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Efficient, compromise resilient and append-only cryptographic schemes for secure audit logging

Publication ,  Conference
Yavuz, AA; Ning, P; Reiter, MK
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
September 11, 2012

Due to the forensic value of audit logs, it is vital to provide compromise resiliency and append-only properties in a logging system to prevent active attackers. Unfortunately, existing symmetric secure logging schemes are not publicly verifiable and cannot address applications that require public auditing (e.g., public financial auditing), besides being vulnerable to certain attacks and dependent on continuous trusted server support. Moreover, Public Key Cryptography (PKC)-based secure logging schemes require Expensive Operations (ExpOps) that are costly for both loggers and verifiers, and thus are impractical for computation-intensive environments. In this paper, we propose a new class of secure audit logging scheme called Log F orward-secure and A ppend-only S ignature (LogFAS). LogFAS achieves the most desirable properties of both symmetric and PKC-based schemes. LogFAS can produce publicly verifiable forward-secure and append-only signatures without requiring any online trusted server support or time factor. Most notably, LogFAS is the only PKC-based secure audit logging scheme that achieves the high verifier computational and storage efficiency. That is, LogFAS can verify L log entries with always a small-constant number of ExpOps regardless of the value of L. Moreover, each verifier stores only a small and constant-size public key regardless of the number of log entries to be verified or the number of loggers in the system. In addition, a LogFAS variation allows fine-grained verification of any subset of log entries and fast detection of corrupted log entries. All these properties make LogFAS an ideal scheme for secure audit logging in computation-intensive applications. © 2012 Springer-Verlag.

Duke Scholars

Published In

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

DOI

EISSN

1611-3349

ISSN

0302-9743

ISBN

9783642329456

Publication Date

September 11, 2012

Volume

7397 LNCS

Start / End Page

148 / 163

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

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Yavuz, A. A., Ning, P., & Reiter, M. K. (2012). Efficient, compromise resilient and append-only cryptographic schemes for secure audit logging. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7397 LNCS, pp. 148–163). https://doi.org/10.1007/978-3-642-32946-3_12
Yavuz, A. A., P. Ning, and M. K. Reiter. “Efficient, compromise resilient and append-only cryptographic schemes for secure audit logging.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7397 LNCS:148–63, 2012. https://doi.org/10.1007/978-3-642-32946-3_12.
Yavuz AA, Ning P, Reiter MK. Efficient, compromise resilient and append-only cryptographic schemes for secure audit logging. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2012. p. 148–63.
Yavuz, A. A., et al. “Efficient, compromise resilient and append-only cryptographic schemes for secure audit logging.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7397 LNCS, 2012, pp. 148–63. Scopus, doi:10.1007/978-3-642-32946-3_12.
Yavuz AA, Ning P, Reiter MK. Efficient, compromise resilient and append-only cryptographic schemes for secure audit logging. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2012. p. 148–163.
Journal cover image

Published In

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

DOI

EISSN

1611-3349

ISSN

0302-9743

ISBN

9783642329456

Publication Date

September 11, 2012

Volume

7397 LNCS

Start / End Page

148 / 163

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences