27,378 research outputs found
Homomorphic encryption and some black box attacks
This paper is a compressed summary of some principal definitions and concepts
in the approach to the black box algebra being developed by the authors. We
suggest that black box algebra could be useful in cryptanalysis of homomorphic
encryption schemes, and that homomorphic encryption is an area of research
where cryptography and black box algebra may benefit from exchange of ideas
Roadmap on optical security
Postprint (author's final draft
Modeling Adversaries in a Logic for Security Protocol Analysis
Logics for security protocol analysis require the formalization of an
adversary model that specifies the capabilities of adversaries. A common model
is the Dolev-Yao model, which considers only adversaries that can compose and
replay messages, and decipher them with known keys. The Dolev-Yao model is a
useful abstraction, but it suffers from some drawbacks: it cannot handle the
adversary knowing protocol-specific information, and it cannot handle
probabilistic notions, such as the adversary attempting to guess the keys. We
show how we can analyze security protocols under different adversary models by
using a logic with a notion of algorithmic knowledge. Roughly speaking,
adversaries are assumed to use algorithms to compute their knowledge; adversary
capabilities are captured by suitable restrictions on the algorithms used. We
show how we can model the standard Dolev-Yao adversary in this setting, and how
we can capture more general capabilities including protocol-specific knowledge
and guesses.Comment: 23 pages. A preliminary version appeared in the proceedings of
FaSec'0
Average-Case Complexity
We survey the average-case complexity of problems in NP.
We discuss various notions of good-on-average algorithms, and present
completeness results due to Impagliazzo and Levin. Such completeness results
establish the fact that if a certain specific (but somewhat artificial) NP
problem is easy-on-average with respect to the uniform distribution, then all
problems in NP are easy-on-average with respect to all samplable distributions.
Applying the theory to natural distributional problems remain an outstanding
open question. We review some natural distributional problems whose
average-case complexity is of particular interest and that do not yet fit into
this theory.
A major open question whether the existence of hard-on-average problems in NP
can be based on the PNP assumption or on related worst-case assumptions.
We review negative results showing that certain proof techniques cannot prove
such a result. While the relation between worst-case and average-case
complexity for general NP problems remains open, there has been progress in
understanding the relation between different ``degrees'' of average-case
complexity. We discuss some of these ``hardness amplification'' results
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