2016 6th International Conference on Computer and Knowledge Engineering (ICCKE)最新文献_第2页

Multi-level Intrusion detection system in cloud environment based on trust level 云环境下基于信任级别的多级入侵检测系统

2016 6th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2016-10-01 DOI: 10.1109/ICCKE.2016.7802122

Z. Salek, F. M. Madani

{"title":"Multi-level Intrusion detection system in cloud environment based on trust level","authors":"Z. Salek, F. M. Madani","doi":"10.1109/ICCKE.2016.7802122","DOIUrl":"https://doi.org/10.1109/ICCKE.2016.7802122","url":null,"abstract":"Cloud computing is a new way to address a wide range of resource needs. Cloud environment provides a framework for dynamic and saleable use of services. It provides access to computing and data storage resources on a pay per usage model. Although there are many known advantages for cloud, security is still one of its most challenging issues. Intrusion detection systems are a common security tool which can also be used in cloud environment to increase the level of security. But conventional intrusion detection systems are not able to fully handle the features of the cloud, such as highly distributed or the variety of services. Also there are differences in security needs for each service or user of different cloud service providers. In this study we proposed a multi-level architecture for intrusion detection system based on different levels of risk level identified for each user. User's risk level can be defined through the computed trust level; as risk level can be reveres of trust level for each user. With identified trust level, users are categorized in to three groups of “High risk”, “Medium risk” and “Low risk”. After the risk levels are identified and users are assigned to a security group, pre-configured IDS agent is assigned to user's virtual machine. IDS are configured in three types of HIDS, MIDS and LIDS in proportion to the security groups described before. These three types of IDS agents vary in number of rules in their rule set, and configuration of rules in each level. A higher level agent for each type of IDS controls the performance and updates rule sets. There is a global agent which collects alert logs to analyze them for detecting correlation in alerts. This architecture improves resource usage, time and packet drop without a tangible impact on accuracy.","PeriodicalId":205768,"journal":{"name":"2016 6th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123408662","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: 6

Hierarchical cooperation of experts in learning from crowds 专家在群体学习中的分层合作

2016 6th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2016-10-01 DOI: 10.1109/ICCKE.2016.7802142

M. Esmaeily, Saeid Abbassi, H. Yazdi, R. Monsefi

引用次数: 1

PPRA: A new pre-fetching and prediction based replication algorithm in data grid PPRA:一种新的基于数据网格预取和预测的复制算法

2016 6th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2016-10-01 DOI: 10.1109/ICCKE.2016.7802149

Mahsa Beigrezaei, A. Haghighat, M. R. Meybodi, Maryam Runiassy

{"title":"PPRA: A new pre-fetching and prediction based replication algorithm in data grid","authors":"Mahsa Beigrezaei, A. Haghighat, M. R. Meybodi, Maryam Runiassy","doi":"10.1109/ICCKE.2016.7802149","DOIUrl":"https://doi.org/10.1109/ICCKE.2016.7802149","url":null,"abstract":"Today, scientific and business applications generate huge amounts of data. Users of data grid, who are distributed all over the grid geographically, need such data. So ensuring the access to this distributed data efficiently is one of the most important challenges in Data grid network. Data replication algorithms are known as the most common method used to overcome this problem. They distribute several copies of a file in the proper site to reduce access time, transfer cost, and bandwidth consumption. In this paper, we put forward a new dynamic replication algorithm called pre-fetching and prediction based replication algorithm (PPRA). PPRA replicates the popular file in suitable sites where next file accessing will happen with more likelihood and statistical methods are used to predict the number of future accesses to a file in each site. It also pre-fetches future needs to requester grid sites in order to increase local accessing to files. Therefore, it leads to lower file access time, means of response time and bandwidth consumption. OptorSim, as a common grid simulator, is used to examine the efficiency of this dynamic replication algorithm. The simulation results show that PPRA can give better average job execution time and bandwidth consumption as compared with NoRep, LRU, LFU, BHR and Modified BHR algorithms.","PeriodicalId":205768,"journal":{"name":"2016 6th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116560592","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: 3

Modular-based measuring semantic quality of ontology 基于模块化的本体语义质量度量

2016 6th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2016-10-01 DOI: 10.1109/ICCKE.2016.7802108

Mina Ardakani Movaghati, A. Barforoush

引用次数: 5

Classification of Iranian paintings using texture analysis 利用纹理分析对伊朗绘画进行分类

2016 6th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2016-10-01 DOI: 10.1109/ICCKE.2016.7802129

S. Keshvari, A. Chalechale

引用次数: 2

HFIaaS: A proposed FPGA Infrastructure as a Service framework using High-Level Synthesis HFIaaS:一种使用高级综合的FPGA基础设施即服务框架

2016 6th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2016-10-01 DOI: 10.1109/ICCKE.2016.7802118

