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检索条件"任意字段=7th IASTED International Conference on Advances in Computer Science and Technology"

共 1504 条记录，以下是581-590 订阅

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Semi-Supervised Outlier Detection and Deep Feature Extraction for Detecting Cyber-Attacks in Smart Grids Using PMU Data 17th

Semi-Supervised Outlier Detection and Deep Feature Extractio...

引用

17th international conference on Information technology: New Generations, ITNG 2020

作者： Qi, Ruobin Rasband, Craig Zheng, Jun Longoria, Raul Department of Computer Science and Engineering New Mexico Institute of Mining and Technology SocorroNM United States Department of Computer Science Prairie View A&M University PrairieTX United States

ISBN: (纸本)9783030430191

Smart grids are facing many challenges including cyber-attacks which can cause devastating damages to the grids. Existing machine learning based approaches for detecting cyber-attacks in smart grids are mainly based on supervised learning, which needs representative instances from various attack types to obtain good detection models. In this paper, we investigated semi-supervised outlier detection algorithms for this problem which only use instances of normal events for model training. Data collected by phasor measurement units (PMUs) was used for training the detection model. the semi-supervised outlier detection algorithms were augmented with deep feature extraction for enhanced detection performance. Our results show that semi-supervised outlier detection algorithms can perform better than popular supervised algorithms. Deep feature extraction can significantly improve the performance of semi-supervised algorithms for detecting cyber-attacks in smart grids. © Springer Nature Switzerland AG 2020.

关键词： Feature extraction

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An application of WSN in smart aquaculture farming 4th

An application of WSN in smart aquaculture farming

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4th international conference on Research in Intelligent and Computing in Engineering, RICE 2019

作者： Huy, thong Nguyen Tuan, Khanh Nguyen Trung, thanh Tran Department of Global Production Engineering and Management Faculty of Engineering Vietnamese-German University Thu Dau MotBinh Duong Viet Nam Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Taipei Taiwan

ISBN: (纸本)9789811527791

Aquaculture farming carries one of the most important roles in the Vietnam economy. this paper focuses on the implementation of wireless sensor network (WSN) in shrimp farms, including the automation, remote control, and monitoring of the pond parameters. Using embedded computer Raspberry Pi 3, wireless communication modules Xbee S2c, the system can help farmers control pumps, actuator, and light via their web browser. Besides, parameters of the pond such as temperature and illuminating power are updated on the Internet via cloud service. the implementation of this project is expected to reduce energy consumption, human resource, and fast reaction to the change of the production pond, especially for large farms with multiple ponds. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Wireless sensor networks

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Adaptive thresholding skin lesion segmentation with gabor filters and principal component analysis 4th

Adaptive thresholding skin lesion segmentation with gabor fi...

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4th international conference on Research in Intelligent and Computing in Engineering, RICE 2019

作者： thanh, Dang N. H. Hien, Nguyen Ngoc Surya Prasath, V.B. Erkan, Uğur Khamparia, Aditya Department of Information Technology Hue College of Industry Hue Viet Nam Center of Occupational Skills Development Dong Thap University Cao Lanh Viet Nam Division of Biomedical Informatics Cincinnati Children’s Hospital Medical Center Cincinnati United States Department of Pediatrics University of Cincinnati CincinnatiOH United States Department of Biomedical Informatics College of Medicine University of Cincinnati Cincinnati United States Department of Electrical Engineering and Computer Science University of Cincinnati Cincinnati United States Computer Engineering Faculty of Engineering Karamanoğlu Mehmetbey University Karaman Turkey School of Computer Science and Engineering Lovely Professional University PhagwaraPunjab India

ISBN: (纸本)9789811527791

In this article, we study and propose an adaptive thresholding segmentation method for dermoscopic images with Gabor filters and Principal Component Analysis. the Gabor filters is used for extracting statistical features of image and the Principal Component Analysis is applied for transforming features to various bases. In experiments, we implement tests with the ISIC dataset. Segmentation results are assessed by the Dice and the Jaccard similarities. We also compare the proposed method to other similar methods to prove its own effectiveness. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Gabor filters

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Ensemble Recognition Based on the Harmonic Information Gain Ratio for Unsafe Behaviors in Coal Mines 12th

Ensemble Recognition Based on the Harmonic Information Gain ...

