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Device implant attack detection for the Smart Grid Infrastructure

Device implant attack detection for the Smart Grid Infrastru...

引用

international conference on Computer Sciences and convergence Information technology (ICCIT)

作者： Zubair A. Baig Saif Ahmad Department of Computer Engineering King Mongkut's Institute of Technology Ladkrabang Dhahran Saudi Arabia

ISBN: (纸本)9781467308946

The Smart Grid Infrastructure (SGI) is a crucial platform for providing stakeholders of the the electricity grid with intelligent data for sustained and smooth operations. As with every emerging infrastructure, the effects of malicious attacks by the adversary class cannot be overlooked. More so if the extent of damage that may be caused through such attacks can affect large user bases of such technology. A typical SGI may consist of disparate and heterogeneous devices, cooperating and exchanging customer-specific data (readings), in hierarchical manner (from consumer devices to centralized servers through smart meters and data concentrators/aggregators). The interconnection of all such devices (both through wireless and wired channels) to the Internet, exposes the SGI to threats that do indeed exist, and have transpired into malicious attacks against critical information resources during the past two decades. One attack category that may be identified for the SGI is the device implant attack, wherein rogue devices may be installed within a consumer's premises so as to report falsified readings to the smart meter. In this paper, a collaborative approach towards timely detection of such attacks through pattern reconstruction and verification is proposed. The scheme is capable of detecting anomalous readings within a consumer's household, with minimal communication and processing overhead imposed.

关键词： overhead minimal verification Smart meters Verification Minimal Power grids Smart grids INFRASTRUCTURE Consumers CHGB gene reading Information Resources Implants and Prostheses

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Improving Blind Equalization Algorithm for Wireless Communication Systems

Improving Blind Equalization Algorithm for Wireless Communic...

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ACIS international conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed computing (SNPD)

作者： Lijun Sun Ying He School of Information Science and Engineering Henan University of Technology Zhengzhou China Department of Computer Henan Business College Zhengzhou China

Blind equalization technique is an effective approach for canceling the intersymbol interference (ISI) induced by multipath effect in digital wireless communications. The convergence behavior as well as the residual mean square error (MSE) of a blind equalizer is an interesting issue in its design. Perhaps the main drawback of the traditional constant modulus algorithm (CMA) is its relatively slow convergence, especially in the time varying multipath wireless channels. In order to overcome this difficulty, a novel combined blind equalization algorithm based on a normalized iterative method is proposed in this paper. At the beginning of the iteration process, the normalized super-exponential iterative algorithm is utilized to perform an initial equalization, and then the iteration process switches to a decision-directed (DD) algorithm at appropriate values of the mean square error. This switch method can obtain a great improvement in both convergence behavior and residual MSE. The performance of the proposed algorithm is verified through computer simulations.

关键词： Blind equalizers Wireless communication Iterative algorithms convergence Switches Intersymbol interference Mean square error methods Interference cancellation Iterative methods Decision feedback equalizers

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Adaptive Genetic Algorithm Based Optimal PID Controller Design of an Active Magnetic Bearing System

Adaptive Genetic Algorithm Based Optimal PID Controller Desi...

引用

international conference on Innovative computing, Information and Control (ICICIC)

作者： Hung-Cheng Chen Department of Electrical Engineering National Chin-Yi University of Technology Taiwan

This paper proposes a novel adaptive genetic algorithm (AGA) for the multi-objective optimization design of a PID controller and applies it to the control of a real active magnetic bearing (AMB) system. The performances of the AGA are compared with that of the simple genetic algorithm (SGA) in optimizing dynamic responses of the controlled AMB. It shows that because of the proposed AGA can adjust the parameters adaptively according to the value of individual fitness and dispersion degree of population, this algorithm realizes the goals of maintaining diversity in the population and sustaining the convergence capacity of the genetic algorithm. The problems of convergence and prematurity occurred in SGA are then solved. The dynamic model of AMB system for axial motion is also presented, together with experimental and simulation results to verify its availability and good dynamic response.

关键词： Control systems Genetic algorithms Biological cells Gallium Rotors Magnetic levitation Optimization

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An Information Fashion Algorithm Based on Extremal Optimization

An Information Fashion Algorithm Based on Extremal Optimizat...

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international conference on Computational Intelligence and Natural computing, CINC

作者： XiaoGang Fu Jinshou Yu Institute of Automation East China University of Science and Technology Shanghai China

A hybrid Information Fashion Algorithm (IFA) based on Extremal Optimization (EOIFA) with adaptive levy mutation was proposed in this paper. It applied the idea of combination mechanism of global and local search. In the process of the global search, IFA is an evolutionary algorithm based on the simulation of simplified social models and the swarming theory that can quickly approach a approximate optimal solution. During the local search, as a powerful local search capabilities algorithm EO with adaptive leacutevy mutation helps IFA out of local optimal points. Simulation study and its application have proved its capability of strong global search and high immunity against premature convergence. Then EOIFA is applied to optimize PID controller parameters . The obtained results indicate that the new method proposed by this paper is feasible and effective.

