500 research outputs found
Noise from metallic surfaces -- effects of charge diffusion
Non-local electrodynamic models are developed for describing metallic
surfaces for a diffusive metal. The electric field noise at a distance z_0 from
the surface is evaluated and compared with data from ion chips that show
anomalous heating with a noise power decaying as z_0^{-4}. We find that high
surface diffusion can account for the latter result.Comment: 16 pages, 2 figures. Revised version focusing on charge diffusing and
anomalous heatin
Electromagnetic wave refraction at an interface of a double wire medium
Plane-wave reflection and refraction at an interface with a double wire
medium is considered. The problem of additional boundary conditions (ABC) in
application to wire media is discussed and an ABC-free approach, known in the
solid state physics, is used. Expressions for the fields and Poynting vectors
of the refracted waves are derived. Directions and values of the power density
flow of the refracted waves are found and the conservation of the power flow
through the interface is checked. The difference between the results, given by
the conventional model of wire media and the model, properly taking into
account spatial dispersion, is discussed.Comment: 17 pages, 11 figure
Poynting's theorem and energy conservation in the propagation of light in bounded media
Starting from the Maxwell-Lorentz equations, Poynting's theorem is
reconsidered. The energy flux vector is introduced as S_e=(E x B)/mu_0 instead
of E x H, because only by this choice the energy dissipation can be related to
the balance of the kinetic energy of the matter subsystem. Conservation of the
total energy as the sum of kinetic and electromagnetic energy follows. In our
discussion, media and their microscopic nature are represented exactly by their
susceptibility functions, which do not necessarily have to be known. On this
footing, it can be shown that energy conservation in the propagation of light
through bounded media is ensured by Maxwell's boundary conditions alone, even
for some frequently used approximations. This is demonstrated for approaches
using additional boundary conditions and the dielectric approximation in
detail, the latter of which suspected to violate energy conservation for
decades.Comment: 5 pages, RevTeX4, changes: complete rewrit
Theoretical analysis of the focusing of acoustic waves by two-dimensional sonic crystals
Motivated by a recent experiment on acoustic lenses, we perform numerical
calculations based on a multiple scattering technique to investigate the
focusing of acoustic waves with sonic crystals formed by rigid cylinders in
air. The focusing effects for crystals of various shapes are examined. The
dependance of the focusing length on the filling factor is also studied. It is
observed that both the shape and filling factor play a crucial role in
controlling the focusing. Furthermore, the robustness of the focusing against
disorders is studied. The results show that the sensitivity of the focusing
behavior depends on the strength of positional disorders. The theoretical
results compare favorably with the experimental observations, reported by
Cervera, et al. (Phys. Rev. Lett. 88, 023902 (2002)).Comment: 8 figure
Homomorphic Evaluation of the AES Circuit
We describe a working implementation of leveled homomorphic encryption (with or without bootstrapping) that can evaluate the AES-128 circuit. This implementation is built on top of the HElib library, whose design was inspired by an early version of the current work. Our main implementation (without bootstrapping) takes about 4 minutes and 3GB of RAM, running on a small laptop, to evaluate an entire AES-128 encryption operation. Using SIMD techniques, we can process upto 120 blocks in each such evaluation, yielding an amortized rate of just over 2 seconds per block.
For cases where further processing is needed after the AES computation, we describe a different setting that uses bootstrapping. We describe an implementation that lets us process 180 blocks in just over 18 minutes using 3.7GB of RAM on the same laptop, yielding amortized 6 seconds/block. We note that somewhat better amortized per-block cost can be obtained using byte-slicing (and maybe also bit-slicing ) implementations, at the cost of significantly slower wall-clock time for a single evaluation
MV3: A new word based stream cipher using rapid mixing and revolving buffers
MV3 is a new word based stream cipher for encrypting long streams of data. A
direct adaptation of a byte based cipher such as RC4 into a 32- or 64-bit word
version will obviously need vast amounts of memory. This scaling issue
necessitates a look for new components and principles, as well as mathematical
analysis to justify their use. Our approach, like RC4's, is based on rapidly
mixing random walks on directed graphs (that is, walks which reach a random
state quickly, from any starting point). We begin with some well understood
walks, and then introduce nonlinearity in their steps in order to improve
security and show long term statistical correlations are negligible. To
minimize the short term correlations, as well as to deter attacks using
equations involving successive outputs, we provide a method for sequencing the
outputs derived from the walk using three revolving buffers. The cipher is fast
-- it runs at a speed of less than 5 cycles per byte on a Pentium IV processor.
A word based cipher needs to output more bits per step, which exposes more
correlations for attacks. Moreover we seek simplicity of construction and
transparent analysis. To meet these requirements, we use a larger state and
claim security corresponding to only a fraction of it. Our design is for an
adequately secure word-based cipher; our very preliminary estimate puts the
security close to exhaustive search for keys of size < 256 bits.Comment: 27 pages, shortened version will appear in "Topics in Cryptology -
CT-RSA 2007
The weak password problem: chaos, criticality, and encrypted p-CAPTCHAs
Vulnerabilities related to weak passwords are a pressing global economic and
security issue. We report a novel, simple, and effective approach to address
the weak password problem. Building upon chaotic dynamics, criticality at phase
transitions, CAPTCHA recognition, and computational round-off errors we design
an algorithm that strengthens security of passwords. The core idea of our
method is to split a long and secure password into two components. The first
component is memorized by the user. The second component is transformed into a
CAPTCHA image and then protected using evolution of a two-dimensional dynamical
system close to a phase transition, in such a way that standard brute-force
attacks become ineffective. We expect our approach to have wide applications
for authentication and encryption technologies.Comment: 5 pages, 6 figer
Confidential Boosting with Random Linear Classifiers for Outsourced User-generated Data
User-generated data is crucial to predictive modeling in many applications.
With a web/mobile/wearable interface, a data owner can continuously record data
generated by distributed users and build various predictive models from the
data to improve their operations, services, and revenue. Due to the large size
and evolving nature of users data, data owners may rely on public cloud service
providers (Cloud) for storage and computation scalability. Exposing sensitive
user-generated data and advanced analytic models to Cloud raises privacy
concerns. We present a confidential learning framework, SecureBoost, for data
owners that want to learn predictive models from aggregated user-generated data
but offload the storage and computational burden to Cloud without having to
worry about protecting the sensitive data. SecureBoost allows users to submit
encrypted or randomly masked data to designated Cloud directly. Our framework
utilizes random linear classifiers (RLCs) as the base classifiers in the
boosting framework to dramatically simplify the design of the proposed
confidential boosting protocols, yet still preserve the model quality. A
Cryptographic Service Provider (CSP) is used to assist the Cloud's processing,
reducing the complexity of the protocol constructions. We present two
constructions of SecureBoost: HE+GC and SecSh+GC, using combinations of
homomorphic encryption, garbled circuits, and random masking to achieve both
security and efficiency. For a boosted model, Cloud learns only the RLCs and
the CSP learns only the weights of the RLCs. Finally, the data owner collects
the two parts to get the complete model. We conduct extensive experiments to
understand the quality of the RLC-based boosting and the cost distribution of
the constructions. Our results show that SecureBoost can efficiently learn
high-quality boosting models from protected user-generated data
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