647 research outputs found
Epitaxial growth and surface reconstruction of CrSb(0001)
Smooth CrSb(0001) films have been grown by molecular beam epitaxy on MnSb(0001) – GaAs(111) substrates. CrSb(0001) shows (2 × 2), triple domain (1 × 4) and (√3×√3)R30° reconstructed surfaces as well as a (1 × 1) phase. The dependence of reconstruction on substrate temperature and incident fluxes is very similar to MnSb(0001)
Sound and Precise Malware Analysis for Android via Pushdown Reachability and Entry-Point Saturation
We present Anadroid, a static malware analysis framework for Android apps.
Anadroid exploits two techniques to soundly raise precision: (1) it uses a
pushdown system to precisely model dynamically dispatched interprocedural and
exception-driven control-flow; (2) it uses Entry-Point Saturation (EPS) to
soundly approximate all possible interleavings of asynchronous entry points in
Android applications. (It also integrates static taint-flow analysis and least
permissions analysis to expand the class of malicious behaviors which it can
catch.) Anadroid provides rich user interface support for human analysts which
must ultimately rule on the "maliciousness" of a behavior.
To demonstrate the effectiveness of Anadroid's malware analysis, we had teams
of analysts analyze a challenge suite of 52 Android applications released as
part of the Auto- mated Program Analysis for Cybersecurity (APAC) DARPA
program. The first team analyzed the apps using a ver- sion of Anadroid that
uses traditional (finite-state-machine-based) control-flow-analysis found in
existing malware analysis tools; the second team analyzed the apps using a
version of Anadroid that uses our enhanced pushdown-based
control-flow-analysis. We measured machine analysis time, human analyst time,
and their accuracy in flagging malicious applications. With pushdown analysis,
we found statistically significant (p < 0.05) decreases in time: from 85
minutes per app to 35 minutes per app in human plus machine analysis time; and
statistically significant (p < 0.05) increases in accuracy with the
pushdown-driven analyzer: from 71% correct identification to 95% correct
identification.Comment: Appears in 3rd Annual ACM CCS workshop on Security and Privacy in
SmartPhones and Mobile Devices (SPSM'13), Berlin, Germany, 201
Empires and Percolation: Stochastic Merging of Adjacent Regions
We introduce a stochastic model in which adjacent planar regions merge
stochastically at some rate , and observe analogies with the
well-studied topics of mean-field coagulation and of bond percolation. Do
infinite regions appear in finite time? We give a simple condition on
for this {\em hegemony} property to hold, and another simple condition for it
to not hold, but there is a large gap between these conditions, which includes
the case . For this case, a non-rigorous analytic
argument and simulations suggest hegemony.Comment: 13 page
Random multi-index matching problems
The multi-index matching problem (MIMP) generalizes the well known matching
problem by going from pairs to d-uplets. We use the cavity method from
statistical physics to analyze its properties when the costs of the d-uplets
are random. At low temperatures we find for d>2 a frozen glassy phase with
vanishing entropy. We also investigate some properties of small samples by
enumerating the lowest cost matchings to compare with our theoretical
predictions.Comment: 22 pages, 16 figure
Entropy-driven cutoff phenomena
In this paper we present, in the context of Diaconis' paradigm, a general
method to detect the cutoff phenomenon. We use this method to prove cutoff in a
variety of models, some already known and others not yet appeared in
literature, including a chain which is non-reversible w.r.t. its stationary
measure. All the given examples clearly indicate that a drift towards the
opportune quantiles of the stationary measure could be held responsible for
this phenomenon. In the case of birth- and-death chains this mechanism is
fairly well understood; our work is an effort to generalize this picture to
more general systems, such as systems having stationary measure spread over the
whole state space or systems in which the study of the cutoff may not be
reduced to a one-dimensional problem. In those situations the drift may be
looked for by means of a suitable partitioning of the state space into classes;
using a statistical mechanics language it is then possible to set up a kind of
energy-entropy competition between the weight and the size of the classes.
Under the lens of this partitioning one can focus the mentioned drift and prove
cutoff with relative ease.Comment: 40 pages, 1 figur
Duplication-divergence model of protein interaction network
We show that the protein-protein interaction networks can be surprisingly
well described by a very simple evolution model of duplication and divergence.
The model exhibits a remarkably rich behavior depending on a single parameter,
the probability to retain a duplicated link during divergence. When this
parameter is large, the network growth is not self-averaging and an average
vertex degree increases algebraically. The lack of self-averaging results in a
great diversity of networks grown out of the same initial condition. For small
values of the link retention probability, the growth is self-averaging, the
average degree increases very slowly or tends to a constant, and a degree
distribution has a power-law tail.Comment: 8 pages, 13 figure
Anomalous scaling due to correlations: Limit theorems and self-similar processes
We derive theorems which outline explicit mechanisms by which anomalous
scaling for the probability density function of the sum of many correlated
random variables asymptotically prevails. The results characterize general
anomalous scaling forms, justify their universal character, and specify
universality domains in the spaces of joint probability density functions of
the summand variables. These density functions are assumed to be invariant
under arbitrary permutations of their arguments. Examples from the theory of
critical phenomena are discussed. The novel notion of stability implied by the
limit theorems also allows us to define sequences of random variables whose sum
satisfies anomalous scaling for any finite number of summands. If regarded as
developing in time, the stochastic processes described by these variables are
non-Markovian generalizations of Gaussian processes with uncorrelated
increments, and provide, e.g., explicit realizations of a recently proposed
model of index evolution in finance.Comment: Through text revision. 15 pages, 3 figure
Random tree growth by vertex splitting
We study a model of growing planar tree graphs where in each time step we
separate the tree into two components by splitting a vertex and then connect
the two pieces by inserting a new link between the daughter vertices. This
model generalises the preferential attachment model and Ford's -model
for phylogenetic trees. We develop a mean field theory for the vertex degree
distribution, prove that the mean field theory is exact in some special cases
and check that it agrees with numerical simulations in general. We calculate
various correlation functions and show that the intrinsic Hausdorff dimension
can vary from one to infinity, depending on the parameters of the model.Comment: 47 page
Unicyclic Components in Random Graphs
The distribution of unicyclic components in a random graph is obtained
analytically. The number of unicyclic components of a given size approaches a
self-similar form in the vicinity of the gelation transition. At the gelation
point, this distribution decays algebraically, U_k ~ 1/(4k) for k>>1. As a
result, the total number of unicyclic components grows logarithmically with the
system size.Comment: 4 pages, 2 figure
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