关键词： Genetic mutations Automation Three-term control Radiofrequency interference Computational intelligence Evolutionary computation Radio frequency Electron traps convergence Optimization methods

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Design of FIR filter using PSO with CFA and inertia weight approach

Design of FIR filter using PSO with CFA and inertia weight a...

引用

international conference on computing, Communication & Automation (ICCCA)

作者： Mohan Kumar T.N Sasamal Dep't of Electronics and Communication Engg. National Institute of Technology Kurukshetra India

ISBN: (纸本)9781479988914

An efficient method of digital finite impulse response filter design with linear phase using particle swarm optimization (PSO) with constriction factor (CFA) and inertia weight is presented in this paper. An iteration based technique is used to find the optimal solution of the objective function used in this paper. The objective function is the mean square error between the actual filter and the ideal filter. By using the optimization algorithm the deviation of the actual filter from the ideal filter is to be minimized. PSO with CFA and inertia weight approach uses a new equation to update the position and velocity of the particles according to iteration number. In this way particle moves towards the desired solution or optimal solution with in the search space. The simulation results are shown for the design of the filter and convergence behavior with respect to iteration cycle.

关键词： Finite impulse response filters IIR filters Particle swarm optimization Band-pass filters Filtering algorithms convergence

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Neural Future-Dependent Online Mirror Descent 6

Neural Future-Dependent Online Mirror Descent

引用

6th international conference on Algorithms, computing and Artificial Intelligence, ACAI 2023

作者： Xie, Kezhe Liu, Weiming Li, Bin University of Science and Technology of China Hefei China Tencent AI Lab Shenzhen China

ISBN: (纸本)9798400709203

In recent years, many neural-network-based iterative Nash Equilibrium Finding (NEF) algorithms have been proposed for solving large-scale Extensive-Form Imperfect-Information Games (EF-IIGs). These algorithms use neural networks to approximate the values and strategies that change at every iteration, which enables the application of the NEF algorithms in large-scale games. However, previous algorithms usually have to approximate some kind of values that accumulated at every iteration and suffer from the problem of accumulating approximation error as the iteration progresses. As a result, the algorithms are prone to premature convergence and resulting high-exploitability strategies. Additionally, due to the highly dynamic of the approximation target, it may require many training steps for a good approximation in every iteration. In this paper, we propose a new algorithm named Neural FD-OMD. Neural FD-OMD does not approximate cumulative variables, but the strategy at every iteration. So the approximation error is controlled in each iteration and will not propagate to the future iterations. More importantly, Neural FD-OMD limits strategy deviation between iterations. As a result, Neural FD-OMD can use much fewer training steps than previous algorithms to track strategy by fine-tuning the neural network. Experiments on multiple poker games show that Neural FD-OMD outperforms previous NEF algorithms significantly, especially in large-scale games. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Mirrors

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Design and implementation of cloud security defense system with software defined networking technologies

Design and implementation of cloud security defense system w...

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international conference on Information and Communication technology convergence (ICTC)

作者： Sin-Fu Lai Hui-Kai Su Wen-Hsu Hsiao Kim-Joan Chen Dept. of Communications Engineering National Chung Cheng University Chiayi County Taiwan Dept. of Electrical Engineering National Formosa University Yunlin County Taiwan Dept. of Applied Digital Media Wu-Feng University Chiayi County Taiwan Dept. of Electrical Engineering National Chung Cheng University Chiayi County Taiwan

ISBN: (纸本)9781509013265

In recent years, the rapid development of cloud computing and software-defined networking. Cloud security issues are more important, we hope to use the virtualization technology of cloud to implement vIDS and vFirewall so that we can according to the requirements of tenants dynamically adjust and replace hardware equipment with software to cut down the high cost. This paper proposes and we design Security Policy Decision System (SPDS) in the cloud, by using OpenStack to create multiple vIDS to detect the distributed denial of service (DDoS) attacks and combined with multiple vFirewall to filter the attack packets so that we can introduced SDN technology to distribute the flow to multiple vIDS to analyze attack packets or direct traffic elsewhere do processing. We hope to take advantage of SDN in the cloud through vIDS, SPDS (security policy decision system) and vFirewall to effectively alleviate the impact of the DDoS attack in the cloud environment.

