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https://doi.org/10.1109/csf.20...
Article . 2014 . Peer-reviewed
Data sources: Crossref
DBLP
Conference object . 2023
Data sources: DBLP
DBLP
Article . 2020
Data sources: DBLP
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Automated Analysis and Synthesis of Block-Cipher Modes of Operation

Authors: Alex J. Malozemoff; Jonathan Katz; Matthew D. Green;

Automated Analysis and Synthesis of Block-Cipher Modes of Operation

Abstract

Block ciphers such as AES are deterministic, keyed functions that operate on small, fixed-size blocks. Block-cipher modes of operation define a mechanism for probabilistic encryption of arbitrary length messages using any underlying block cipher. A mode of operation can be proven secure (say, against chosen-plaintext attacks) based on the assumption that the underlying block cipher is a pseudorandom function. Such proofs are complex and error-prone, however, and must be done from scratch whenever a new mode of operation is developed. We propose an automated approach for the security analysis of block-cipher modes of operation based on a "local" analysis of the steps carried out by the mode when handling a single message block. We model these steps as a directed, acyclic graph, with nodes corresponding to instructions and edges corresponding to intermediate values. We then introduce a set of labels and constraints on the edges, and prove a meta-theorem showing that any mode for which there exists a labeling of the edges satisfying these constraints is secure (against chosen-plaintext attacks). This allows us to reduce security of a given mode to a constraint-satisfaction problem, which in turn can be handled using an SMT solver. We couple our security-analysis tool with a routine that automatically generates viable modes, together, these allow us to synthesize hundreds of secure modes.

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    popularity
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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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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
21
Top 10%
Top 10%
Top 10%