Efficient Fully Anonymous Public-Key Trace and Revoke with Adaptive IND-CCA Security

Mriganka Mandal, Ramprasad Sarkar, Junbeom Hur, Koji Nuida

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

We aim to efficiently design a unified, cost-effective primitive exhibiting two mutually orthogonal functionalities, namely subscribed users anonymity and public-key traitor traceability in the context of Broadcast Encryption (BE), and propose an explicit construction of identity-based Fully Anonymous Public-Key Trace and Revoke (FAnoPKTR) scheme that is obtained by coupling the Identity-Based Encryption (IBE) framework with the collusion-secure optimal probabilistic fingerprinting codes. In addition to being adaptively secure, our design is proven to be INDistinguishable Chosen-Ciphertext Attack (IND-CCA) secure under asymmetric Decisional Bilinear Diffie-Hellman Type-3 (DBDH-3) assumption in standard security model without random oracles. Our asymmetric Type-3 bilinear pairing-based scheme has communication bandwidth that grows with the size of a subscriber set for any encryption, and the user secret-key size is constant. Moreover, our decryption algorithm is faster, which requires only three asymmetric pairings to recover the encrypted broadcast message.

Original languageEnglish
Title of host publicationInformation Security Practice and Experience - 16th International Conference, ISPEC 2021, Proceedings
EditorsRobert Deng, Feng Bao, Guilin Wang, Jian Shen, Mark Ryan, Weizhi Meng, Ding Wang
PublisherSpringer Science and Business Media Deutschland GmbH
Pages168-189
Number of pages22
ISBN (Print)9783030932053
DOIs
Publication statusPublished - 2021
Event16th International Conference on Information Security Practice and Experience, ISPEC 2021 - Nanjing, China
Duration: Dec 17 2021Dec 19 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13107 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Information Security Practice and Experience, ISPEC 2021
Country/TerritoryChina
CityNanjing
Period12/17/2112/19/21

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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