47,528 research outputs found
Fuzzy Extractors: How to Generate Strong Keys from Biometrics and Other Noisy Data
We provide formal definitions and efficient secure techniques for
- turning noisy information into keys usable for any cryptographic
application, and, in particular,
- reliably and securely authenticating biometric data.
Our techniques apply not just to biometric information, but to any keying
material that, unlike traditional cryptographic keys, is (1) not reproducible
precisely and (2) not distributed uniformly. We propose two primitives: a
"fuzzy extractor" reliably extracts nearly uniform randomness R from its input;
the extraction is error-tolerant in the sense that R will be the same even if
the input changes, as long as it remains reasonably close to the original.
Thus, R can be used as a key in a cryptographic application. A "secure sketch"
produces public information about its input w that does not reveal w, and yet
allows exact recovery of w given another value that is close to w. Thus, it can
be used to reliably reproduce error-prone biometric inputs without incurring
the security risk inherent in storing them.
We define the primitives to be both formally secure and versatile,
generalizing much prior work. In addition, we provide nearly optimal
constructions of both primitives for various measures of ``closeness'' of input
data, such as Hamming distance, edit distance, and set difference.Comment: 47 pp., 3 figures. Prelim. version in Eurocrypt 2004, Springer LNCS
3027, pp. 523-540. Differences from version 3: minor edits for grammar,
clarity, and typo
Scalable Byzantine Reliable Broadcast
Byzantine reliable broadcast is a powerful primitive that allows a set of processes to agree on a message from a designated sender, even if some processes (including the sender) are Byzantine. Existing broadcast protocols for this setting scale poorly, as they typically build on quorum systems with strong intersection guarantees, which results in linear per-process communication and computation complexity.
We generalize the Byzantine reliable broadcast abstraction to the probabilistic setting, allowing each of its properties to be violated with a fixed, arbitrarily small probability. We leverage these relaxed guarantees in a protocol where we replace quorums with stochastic samples. Compared to quorums, samples are significantly smaller in size, leading to a more scalable design. We obtain the first Byzantine reliable broadcast protocol with logarithmic per-process communication and computation complexity.
We conduct a complete and thorough analysis of our protocol, deriving bounds on the probability of each of its properties being compromised. During our analysis, we introduce a novel general technique that we call adversary decorators. Adversary decorators allow us to make claims about the optimal strategy of the Byzantine adversary without imposing any additional assumptions. We also introduce Threshold Contagion, a model of message propagation through a system with Byzantine processes. To the best of our knowledge, this is the first formal analysis of a probabilistic broadcast protocol in the Byzantine fault model. We show numerically that practically negligible failure probabilities can be achieved with realistic security parameters
Applications of Fog Computing in Video Streaming
The purpose of this paper is to show the viability of fog computing in the area of video streaming in vehicles. With the rise of autonomous vehicles, there needs to be a viable entertainment option for users. The cloud fails to address these options due to latency problems experienced during high internet traffic. To improve video streaming speeds, fog computing seems to be the best option. Fog computing brings the cloud closer to the user through the use of intermediary devices known as fog nodes. It does not attempt to replace the cloud but improve the cloud by allowing faster upload and download of information. This paper explores two algorithms that would work well with vehicles and video streaming. This is simulated using a Java application, and then graphically represented. The results showed that the simulation was an accurate model and that the best algorithm for request history maintenance was the variable model
On the Commitment Capacity of Unfair Noisy Channels
Noisy channels are a valuable resource from a cryptographic point of view.
They can be used for exchanging secret-keys as well as realizing other
cryptographic primitives such as commitment and oblivious transfer. To be
really useful, noisy channels have to be consider in the scenario where a
cheating party has some degree of control over the channel characteristics.
Damg\r{a}rd et al. (EUROCRYPT 1999) proposed a more realistic model where such
level of control is permitted to an adversary, the so called unfair noisy
channels, and proved that they can be used to obtain commitment and oblivious
transfer protocols. Given that noisy channels are a precious resource for
cryptographic purposes, one important question is determining the optimal rate
in which they can be used. The commitment capacity has already been determined
for the cases of discrete memoryless channels and Gaussian channels. In this
work we address the problem of determining the commitment capacity of unfair
noisy channels. We compute a single-letter characterization of the commitment
capacity of unfair noisy channels. In the case where an adversary has no
control over the channel (the fair case) our capacity reduces to the well-known
capacity of a discrete memoryless binary symmetric channel
Coding Schemes for Achieving Strong Secrecy at Negligible Cost
We study the problem of achieving strong secrecy over wiretap channels at
negligible cost, in the sense of maintaining the overall communication rate of
the same channel without secrecy constraints. Specifically, we propose and
analyze two source-channel coding architectures, in which secrecy is achieved
by multiplexing public and confidential messages. In both cases, our main
contribution is to show that secrecy can be achieved without compromising
communication rate and by requiring only randomness of asymptotically vanishing
rate. Our first source-channel coding architecture relies on a modified wiretap
channel code, in which randomization is performed using the output of a source
code. In contrast, our second architecture relies on a standard wiretap code
combined with a modified source code termed uniform compression code, in which
a small shared secret seed is used to enhance the uniformity of the source code
output. We carry out a detailed analysis of uniform compression codes and
characterize the optimal size of the shared seed.Comment: 15 pages, two-column, 5 figures, accepted to IEEE Transactions on
Information Theor
TANGO: Transparent heterogeneous hardware Architecture deployment for eNergy Gain in Operation
The paper is concerned with the issue of how software systems actually use
Heterogeneous Parallel Architectures (HPAs), with the goal of optimizing power
consumption on these resources. It argues the need for novel methods and tools
to support software developers aiming to optimise power consumption resulting
from designing, developing, deploying and running software on HPAs, while
maintaining other quality aspects of software to adequate and agreed levels. To
do so, a reference architecture to support energy efficiency at application
construction, deployment, and operation is discussed, as well as its
implementation and evaluation plans.Comment: Part of the Program Transformation for Programmability in
Heterogeneous Architectures (PROHA) workshop, Barcelona, Spain, 12th March
2016, 7 pages, LaTeX, 3 PNG figure
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