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Protecting consensus seeking NIDS modules against multiple attackers 17

Protecting consensus seeking NIDS modules against multiple a...

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8th international Symposium on Information and Communication technology, SoICT 2017

作者： Toulouse, Michel Nguyen, Phuong Khanh Vietnamese-German University Binh Duong New City Viet Nam Hanoi University of Science and Technology Hanoi Viet Nam

ISBN: (纸本)9781450353281

This work concerns distributed consensus algorithms and application to a network intrusion detection system (NIDS) [21]. We consider the problem of defending the system against multiple data falsification attacks (Byzantine attacks), a vulnerability of distributed peer-to-peer consensus algorithms that has not been widely addressed in its practicality. We consider both naive (independent) and colluding attackers. We test three defense strategy implementations, two classified as outlier detection methods and one reputation-based method. We have narrowed our attention to outlier and reputation-based methods because they are relatively light computationally speaking. We have left out control theoretic methods which are likely the most effective methods, however their computational cost increase rapidly with the number of attackers. We compare the efficiency of these three implementations for their computational cost, detection performance, convergence behavior and possible impacts on the intrusion detection accuracy of the NIDS. Tests are performed based on simulations of distributed denial of service attacks using the KSL-KDD data set. © 2017 Association for computing Machinery.

关键词： Intrusion detection

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A security analysis and reinforcement design adopting fingerprints over drawbacks of passwords based authentication in remote home automation control system 17

A security analysis and reinforcement design adopting finger...

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6th international conference on Informatics, Environment, Energy and Applications, IEEA 2017

作者： Mukundwa, Chantal Lee, Seok Won Kim, Ki Hyung Computer Engineering Ajou University Korea Republic of Depts. of Software Convergence Technology Information and Computer Engineering Ajou University Korea Republic of Dept. of Knowledge and Information Engineering Ajou University Korea Republic of

ISBN: (纸本)9781450352307

Privacy has been one of the focus in information security discussion over years and it has become an issue everyone would like to protect though sometime people end up giving up some of their privacy in exchange of other services;however, the privacy in home automation is still crucial as ensuring only allowed users can access the appliances within the house. In this research, we evaluated the drawbacks of using passwords for authentication on mobile application used for home automation and provided and analyzed a more robust system design using fingerprints to take the advantage over uniqueness of fingerprint to identify humans. © 2017 ACM.

关键词： Authentication

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Research on Multi-CPU Cluster Modeling and Real-Time Simulation Analysis of High Proportion Active Distribution Network 3

Research on Multi-CPU Cluster Modeling and Real-Time Simulat...

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2017 3rd IEEE international conference on Control Science and Systems Engineering (ICCSSE)

作者： Keyan Liu Wanxing Sheng Dingyu Chen Songhuai Du Hua Ye Juan Su Yonghua Zhang China Electric Power Research Institute China Agricultural University

ISBN: (纸本)9781538604854

High proportion of renewable energy was increased in the distribution network, which will face complex grid complex test and show the scale the diversity and complexity of the operating state. So that the evolution of Wind-photovoltaicenergy storage(Wind-PV-ES) hybrid network transient process is not clear. In the other hand, Transient simulation tool plays a significant role in obtaining a full and detailed response under various operation conditions. However, the simulation capability and speed become limited with increased system size. In order to study the background of high proportion of WindPV-ES in the distribution network, this paper model Wind-PVES and its control system in the multi-CPU cluster fine-grained real-time simulation platform. The control system was further decoupled according to its topology. The multi-CPU can be easily realized, and the computation loads are balanced by DG modeling. The model is used to calculate the load balancing as the optimal condition to be decoupled by the distribution parameters. Parallel computing to ensure the accuracy of the transient simulation results and convergence effect and improve the simulation speed. Then this paper used two typical examples to realize the verification of Multi-CPU simulation results. The simulation results show that the simulation accuracy decreases with the increase of model computation, but the simulation speed is greatly improved. The result reflects the characteristics and transient characteristics of grid-connected transient operation. The effectiveness of the proposed method is validated in integrated simulation of distributed generation system.

关键词： wind-photovoltaic-batter storage modeling multi-CPU cluster calculate real-time simulation distributed parameter decoupled model transient grid process

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Prediction Consensus-Based Distributed Kalman Filtering with Packet Loss 36

Prediction Consensus-Based Distributed Kalman Filtering with...

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第36届中国控制会议

作者： Sha Fan Huaicheng Yan Hao Zhang Mengling Wang Xisheng Zhan Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology College of Mechatronics and Control Engineering Hubei Normal University Department of Control Science and Engineering Tongji University

ISBN: (纸本)9781538629185

This paper is concerned with the problem of distributed state estimation for linear discrete system with packet loss.A state prediction consensus mechanism is introduced to promote the estimation *** applying matrix theory,a sufficient condition for the convergence of the estimation error system is ***,a numerical example is given to show the algorithm proposed in this paper has better consensus performance compared with a classical Kalman consensus filtering（KCF） by some simulations in real and packet-dropping cases,***,the influence of consensus coefficient and prediction consensus coefficient on the estimation error covariance are presented by simulation.

