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Analysis of Client-Side Security for Long-Term Time-Stamping Services

Authors: Long Meng; Liqun Chen 0002;

Analysis of Client-Side Security for Long-Term Time-Stamping Services

Abstract

Time-stamping services produce time-stamp tokens as evidences to prove that digital data existed at given points in time. Time-stamp tokens contain verifiable cryptographic bindings between data and time, which are produced using cryptographic algorithms. In the ANSI, ISO/IEC and IETF standards for time-stamping services, cryptographic algorithms are addressed in two aspects: (i) Client-side hash functions used to hash data into digests for nondisclosure. (ii) Server-side algorithms used to bind the time and digests of data. These algorithms are associated with limited lifespans due to their operational life cycles and increasing computational powers of attackers. After the algorithms are compromised, time-stamp tokens using the algorithms are no longer trusted. The ANSI and ISO/IEC standards provide renewal mechanisms for time-stamp tokens. However, the renewal mechanisms for client-side hash functions are specified ambiguously, that may lead to the failure of implementations. Besides, in existing papers, the security analyses of long-term time-stamping schemes only cover the server-side renewal, and the client-side renewal ismissing. In this paper, we analyse the necessity of client-side renewal, and propose a comprehensive long-term time-stamping scheme that addresses both client-side renewal and server-side renewal mechanisms. After that, we formally analyse and evaluate the client-side security of our proposed scheme.

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Keywords

ISO/IEC time-stamping, Time-stamping, hash function

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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