关键词： Cloud computing Switches Detectors Monitoring Computer crime

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Developing 3D Annotation Features for 3D Digital Textbooks 4th

Developing 3D Annotation Features for 3D Digital Textbooks

引用

4th international conference on Big Data Applications and Services ( (BigDAS)

作者： Jeong, Jin-Uk Ryu, Gae-A Kim, Mihye Yoo, Kwan-Hee Catholic Univ Daegu Dept Comp Sci Educ Gyongsan Gyeongbuk South Korea Chungbuk Natl Univ Dept Digital Informat & Convergence 410 Seongbongro Cheongju Chungbuk South Korea

ISBN: (纸本)9789811306952;9789811306945

Digital textbooks (DTs) have been established as the major media for future and smart education in South Korea. In general, DTs are implemented using two-dimensional (2D) web-based platforms with embedded 3D content, including images, motion graphics, animations, and video and audio. Recently, these 2D-based DTs have evolved into a 3D-based interface by adopting various types of 3D virtual environments. Accordingly, a number of 3D DTs have been developed;however, these are mainly focused on the implementation of the basic features of DTs, including displaying text and images, viewing pages, zooming in and out, indexing, moving to a certain page, and finding a specific text or object. Furthermore, these have not yet been comprehensively implemented, and further development is required to provide more diverse input and annotation features to facilitate better dynamic interaction between students and DTs. Here, we introduce 3D annotation features that were designed and implemented to enable users to freely annotate on 3D DTs with various forms of input, facilitating dynamic user interactions. These include stylus writing, underlining, highlighting, drawing lines and shapes, and the insertion of textboxes, sound and video files, and voice memos. Students may highlight text or place notes to give commentary on the content of DTs using stylus writings, lines, shapes, text, multimedia files, and voice memos to aid their studying. The 3D annotation features were developed using the eXtensible 3D (X3D) standard, which is an XML-based international standard file format for representing scenes and 3D objects in computer graphics, extended from the virtual reality modeling language (VRML), along with the Java Applet and JavaScript. We aim to enhance student engagement in the learning process by supporting various forms of dynamic interaction features via a natural user interface. We believe that the approaches we describe provide a viable solution to enable 3D annotation on DTs

关键词： Digital textbook 3D digital textbook X3D-based 3D digital textbook 3D annotation

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Hybrid particle swarm optimization algorithm for traveling salesman problem based on ternary optical computer 4

Hybrid particle swarm optimization algorithm for traveling s...

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4th international conference on Machine Learning and Big Data Analytics for IoT Security and Privacy, SPIoT 2023

作者： Sun, Shaojiang Tong, Yihui Qi, Baofeng Wang, Zhehe Wang, Xianchao School of Computer and Information Engineering Fuyang Normal University Fuyang236600 China School of Computer Science and Technology Hainan Tropical Ocean University Sanya572000 China

In recent years, as a novel computer, the ternary optical computer (TOC) has attracted many attentions because of its own mega-parallelism. And with the development of optical computing technology, the exploration of applications based on TOC is also advancing. Travel Salesman problem (TSP) is a classical combinatorial optimization problem, which is also a NP problem. How to solve this problem quickly and efficiently is the major research direction. Particle swarm optimization algorithm (PSO) are prone to premature convergence and insufficient local search capability. To deal with the shortcomings of the problem, we promoted a hybrid algorithm that the hybrid particle swarm optimization algorithm (HPSO) to solve the problem. By introducing greedy strategy, the algorithm generates excellent populations. And the improved Metropolis criterion is added to individual learning and population learning to accept inferior solutions with certain probability, which can effectively increase the population diversity and the mutation adopts the 2-opt optimization strategy, which can solve the path crossing problem effectively, enhance the local optimization capability of the algorithm, and find higher quality solutions. At last, the results show that HPSO solves the TSP with fast convergence speed and high quality of the optimal solution. © 2024 The Authors.

关键词： Particle swarm optimization (PSO)

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Ensemble Classifier based on Decision-Fusion of Multiple Models for Speech Emotion Recognition

Ensemble Classifier based on Decision-Fusion of Multiple Mod...

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international conference on Information and Communication technology convergence

作者： Kyoungju Noh Jiyoun Lim Seungeun Chung Gague Kim Hyuntae Jeong Wearable Computing Research Section Electronics and Telecommunications Research Institute

This paper proposes an ensemble classifier based on decision-fusion of multiple SER (Speech Emotion Recognition) models. The one of the multiple SER models used in this work is a typical categorical learning model for classifying the emotion labels, while the others are A/V (Arousal/Valence) models that recognize multiple A/V states based on the Russell's A/V emotion space. The evaluation performed in this work shows that the SER accuracy of the proposed ensemble classifier that combines each output of categorical model and A/V models is improved compare to the result when each SER model is applied separately.

关键词： Emotion recognition Speech recognition Mel frequency cepstral coefficient Training Biological system modeling Computational modeling Feature extraction

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