关键词： Distributed state estimation Packet loss Kalman consensus filtering（KCF） State prediction consensus mechanism

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international conference for convergence of technology (I2CT)

Provides an abstract for each of the presentations and may include a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conference proceed... 详细信息

关键词： Computer science Mechanical engineering Information technology Mobile computing Wireless sensor networks Instruments Computational modeling

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EUR assessment of unconventional assets using machine learning and distributed computing techniques

EUR assessment of unconventional assets using machine learni...

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SPE/AAPG/SEG Unconventional Resources technology conference 2017

作者： Guo, Zhenyu Chen, Chaohui Gao, Guohua Cao, Richard Li, Ruijian Liu, Chunlei Shell International Exploration and Production Inc. United States Inc. United States Shell Exploration and Production Co United States

ISBN: (纸本)9781613995433

Reservoir model parameters generally have quite large uncertainty ranges and need to be calibrated by history matching available production data. The ensemble of calibrated models has a direct impact on business decision making, such as EUR assessment and well spacing optimization. Multi-realization history matching (MHM) techniques have been applied to quantify the EUR uncertainty. In practice, MHM requires performing a large number of reservoir simulations on a distributed computing environment. Given the current low oil price environment, it is demanding to reduce the computational cost of MHM without compromising forecasting quality. To solve this challenge, this paper proposed a novel EUR assessment method that integrates a machine learning technique with an advanced distributed computing technique in a history matching workflow. Starting from an initial ensemble of reservoir models, each realization is calibrated iteratively with a previously published Distributed Gauss-Newton method (DGN). Responses of the reservoir realizations are generated by running simulations on a high-performance-cluster (HPC) concurrently. The responses generated during iterations are added to the training data set, which is used to train a set of support vector regression (SVR) models. As the sensitivity matrix for each realization can be estimated analytically from the SVR models, the DGN can use the sensitivity matrix to generate better search point such that the objective function value can decrease more rapidly. The procedure is repeated until convergence. The proposed method is applied to assess EUR for several wells in the Permian Liquid Rich Shale Reservoir field with complicated subsurface oil/water/gas multiphase flows. The uncertain parameters include reservoir static properties, hydraulic-fracture properties, and parameters defining dynamic properties such as relative permeabilities, etc. With the integration of SVR in DGN, the new method saves about 65% of the simulation

关键词： Uncertainty analysis

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A hybrid parallel algorithm for solving eeuler equation using explicit rkdg method based on openfoam 15

A hybrid parallel algorithm for solving eeuler equation usin...

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15th international conference on High Performance computing and Simulation, HPCS 2017

作者： Ye, Shuai Ren, Xiaoguang Tang, Yuhua Xu, Liyang Li, Hao Li, Chao Lin, Yufei College of Computer National University of Defense Technology Changsha Hunan China State Key Laboratory of High Performance Computing National University of Defense Technology Changsha Hunan China

ISBN: (纸本)9781538632505

OpenFOAM is a framework of the open source C CFD toolbox for flexible engineering simulation, which uses finite volume method (FVM) in the discretization of partial differential equations (PDEs). The problem solving procedure in OpenFOAM consists in equations dicretization stage, equations solving stage and field limiting stage. The best parallelism is limited by the equation solving stage, which contains communications. Compared to FVM, discontinuous Galerkin (DG) method is a high-order discretization method, which can accelerate the convergence of the residuals over same mesh scale and has higher resolution of the flow. Based on OpenFOAM with DG method, the ratio of overhead in equations discretization stage increases, especially when solving Euler equations using an explicit method. The equations discretization stage has a better potential parallelism than the other two stages due to no existence of communication. In this paper, we will analysis the difference of time cost in these three stages between original OpenFOAM and OpenFOAM with DG method. By decoupling these three stages, a hybrid parallel algorithm for solving PDEs is proposed and implemented based on OpenFOAM with DG method. The experimental results show that the simulation time is reduced by 16%, and the relative speedup of the hybrid parallel algorithm is up to 2.88 compared to the original parallel algorithm with the same degree of parallelism. © 2017 IEEE.

关键词： Computational fluid dynamics

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A deep Bayesian policy reuse approach against non-stationary agents 18

A deep Bayesian policy reuse approach against non-stationary...

