidentiality based on the External Diffie-Hellman (XDH) and-Decisional Bilinear Diffie-Hellman (DBDH) assumptions, respectively, in the standard model.

Publication Date


  • 2020

Citation


  • Kim, I., Hwang, S. O., Susilo, W., Baek, J., & Kim, J. (2020). Efficient Anonymous Multi-group Broadcast Encryption. In Unknown Book (Vol. 12146 LNCS, pp. 251-270). doi:10.1007/978-3-030-57808-4_13

International Standard Book Number (isbn) 13


  • 9783030578077

Scopus Eid


  • 2-s2.0-85091292995

Web Of Science Accession Number


Book Title


  • Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Start Page


  • 251

End Page


  • 270

Abstract


  • Nowadays, broadcasters must supply diverse content to multiple groups without delay in platforms such as social media and streaming sites. Unfortunately, conventional broadcast encryption schemes are deemed unsuitable for such platforms since they generate an independent ciphertext for each piece of contents and hence the number of headers generated during encryption increases linearly with the size of contents. The increased number of headers will result in wasting a limited network bandwidth, which makes the application impractical. To resolve this issue, multi-channel broadcast encryption was proposed in the literature, which transmits a single header for multiple channels to several groups of viewers at a time. However, the multi-channel broadcast encryption is also impractical because it requires heavy computations, communications, and storage overheads. Moreover, it should also address additional issues, such as receiver privacy (anonymity), static user-set size, and limited encryption. In this work, we aim to tackle this problem by proposing an efficient broadcast encryption scheme, called “anonymous multi-group broadcast encryption”. This primitive achieves faster encryption and decryption, provides smaller sized public parameters, private keys, and ciphertexts. Hence, it solves the aforementioned issues of the multi-channel broadcast encryption. Specifically, the proposed scheme provides provable anonymity and confidentiality based on the External Diffie-Hellman (XDH) and-Decisional Bilinear Diffie-Hellman (DBDH) assumptions, respectively, in the standard model.

Publication Date


  • 2020

Citation


  • Kim, I., Hwang, S. O., Susilo, W., Baek, J., & Kim, J. (2020). Efficient Anonymous Multi-group Broadcast Encryption. In Unknown Book (Vol. 12146 LNCS, pp. 251-270). doi:10.1007/978-3-030-57808-4_13

International Standard Book Number (isbn) 13


  • 9783030578077

Scopus Eid


  • 2-s2.0-85091292995

Web Of Science Accession Number


Book Title


  • Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Start Page


  • 251

End Page


  • 270