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12th international conference on advances in Swarm Intelligence, ICSI 2021

作者： Cheng, Jian Jiao, Botao Guo, Yinan Wang, Shijie Research Institute of Mine Big Data China Coal Research Institute Beijing100013 China State Key Laboratory of Coal Mining and Clean Utilization Beijing100013 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China Beijing100083 China Shandong Energy Group Co. Ltd. Jinan250014 China

ISBN: (纸本)9783030788100

More than 90% accidents occurred in coal mine are caused by unsafe behaviors of human. How to effectively identify unsafe behaviors and decrease the possibility of their occurrence is the fundamental of avoiding accidents. However, the number of unsafe behaviors is far less than that of safe ones in a behavior dataset of coal mine. Serious imbalance has a negative impact on recognition efficiency and accuracy. To address the problem, the harmonic information gain ratio is defined by introducing the degree of imbalance into traditional information gain, and the corresponding feature selection method is presented. By integrating it into Underbagging, a novel ensemble recognition based on the harmonic information gain ratio for unsafe behaviors is presented, with the purpose of avoiding information loss caused by feature reduction and guaranteeing recognition accuracy. Based on a sub-dataset obtained by undersampling, the optimal features subset is selected by the proposed feature selection method, and employed to train a base classifier built by support vector machine. the weighted sum of all base classifiers output forms final recognition result. Each weight is calculated from the corresponding harmonic information gain ratio. Experimental results on UCI dataset and a behavior dataset for a particular coal mine indicate that the proposed ensemble recognition method outperforms the others, especially for a dataset with high imbalance ratio. © 2021, Springer Nature Switzerland AG.

关键词： Coal mines

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Multi-label Classification of Short Text Based on Similarity Graph and Restart Random Walk Model 11th

Multi-label Classification of Short Text Based on Similarity...

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11th IFIP TC 12 international conference on Intelligent Information Processing, IIP 2020

作者： Li, Xiaohong Yang, Fanyi Ma, Yuyin Ma, Huifang College of Computer Science and Engineering Northwest Normal University Lanzhou China

ISBN: (纸本)9783030469306

A multi-label classification method of short text based on similarity graph and restart random walk model is proposed. Firstly, the similarity graph is created by using data and labels as the node, and the weights on the edges are calculated through an external knowledge, so the initial matching degree of between the sample and the label set is obtained. After that, we build a label dependency graph with labels as vertices, and using the previous matching degree as the initial prediction value to calculate the relationship between the sample and each node until the probability distribution becomes stable. Finally, the obtained relationship vector is the label probability distribution vector of the sample predicted by the method in this paper. Experimental results show that we provides a more efficient and reliable multi-label short-text classification algorithm. © 2020, IFIP international Federation for Information Processing.

关键词： Classification (of information)

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An Evaluation of One-Class Feature Selection and Classification for Zero-Day Android Malware Detection 17th

An Evaluation of One-Class Feature Selection and Classificat...

引用

17th international conference on Information technology: New Generations, ITNG 2020

作者： Wang, Yang Zheng, Jun Ultramain Systems Inc. AlbuquerqueNM United States Department of Computer Science and Engineering New Mexico Institute of Mining and Technology SocorroNM United States

ISBN: (纸本)9783030430191

Security has become a serious problem for Android system as the number of Android malware increases rapidly. A great amount of effort has been devoted to protect Android devices against the threats of malware. Majority of the existing work use two-class classification methods which suffer the overfitting problem due to the lack of malicious samples. this will result in poor performance of detecting zero-day malware attacks. In this paper, we evaluated the performance of various one-class feature selection and classification methods for zero-day Android malware detection. Unlike two-class methods, one-class methods only use benign samples to build the detection model which overcomes the overfitting problem. Our results demonstrate the capability of the one-class methods over the two-class methods in detecting zero-day Android malware attacks. © Springer Nature Switzerland AG 2020.

关键词： Android malware

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A study of epidemic approach for worm propagation in wireless sensor network 4th

A study of epidemic approach for worm propagation in wireles...