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Proceedings of the 32nd international conference on Neural Information Processing Systems

作者： Yan Zheng Zhaopeng Meng Jianye Hao Zongzhang Zhang Tianpei Yang Changjie Fan College of Intelligence and Computing Tianjin University Tianjin China School of Computer Science and Technology Soochow University Suzhou China NetEase Fuxi Lab NetEase Inc. Hangzhou China

In multiagent domains, coping with non-stationary agents that change behaviors from time to time is a challenging problem, where an agent is usually required to be able to quickly detect the other agent's policy during online interaction, and then adapt its own policy accordingly. This paper studies efficient policy detecting and reusing techniques when playing against non-stationary agents in Markov games. We propose a new deep BPR+ algorithm by extending the recent BPR+ algorithm with a neural network as the value-function approximator. To detect policy accurately, we propose the rectified belief model taking advantage of the opponent model to infer the other agent's policy from reward signals and its behaviors. Instead of directly storing individual policies as BPR+, we introduce distilled policy network that serves as the policy library in BPR+, using policy distillation to achieve efficient online policy learning and reuse. Deep BPR+ inherits all the advantages of BPR+ and empirically shows better performance in terms of detection accuracy, cumulative rewards and speed of convergence compared to existing algorithms in complex Markov games with raw visual inputs.

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A Novel Framework for FIR Digital Filter Design Based on P system with PSO

A Novel Framework for FIR Digital Filter Design Based on P s...

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international conference on Information Systems and Computer Aided Education (ICISCAE)

作者： Chengfang Zhang Zhen Yue Fengjuan Wang Dan Yan Sichuan Police College Luzhou China Beijing University of Posts and Telecommunications Beijing China Chengdu Company Space star technology co. LTD Chengdu China

ISBN: (纸本)9781538657393;9781538657386

Digital filter plays an important role in the digital signal processing, with a wide range of theoretical and practical application. The essential characteristic of the digital filter is that it can make the useful signal as much as possible all go through, while maximally suppress the useless signal. Due to the structure and function of digital filter, the classical filter design methods will suffer from some shortcomings: slow convergence and local minimums. To overcome the shortcomings in FIR filter design, a novel P systems-based method for optimal FIR filter design under the framework of P system is proposed by combining parallel property of P system, which is named as Tissue P Systems algorithm (TPS). In the proposed TPS model, instead of traditional design methods, a star tissue P system is designed as its computing framework, while the impulse response coefficients of the filter are regarded as the objects in the elementary membranes. Each object in cells expresses a group of filter coefficients to be optimized by using velocity-position model of PSO, and inherent communication mechanism is used to share the objects among different elementary membranes, so as to determine the optimal filter parameters. Low-pass filter (LP), high-pass filter (HP), band-pass filter (BP) and band-stop filter (BS) are employed to verify the effectiveness of the proposed method. Five state-of-the-art design methods, which are Parks-McClellan (PM), real-coded GA (RGA), particle swarm optimization (PSO), differential evolution (DE) and opposition-based harmony search (OHS) are used to exhibit the advantages of the proposed framework. The comparison results demonstrate the proposed TPS model that obtains better performance regarding magnitude response, with minimum stopband ripple, and maximum stopband attenuation. Moreover, the simulation results also show that the proposed FIR filter can close the requirements of ideal filter to the maximum extent.

关键词： Finite impulse response filters Band-pass filters Low pass filters Filtering algorithms Optimization Attenuation

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Error vector magnitude optimization with cubic metric reduction and out-of-band radiation constraints in OFDM systems 7

Error vector magnitude optimization with cubic metric reduct...

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7th IEEE international conference on Signal Processing, Communications and computing, ICSPCC 2017

作者： Yu, Lin Tu, Xiaodong Xie, Jun Meng, Zhonglou Zhu, Xiaodong Gong, Yi National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of China Chengdu China School of Communication and Information Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781538631409

Orthogonal frequency division multiple (OFDM) has been introduced into long term evolution (LTE) because of its high spectral efficiency and robust anti-multipath fading ability. However, a major drawback of OFDM signals is high fluctuations of signal envelope. Peak-to-average power ratio (PAPR) is a well-known measure for the envelope fluctuations. Recently, another metric named cubic metric (CM) has been proposed as a more accurate measure to quantify the fluctuations of signal envelope. This paper proposes a CM reduction method based on convex optimization technique. We consider comprehensively the performance in CM reduction, in-band distortion, and out-ofband radiation with an optimization model, whose objective is to achieve the minimum error vector magnitude (EVM) subject to CM and spectral mask constraints. A customized interior point method (IPM) is proposed to solve the optimization problem. Simulation results validate the good performance of the proposed method in CM reduction and convergence rate. It is shown that, with only three iterations, the proposed algorithm can achieve the minimum EVM under the conditions of given CM and out-of-band radiation. © 2017 IEEE.

关键词： Peak to average power ratio

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