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Secure audit logs to support computer forensics
Open accessAbstract
In many real-world applications, sensitive information must be kept it log files on an untrusted machine. In the event that an attacker captures this machine, we would like to guarantee that he will gain little or no information from the log files and to limit his ability to corrupt the log files. We describe a computationally cheap method for making all log entries generated prior to the logging machine's compromise impossible for the attacker to read, and also impossible to modify or destroy undetectably.
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“Key-evolution schemes (Schneier and Kelsey, 1999) chain successive log entries through evolving cryptographic keys, providing forward integrity but requiring careful key management and offering only sequential verification.”
From Lightweight Tamper-Evident Log Integrity Verification for IoT Edge Environments: A Merkle Tree Pipeline with Adaptive Chunking (2026) · cites this paper as Schneier and Kelsey, 1999
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Metadata
- Authors
- Schneier, B., & Kelsey, J.
- Affiliations
- University of Minnesota (US)
- Venue
- ACM Transactions on Information and System Security
- Published
- 1999-05
- Volume
- 2
- Issue
- 2
- Pages
- 159-176
- ISSN
- 1094-9224 (ISSN-L)
- 1557-7406
- OpenAlex
- W1987593503
- Cited by
- 443
- References
- 26
- Citations by year
- 2026: 38 · 2025: 7 · 2024: 5 · 2023: 11 · 2022: 5 · 2021: 10 · 2020: 18 · 2019: 23 · 2018: 22 · 2017: 19 · 2016: 10 · 2015: 30 · 2014: 29 · 2013: 23 · 2012: 21
- FWCI
- 3.73
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- ACM Transactions on Information and System Security (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Cryptography and Data Security
- Physical Sciences › Computer Science › Hardware and Architecture › Security and Verification in Computing
- Physical Sciences › Computer Science › Information Systems › Digital and Cyber Forensics
- Keywords
- audit logs, log integrity, digital forensics, secure logging
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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