682 research outputs found
Detection of selfish manipulation of carrier sensing in 802.11 networks
Recently, tuning the clear channel assessment (CCA) threshold in conjunction with power control has been considered for improving the performance of WLANs. However, we show that, CCA tuning can be exploited by selfish nodes to obtain an unfair share of the available bandwidth. Specifically, a selfish entity can manipulate the CCA threshold to ignore ongoing transmissions; this increases the probability of accessing the medium and provides the entity a higher, unfair share of the bandwidth. We experiment on our 802.11 testbed to characterize the effects of CCA tuning on both isolated links and in 802.11 WLAN configurations. We focus on AP-client(s) configurations, proposing a novel approach to detect this misbehavior. A misbehaving client is unlikely to recognize low power receptions as legitimate packets; by intelligently sending low power probe messages, an AP can efficiently detect a misbehaving node. Our key contributions are: 1) We are the first to quantify the impact of selfish CCA tuning via extensive experimentation on various 802.11 configurations. 2) We propose a lightweight scheme for detecting selfish nodes that inappropriately increase their CCAs. 3) We extensively evaluate our system on our testbed; its accuracy is 95 percent while the false positive rate is less than 5 percent. © 2012 IEEE
Secret Sharing Based on a Hard-on-Average Problem
The main goal of this work is to propose the design of secret sharing schemes
based on hard-on-average problems. It includes the description of a new
multiparty protocol whose main application is key management in networks. Its
unconditionally perfect security relies on a discrete mathematics problem
classiffied as DistNP-Complete under the average-case analysis, the so-called
Distributional Matrix Representability Problem. Thanks to the use of the search
version of the mentioned decision problem, the security of the proposed scheme
is guaranteed. Although several secret sharing schemes connected with
combinatorial structures may be found in the bibliography, the main
contribution of this work is the proposal of a new secret sharing scheme based
on a hard-on-average problem, which allows to enlarge the set of tools for
designing more secure cryptographic applications
Nearly optimal robust secret sharing
Abstract: We prove that a known approach to improve Shamir's celebrated secret sharing scheme; i.e., adding an information-theoretic authentication tag to the secret, can make it robust for n parties against any collusion of size ÎŽn, for any constant ÎŽ â (0; 1/2). This result holds in the so-called ânonrushingâ model in which the n shares are submitted simultaneously for reconstruction. We thus finally obtain a simple, fully explicit, and robust secret sharing scheme in this model that is essentially optimal in all parameters including the share size which is k(1+o(1))+O(Îș), where k is the secret length and Îș is the security parameter. Like Shamir's scheme, in this modified scheme any set of more than ÎŽn honest parties can efficiently recover the secret. Using algebraic geometry codes instead of Reed-Solomon codes, the share length can be decreased to a constant (only depending on ÎŽ) while the number of shares n can grow independently. In this case, when n is large enough, the scheme satisfies the âthresholdâ requirement in an approximate sense; i.e., any set of ÎŽn(1 + Ï) honest parties, for arbitrarily small Ï > 0, can efficiently reconstruct the secret
An Epitome of Multi Secret Sharing Schemes for General Access Structure
Secret sharing schemes are widely used now a days in various applications,
which need more security, trust and reliability. In secret sharing scheme, the
secret is divided among the participants and only authorized set of
participants can recover the secret by combining their shares. The authorized
set of participants are called access structure of the scheme. In Multi-Secret
Sharing Scheme (MSSS), k different secrets are distributed among the
participants, each one according to an access structure. Multi-secret sharing
schemes have been studied extensively by the cryptographic community. Number of
schemes are proposed for the threshold multi-secret sharing and multi-secret
sharing according to generalized access structure with various features. In
this survey we explore the important constructions of multi-secret sharing for
the generalized access structure with their merits and demerits. The features
like whether shares can be reused, participants can be enrolled or dis-enrolled
efficiently, whether shares have to modified in the renewal phase etc., are
considered for the evaluation
Multi-round Master-Worker Computing: a Repeated Game Approach
We consider a computing system where a master processor assigns tasks for
execution to worker processors through the Internet. We model the workers
decision of whether to comply (compute the task) or not (return a bogus result
to save the computation cost) as a mixed extension of a strategic game among
workers. That is, we assume that workers are rational in a game-theoretic
sense, and that they randomize their strategic choice. Workers are assigned
multiple tasks in subsequent rounds. We model the system as an infinitely
repeated game of the mixed extension of the strategic game. In each round, the
master decides stochastically whether to accept the answer of the majority or
verify the answers received, at some cost. Incentives and/or penalties are
applied to workers accordingly. Under the above framework, we study the
conditions in which the master can reliably obtain tasks results, exploiting
that the repeated games model captures the effect of long-term interaction.
That is, workers take into account that their behavior in one computation will
have an effect on the behavior of other workers in the future. Indeed, should a
worker be found to deviate from some agreed strategic choice, the remaining
workers would change their own strategy to penalize the deviator. Hence, being
rational, workers do not deviate. We identify analytically the parameter
conditions to induce a desired worker behavior, and we evaluate experi-
mentally the mechanisms derived from such conditions. We also compare the
performance of our mechanisms with a previously known multi-round mechanism
based on reinforcement learning.Comment: 21 pages, 3 figure
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