28,626 research outputs found
Quantifying Timing Leaks and Cost Optimisation
We develop a new notion of security against timing attacks where the attacker
is able to simultaneously observe the execution time of a program and the
probability of the values of low variables. We then show how to measure the
security of a program with respect to this notion via a computable estimate of
the timing leakage and use this estimate for cost optimisation.Comment: 16 pages, 2 figures, 4 tables. A shorter version is included in the
proceedings of ICICS'08 - 10th International Conference on Information and
Communications Security, 20-22 October, 2008 Birmingham, U
Dimension Reduction via Colour Refinement
Colour refinement is a basic algorithmic routine for graph isomorphism
testing, appearing as a subroutine in almost all practical isomorphism solvers.
It partitions the vertices of a graph into "colour classes" in such a way that
all vertices in the same colour class have the same number of neighbours in
every colour class. Tinhofer (Disc. App. Math., 1991), Ramana, Scheinerman, and
Ullman (Disc. Math., 1994) and Godsil (Lin. Alg. and its App., 1997)
established a tight correspondence between colour refinement and fractional
isomorphisms of graphs, which are solutions to the LP relaxation of a natural
ILP formulation of graph isomorphism.
We introduce a version of colour refinement for matrices and extend existing
quasilinear algorithms for computing the colour classes. Then we generalise the
correspondence between colour refinement and fractional automorphisms and
develop a theory of fractional automorphisms and isomorphisms of matrices.
We apply our results to reduce the dimensions of systems of linear equations
and linear programs. Specifically, we show that any given LP L can efficiently
be transformed into a (potentially) smaller LP L' whose number of variables and
constraints is the number of colour classes of the colour refinement algorithm,
applied to a matrix associated with the LP. The transformation is such that we
can easily (by a linear mapping) map both feasible and optimal solutions back
and forth between the two LPs. We demonstrate empirically that colour
refinement can indeed greatly reduce the cost of solving linear programs
Control Plane Compression
We develop an algorithm capable of compressing large networks into a smaller
ones with similar control plane behavior: For every stable routing solution in
the large, original network, there exists a corresponding solution in the
compressed network, and vice versa. Our compression algorithm preserves a wide
variety of network properties including reachability, loop freedom, and path
length. Consequently, operators may speed up network analysis, based on
simulation, emulation, or verification, by analyzing only the compressed
network. Our approach is based on a new theory of control plane equivalence. We
implement these ideas in a tool called Bonsai and apply it to real and
synthetic networks. Bonsai can shrink real networks by over a factor of 5 and
speed up analysis by several orders of magnitude.Comment: Extended version of the paper appearing in ACM SIGCOMM 201
Enumerating Polytropes
Polytropes are both ordinary and tropical polytopes. We show that tropical
types of polytropes in are in bijection with cones of a
certain Gr\"{o}bner fan in restricted
to a small cone called the polytrope region. These in turn are indexed by
compatible sets of bipartite and triangle binomials. Geometrically, on the
polytrope region, is the refinement of two fans: the fan of
linearity of the polytrope map appeared in \cite{tran.combi}, and the bipartite
binomial fan. This gives two algorithms for enumerating tropical types of
polytropes: one via a general Gr\"obner fan software such as \textsf{gfan}, and
another via checking compatibility of systems of bipartite and triangle
binomials. We use these algorithms to compute types of full-dimensional
polytropes for , and maximal polytropes for .Comment: Improved exposition, fixed error in reporting the number maximal
polytropes for , fixed error in definition of bipartite binomial
Counterfactual Causality from First Principles?
In this position paper we discuss three main shortcomings of existing
approaches to counterfactual causality from the computer science perspective,
and sketch lines of work to try and overcome these issues: (1) causality
definitions should be driven by a set of precisely specified requirements
rather than specific examples; (2) causality frameworks should support system
dynamics; (3) causality analysis should have a well-understood behavior in
presence of abstraction.Comment: In Proceedings CREST 2017, arXiv:1710.0277
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