Ternary subset difference method and its quantitative analysis

Kazuhide Fukushima, Shinsaku Kiyomoto, Toshiaki Tanaka, Kouichi Sakurai

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

6 Citations (Scopus)


This paper proposes a ternary subset difference method (SD method) that is resistant to coalition attacks. In order to realize a secure ternary SD method, we design a new cover-finding algorithm, label assignment algorithm, and encryption algorithm. These algorithms are required to revoke one or two subtrees simultaneously while maintaining resistance against coalition attacks. We realize this two-way revocation mechanism by creatively using labels and hashed labels. Then, we evaluate the efficiency and security of the ternary SD method. We show that the upper bound of the average message length in the ternary SD method is smaller by about 12.2 percent than that of the conventional SD method, and the number of labels on each client device can be reduced by about 20.4 percent. On the other hand, the computational cost imposed on a client device stays within O(logn). Finally, we prove that the ternary SD method is secure against coalition attacks.

Original languageEnglish
Title of host publicationInformation Security Applications - 9th International Workshop, WISA 2008, Revised Selected Papers
Number of pages15
Publication statusPublished - 2009
Event9th International Workshop on Information Security Applications, WISA 2008 - Jeju Island, Korea, Republic of
Duration: Sept 23 2008Sept 25 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5379 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other9th International Workshop on Information Security Applications, WISA 2008
Country/TerritoryKorea, Republic of
CityJeju Island

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'Ternary subset difference method and its quantitative analysis'. Together they form a unique fingerprint.

Cite this