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International Journal of High Performance Computing and Networking最新文献

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A split and merge video cryptosystem technique based on dual hash functions and Lorenz system 基于对偶哈希函数和洛伦兹系统的分割合并视频密码技术
International Journal of High Performance Computing and Networking Pub Date : 1900-01-01 DOI: 10.1504/ijhpcn.2021.10044886
Ashraf Abu Ein, Monther H. Al Bsool, Ma'moun Al Smadi, Obaida M. Al Hazaimeh
{"title":"A split and merge video cryptosystem technique based on dual hash functions and Lorenz system","authors":"Ashraf Abu Ein, Monther H. Al Bsool, Ma'moun Al Smadi, Obaida M. Al Hazaimeh","doi":"10.1504/ijhpcn.2021.10044886","DOIUrl":"https://doi.org/10.1504/ijhpcn.2021.10044886","url":null,"abstract":"","PeriodicalId":384857,"journal":{"name":"International Journal of High Performance Computing and Networking","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114962022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Parallel solution of the discretized and linearized G-heat equation 离散化和线性化g -热方程的并行解
International Journal of High Performance Computing and Networking Pub Date : 1900-01-01 DOI: 10.1504/IJHPCN.2018.088880
P. Spitéri, Amar Ouaoua, M. Chau, H. Boutabia
{"title":"Parallel solution of the discretized and linearized G-heat equation","authors":"P. Spitéri, Amar Ouaoua, M. Chau, H. Boutabia","doi":"10.1504/IJHPCN.2018.088880","DOIUrl":"https://doi.org/10.1504/IJHPCN.2018.088880","url":null,"abstract":"The present study deals with the numerical solution of the G-heat equation. Since the G-heat equation is defined in an unbounded domain, we firstly state that the solution of the G-heat equation defined in a bounded domain converges to the solution of the G-heat equation when the measure of the domain tends to infinity. Moreover, after time discretisation by an implicit time marching scheme, we define a method of linearisation of each stationary problem, which leads to the solution of a large scale algebraic system. A unified approach analysis of the convergence of the sequential and parallel relaxation methods is given. Finally, we present the results of numerical experiments.","PeriodicalId":384857,"journal":{"name":"International Journal of High Performance Computing and Networking","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127131730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Performance evaluation of OpenMPs target construct on GPUs OpenMPs目标结构在gpu上的性能评价
International Journal of High Performance Computing and Networking Pub Date : 1900-01-01 DOI: 10.1504/IJHPCN.2017.10009068
Vivek Sarkar, R. Ho, Ettore Tiotto, J. Shirako, Akihiro Hayashi
{"title":"Performance evaluation of OpenMPs target construct on GPUs","authors":"Vivek Sarkar, R. Ho, Ettore Tiotto, J. Shirako, Akihiro Hayashi","doi":"10.1504/IJHPCN.2017.10009068","DOIUrl":"https://doi.org/10.1504/IJHPCN.2017.10009068","url":null,"abstract":"","PeriodicalId":384857,"journal":{"name":"International Journal of High Performance Computing and Networking","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130101679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A novel Monte Carlo based neural network model for electricity load forecasting 一种新的基于蒙特卡罗的电力负荷预测神经网络模型
International Journal of High Performance Computing and Networking Pub Date : 1900-01-01 DOI: 10.1504/IJHPCN.2018.10011508
Qingguo Zhou, Binbin Yong, Fucun Li, Jianqing Wu, Zijian Xu, Jun Shen, Huaming Chen
{"title":"A novel Monte Carlo based neural network model for electricity load forecasting","authors":"Qingguo Zhou, Binbin Yong, Fucun Li, Jianqing Wu, Zijian Xu, Jun Shen, Huaming Chen","doi":"10.1504/IJHPCN.2018.10011508","DOIUrl":"https://doi.org/10.1504/IJHPCN.2018.10011508","url":null,"abstract":"","PeriodicalId":384857,"journal":{"name":"International Journal of High Performance Computing and Networking","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115838191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Security in the internet of things: botnet detection in software-defined networks by deep learning techniques 物联网中的安全:通过深度学习技术在软件定义网络中检测僵尸网络
International Journal of High Performance Computing and Networking Pub Date : 1900-01-01 DOI: 10.1504/ijhpcn.2019.10026769
Ivan Letteri, G. D. Penna, Giovanni De Gasperis
{"title":"Security in the internet of things: botnet detection in software-defined networks by deep learning techniques","authors":"Ivan Letteri, G. D. Penna, Giovanni De Gasperis","doi":"10.1504/ijhpcn.2019.10026769","DOIUrl":"https://doi.org/10.1504/ijhpcn.2019.10026769","url":null,"abstract":"The diffusion of the internet of things (IoT) is making cyber-physical smart devices an element of everyone's life, but also exposing them to malware designed for conventional web applications, such as botnets. Botnets are one of the most widespread and dangerous malware, so their detection is an important task. Many works in this context make use of general malware detection techniques and rely on old or biased traffic samples, making their results not completely reliable. Moreover, software-defined networking (SDN), which is increasingly replacing conventional networking especially in the IoT, limits the features that can be used to detect botnets. We propose a botnet detection methodology based on deep learning techniques, tested on a new, SDN-specific dataset with a high (up to 97%) classification accuracy. Our algorithms have been implemented on two state-of-the-art frameworks, i.e., Keras and TensorFlow, so we are confident that our results are reliable and easily reproducible.","PeriodicalId":384857,"journal":{"name":"International Journal of High Performance Computing and Networking","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122992333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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