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4th international conference on Research in Intelligent and Computing in Engineering, RICE 2019

作者： Awasthi, Shashank Kumar, Naresh Srivastava, Pramod Kumar Department of Computer Science Engineering Galgotia’s University Greater Noida India Department of Computer Science Engineering G. L. Bajaj Institute of Technology & Management Greater Noida India Department of Computer Science Engineering Rajkiya Engineering College Azamagarh India

ISBN: (纸本)9789811527791

Wireless sensor networks (WSNs) are novel expansive-scale wireless network systems that comprise conveyed, self-sorting out, low-control, ease, small-sensor gadgets that help to gather data through framework-less wireless network system. Nowadays, propagation of worms is a major issue in wireless sensor network because a large number of attackers (virus) are present in the network by which the total network or communication will be affected. Sometimes network limitation and node boundaries are also responsible for lost information. For means of perfect propagation of worm, some data is required (about the node and network), that is, knowledge of local concept, power of node, as well as network, distribution concept, and timing. In this paper we try to represent the basic concept of different kinds of propagation model for propagation of worm using wireless sensor network. Here we study an epidemic approach for worm propagation in wireless sensor networks (WSNs) to represent the concept of worm propagation in different applications or propagation from one node to another node or from one node to the entire network. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Viruses

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Deriving Scalability Tactics for Development of Data-Intensive Systems 17th

Deriving Scalability Tactics for Development of Data-Intensi...

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17th international conference on Information technology: New Generations, ITNG 2020

作者： Nanda, Smruti Priyambada Reza, Hassan School of Electrical Engineering and Computer Science University of North Dakota Grand Forks United States

ISBN: (纸本)9783030430191

Enforcing scalability quality attribute to an existing developed data-intensive software system is a difficult task. this paper proposes a methodology that reverses the traditional procedure by reframing scalability tactics. the scalability tactics are derived from existing scalable data-intensive system development practices and are presented in the format of a utility tree. these tactics can be analyzed against architectural patterns which are design decessions for software development. this will maximize the hold of scalability attributes in end software product before its actual development. the tactics derived in this paper will help an architect to have the correct design decision for data-intensive system development. Tactics alone may not solve the problem but when contrasted with architectural patterns, they will help in determining if the system is scalable. © Springer Nature Switzerland AG 2020.

关键词： Scalability

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Understanding Security Risks When Exchanging Medical Records Using IHE 17th

Understanding Security Risks When Exchanging Medical Records...

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17th international conference on Information technology: New Generations, ITNG 2020

作者： Bhatia, Simranjit Ibrahim, Ahmed Department of Computer Science University of Virginia CharlottesvilleVA United States

ISBN: (纸本)9783030430191

In today’s digital world, it is common to exchange sensitive data between different parties. As technology continues to advance, electronic health records (EHRs) are just one of several types of information that is being exchanged across multiple channels. the exchange of this information is crucial to provide better patient care across different healthcare providers. However, given the sensitive nature of these documents, it is also important that the manner in which EHRs are exchanged is also secure. In this paper, we investigate the current standards that are being used to support the transfer of EHRs across different parties, as proposed by a standard-setting organization known as Integrating the Healthcare Enterprise (IHE). We give an overview of how each protocol functions, then show potential security risks that might be encountered by using the current standards. these security risks are: vendor dependence, insecure encryption configurations, and the inability to verify third-party exchanges of healthcare information. © Springer Nature Switzerland AG 2020.

关键词： Cryptography

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A Robust Lightweight ECC-Based three-Way Authentication Scheme for IoT in Cloud 6th

A Robust Lightweight ECC-Based Three-Way Authentication Sche...

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6th international conference on Advanced Computing, Networking, and Informatics, ICACNI 2018

作者： Chatterjee, Sayantan Samaddar, Shefalika Ghosh Department of Computer Science and Engineering National Institute of Technology Sikkim737139 India

ISBN: (纸本)9789811396793

Internet of things is an evolving technology which connects multiple embedded devices with a remote server over Internet. Due to limited capacity of embedded devices, it is important to delegate resources from third-party platform. Lots of research is going on to connect IoT devices to a wide resource pool such as cloud. this integration of IoT with cloud services has enormous possibility for future as resource-intensive processes can be delegated to cloud platform instead of executing in IoT node. this paper proposes a lightweight three-way authentication scheme for IoT in cloud where mutual authentication between IoT node and user’s smart device is performed by remote IoT gateway in cloud. the proposed scheme uses a three-factor user authentication to prevent device theft attack and ECC-based communication protocols to ensure less computation and communication overhead. Moreover, the proposed scheme is analysed to show that it is secure against existing relevant cryptographic attacks. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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