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Prevention and trust evaluation scheme based on interpersonal relationships for large-scale peer-to-peer networks

2014, Li, L., Kurths, J., Yang, Y., Liu, G.

In recent years, the complex network as the frontier of complex system has received more and more attention. Peer-to-peer (P2P) networks with openness, anonymity, and dynamic nature are vulnerable and are easily attacked by peers with malicious behaviors. Building trusted relationships among peers in a large-scale distributed P2P system is a fundamental and challenging research topic. Based on interpersonal relationships among peers of large-scale P2P networks, we present prevention and trust evaluation scheme, called IRTrust. The framework incorporates a strategy of identity authentication and a global trust of peers to improve the ability of resisting the malicious behaviors. It uses the quality of service (QoS), quality of recommendation (QoR), and comprehensive risk factor to evaluate the trustworthiness of a peer, which is applicable for large-scale unstructured P2P networks. The proposed IRTrust can defend against several kinds of malicious attacks, such as simple malicious attacks, collusive attacks, strategic attacks, and sybil attacks. Our simulation results show that the proposed scheme provides greater accuracy and stronger resistance compared with existing global trust schemes. The proposed scheme has potential application in secure P2P network coding.

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Topology identification of complex network via chaotic ant swarm algorithm

2013, Peng, H., Li, L., Kurths, J., Li, S., Yang, Y.

Nowadays, the topology of complex networks is essential in various fields as engineering, biology, physics, and other scientific fields. We know in some general cases that there may be some unknown structure parameters in a complex network. In order to identify those unknown structure parameters, a topology identification method is proposed based on a chaotic ant swarm algorithm in this paper. The problem of topology identification is converted into that of parameter optimization which can be solved by a chaotic ant algorithm. The proposed method enables us to identify the topology of the synchronization network effectively. Numerical simulations are also provided to show the effectiveness and feasibility of the proposed method.

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Systems Medicine of Cancer: Bringing Together Clinical Data and Nonlinear Dynamics of Genetic Networks

2016, Blyuss, Konstantin B., Manchanda, Ranjit, Kurths, Jürgen, Alsaedi, Ahmed, Zaikin, Alexey

Editorial

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Sequential decision problems, dependent types and generic solutions

2017, Botta, N., Jansson, P., Ionescu, C., Christiansen, D.R., Brady, E.

We present a computer-checked generic implementation for solving finite-horizon sequential decision problems. This is a wide class of problems, including inter-temporal optimizations, knapsack, optimal bracketing, scheduling, etc. The implementation can handle time-step dependent control and state spaces, and monadic representations of uncertainty (such as stochastic, non-deterministic, fuzzy, or combinations thereof). This level of genericity is achievable in a programming language with dependent types (we have used both Idris and Agda). Dependent types are also the means that allow us to obtain a formalization and computer-checked proof of the central component of our implementation: Bellman’s principle of optimality and the associated backwards induction algorithm. The formalization clarifies certain aspects of backwards induction and, by making explicit notions such as viability and reachability, can serve as a starting point for a theory of controllability of monadic dynamical systems, commonly encountered in, e.g., climate impact research.

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Advances in Time Series Analysis and Its Applications

2016, Gao, Z.-K., Small, M., Donner, R., Meng, D., Ghaffari, H.O.

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Transitions in a genetic transcriptional regulatory system under Lévy motion

2016, Zheng, Y., Serdukova, L., Duan, J., Kurths, J.

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Analysis, simulation and prediction of multivariate random fields with package randomfields

2015, Schlather, Martin, Malinowski, Alexander, Menck, Peter J., Oesting, Marco, Strokorb, Kirstin

Modeling of and inference on multivariate data that have been measured in space, such as temperature and pressure, are challenging tasks in environmental sciences, physics and materials science. We give an overview over and some background on modeling with crosscovariance models. The R package RandomFields supports the simulation, the parameter estimation and the prediction in particular for the linear model of coregionalization, the multivariate Matérn models, the delay model, and a spectrum of physically motivated vector valued models. An example on weather data is considered, illustrating the use of RandomFields for parameter estimation and prediction.

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A reconfigurable logic cell based on a simple dynamical system

2013, Li, L., Yang, C., Hui, S., Yu, W., Kurths, J., Peng, H., Yang, Y.

This paper introduces a new scheme to achieve a dynamic logic gate which can be adjusted flexibly to obtain different logic functions by adjusting specific parameters of a dynamical system. Based on graphical tools and the threshold mechanism, the distribution of different logic gates is studied, and a transformation method between different logics is given. Analyzing the performance of the dynamical system in the presence of noise, we discover that it is resistant to system noise. Moreover, we find some part of the system can be considered as a leaky integrator which has been already widely applied in engineering. Finally, we provide a proof-of-principle hardware implementation of the proposed scheme to illustrate its effectiveness. With the proposed scheme in hand, it is convenient to build the flexible, robust, and general purpose computing devices such as various network coding routers, communication encoders or decoders, and reconfigurable computer chips.

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The Switch in a Genetic Toggle System with Lévy Noise

2016, Xu, Y., Li, Y., Zhang, H., Li, X., Kurths, J.