92,393 research outputs found

    Practical Certificateless Aggregate Signatures From Bilinear Maps

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    Aggregate signature is a digital signature with a striking property that anyone can aggregate n individual signatures on n different messages which are signed by n distinct signers, into a single compact signature to reduce computational and storage costs. In this work, two practical certificateless aggregate signature schemes are proposed from bilinear maps. The first scheme CAS-1 reduces the costs of communication and signer-side computation but trades off the storage, while CAS-2 minimizes the storage but sacrifices the communication costs. One can choose either of the schemes by consideration of the application requirement. Compare with ID-based schemes, our schemes do not entail public key certificates as well and achieve the trust level 3, which imply the frauds of the authority are detectable. Both of the schemes are proven secure in the random oracle model by assuming the intractability of the computational Diffie-Hellman problem over the groups with bilinear maps, where the forking lemma technique is avoided

    On Secure Workflow Decentralisation on the Internet

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    Decentralised workflow management systems are a new research area, where most work to-date has focused on the system's overall architecture. As little attention has been given to the security aspects in such systems, we follow a security driven approach, and consider, from the perspective of available security building blocks, how security can be implemented and what new opportunities are presented when empowering the decentralised environment with modern distributed security protocols. Our research is motivated by a more general question of how to combine the positive enablers that email exchange enjoys, with the general benefits of workflow systems, and more specifically with the benefits that can be introduced in a decentralised environment. This aims to equip email users with a set of tools to manage the semantics of a message exchange, contents, participants and their roles in the exchange in an environment that provides inherent assurances of security and privacy. This work is based on a survey of contemporary distributed security protocols, and considers how these protocols could be used in implementing a distributed workflow management system with decentralised control . We review a set of these protocols, focusing on the required message sequences in reviewing the protocols, and discuss how these security protocols provide the foundations for implementing core control-flow, data, and resource patterns in a distributed workflow environment

    Evolvability signatures of generative encodings: beyond standard performance benchmarks

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    Evolutionary robotics is a promising approach to autonomously synthesize machines with abilities that resemble those of animals, but the field suffers from a lack of strong foundations. In particular, evolutionary systems are currently assessed solely by the fitness score their evolved artifacts can achieve for a specific task, whereas such fitness-based comparisons provide limited insights about how the same system would evaluate on different tasks, and its adaptive capabilities to respond to changes in fitness (e.g., from damages to the machine, or in new situations). To counter these limitations, we introduce the concept of "evolvability signatures", which picture the post-mutation statistical distribution of both behavior diversity (how different are the robot behaviors after a mutation?) and fitness values (how different is the fitness after a mutation?). We tested the relevance of this concept by evolving controllers for hexapod robot locomotion using five different genotype-to-phenotype mappings (direct encoding, generative encoding of open-loop and closed-loop central pattern generators, generative encoding of neural networks, and single-unit pattern generators (SUPG)). We observed a predictive relationship between the evolvability signature of each encoding and the number of generations required by hexapods to adapt from incurred damages. Our study also reveals that, across the five investigated encodings, the SUPG scheme achieved the best evolvability signature, and was always foremost in recovering an effective gait following robot damages. Overall, our evolvability signatures neatly complement existing task-performance benchmarks, and pave the way for stronger foundations for research in evolutionary robotics.Comment: 24 pages with 12 figures in the main text, and 4 supplementary figures. Accepted at Information Sciences journal (in press). Supplemental videos are available online at, see http://goo.gl/uyY1R

    Experimental signature of Quantum Darwinism in photonic cluster states

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    We report on an experimental assessment of the emergence of Quantum Darwinism (QD) from engineered open-system dynamics. We use a photonic hyperentangled source of graph states to address the effects that correlations among the elements of a multi-party environment have on the establishment of objective reality ensuing the quantum-to-classical transition. Besides embodying one of the first experimental efforts towards the characterization of QD, our work illustrates the non-trivial consequences that multipartite entanglement and, in turn, the possibility of having environment-to-system back-action have on the features of the QD framework.Comment: 5 pages, 5 figures, Revtex4-

    Self-Calibration Methods for Uncontrolled Environments in Sensor Networks: A Reference Survey

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    Growing progress in sensor technology has constantly expanded the number and range of low-cost, small, and portable sensors on the market, increasing the number and type of physical phenomena that can be measured with wirelessly connected sensors. Large-scale deployments of wireless sensor networks (WSN) involving hundreds or thousands of devices and limited budgets often constrain the choice of sensing hardware, which generally has reduced accuracy, precision, and reliability. Therefore, it is challenging to achieve good data quality and maintain error-free measurements during the whole system lifetime. Self-calibration or recalibration in ad hoc sensor networks to preserve data quality is essential, yet challenging, for several reasons, such as the existence of random noise and the absence of suitable general models. Calibration performed in the field, without accurate and controlled instrumentation, is said to be in an uncontrolled environment. This paper provides current and fundamental self-calibration approaches and models for wireless sensor networks in uncontrolled environments

    Toward Network-based DDoS Detection in Software-defined Networks

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    To combat susceptibility of modern computing systems to cyberattack, identifying and disrupting malicious traffic without human intervention is essential. To accomplish this, three main tasks for an effective intrusion detection system have been identified: monitor network traffic, categorize and identify anomalous behavior in near real time, and take appropriate action against the identified threat. This system leverages distributed SDN architecture and the principles of Artificial Immune Systems and Self-Organizing Maps to build a network-based intrusion detection system capable of detecting and terminating DDoS attacks in progress

    Hybrid Radio-map for Noise Tolerant Wireless Indoor Localization

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    In wireless networks, radio-map based locating techniques are commonly used to cope the complex fading feature of radio signal, in which a radio-map is built by calibrating received signal strength (RSS) signatures at training locations in the offline phase. However, in severe hostile environments, such as in ship cabins where severe shadowing, blocking and multi-path fading effects are posed by ubiquitous metallic architecture, even radio-map cannot capture the dynamics of RSS. In this paper, we introduced multiple feature radio-map location method for severely noisy environments. We proposed to add low variance signature into radio map. Since the low variance signatures are generally expensive to obtain, we focus on the scenario when the low variance signatures are sparse. We studied efficient construction of multi-feature radio-map in offline phase, and proposed feasible region narrowing down and particle based algorithm for online tracking. Simulation results show the remarkably performance improvement in terms of positioning accuracy and robustness against RSS noises than the traditional radio-map method.Comment: 6 pages, 11th IEEE International Conference on Networking, Sensing and Control, April 7-9, 2014, Miami, FL, US
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