M. Asghari, Amir Rajabzadeh, Majid Dashtbani

{"title":"HFIaaS: A proposed FPGA Infrastructure as a Service framework using High-Level Synthesis","authors":"M. Asghari, Amir Rajabzadeh, Majid Dashtbani","doi":"10.1109/ICCKE.2016.7802118","DOIUrl":"https://doi.org/10.1109/ICCKE.2016.7802118","url":null,"abstract":"This paper presents a framework, called FHIaaS, to provide FPGA Infrastructure as a Service (IaaS) in the cloud. The framework contains two parts, VHDL part, and High-Level Synthesis (HLS) part. The former provides an IaaS including FPGAs and a VHDL synthesis tool. The latter is an HLS tool to convert C programs to VHDL and a VHDL simulator for user-side verification of HLS-driven VHDL codes. Therefore, this framework can provide a service for changing C programs to VHDL codes, simulating the codes, synthesizing the codes, and finally running on FPGAs. In this experimental evaluation, PandA HLS tool is used and CHStone is applied on a VC707 board for workload evaluations. All the applied tests have been done for showing the scalability, the amount of overhead, and the constraints of Virtual Machines (VMs) creations. Furthermore, applied workload for VMs and a Physical Machine (PM) have been compared. The VMs were placed on the same PM to compare them. It has been found that HFIaaS with two VMs was 1.3× better than the PM in total execution time. This study may show that employing this architecture could also be useful for Software as a Service (SaaS). Therefore, considering the proposed architecture, an automatic acceleration system may achieve using HLS tools on a SaaS for full hardware based on FPGA designs.","PeriodicalId":205768,"journal":{"name":"2016 6th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114264893","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

A new anonymous unlinkable mobile payment protocol 一个新的匿名不可链接移动支付协议

2016 6th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2016-10-01 DOI: 10.1109/ICCKE.2016.7802126

F. Zamanian, H. Mala

引用次数: 1

Implementation of artificial features in improvement of biometrics based PPG 人工特征在基于生物识别的PPG改进中的实现

2016 6th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2016-10-01 DOI: 10.1109/ICCKE.2016.7802164

Shima Panahi Moghadam Namini, S. Rashidi

引用次数: 6

Automatic recognition of white blood cells using weighted two phase test sample sparse representation 基于加权两相测试样本稀疏表示的白细胞自动识别

2016 6th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2016-10-01 DOI: 10.1109/ICCKE.2016.7802110

H. Talebi, Alireza Davoudi, A. Mohammadi, M. Menhaj, Alireza Khoshdel, Mehdi Ghorbani

{"title":"Automatic recognition of white blood cells using weighted two phase test sample sparse representation","authors":"H. Talebi, Alireza Davoudi, A. Mohammadi, M. Menhaj, Alireza Khoshdel, Mehdi Ghorbani","doi":"10.1109/ICCKE.2016.7802110","DOIUrl":"https://doi.org/10.1109/ICCKE.2016.7802110","url":null,"abstract":"Microscopic images of blood are very important among the various medical images. One of the most important applications is to diagnosis blood disorders and its types like blood cancer. The main issue to diagnosis blood cancers is white blood globule either mature or not. There are many problem during using image processing to investigate white blood Cell can be mentioned as non-uniformity of colors, different brightness of images, variety of images, different size and texture of images, inherency of white cells in bone marrow images and adjoining of white cells to other blood parts like red blood cell. This paper used Gram-Schmidt orthogonalization process to obtain perpendicular bases that results in segmentation of blood cell kernels. To extract the Cytoplasm borders around the kernel, Variational Level Set Formulation of Active Contours Without Re-initialization method has been used. The main contribution of this paper is that after segmentation, the LBP has been extracted by converting colors in a new space YCBCR on the color factors of each channel so as to extract features. Afterwards by using WTPSSR classification approach and 10-fold valuation the precision of 95.56 has been obtained.","PeriodicalId":205768,"journal":{"name":"2016 6th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"87 46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130378434","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

Face recognition based on modified discriminant independent component analysis 基于改进判别独立分量分析的人脸识别

2016 6th International Conference on Computer and Knowledge Engineering (ICCKE) Pub Date : 2016-10-01 DOI: 10.1109/ICCKE.2016.7802116

Maryam Mollaee, M. Moattar

{"title":"Face recognition based on modified discriminant independent component analysis","authors":"Maryam Mollaee, M. Moattar","doi":"10.1109/ICCKE.2016.7802116","DOIUrl":"https://doi.org/10.1109/ICCKE.2016.7802116","url":null,"abstract":"Independent component analysis (ICA) is a multivariable statistical analysis method which can be applied for face recognition problem. The aim of recognition is to approximately estimate the components from the raw image. Components plays an important role in face recognition systems. Consequently, these components are used for extraction of face image features. However, these features may not be appropriate for classification, since the ICA method does not consider the class information. For the purpose of optimizing the performance of ICA, the discriminant ICA (dICA) method, which is a combination of ICA and LDA methods, is utilized for face recognition in this study. We have also proposed particle swarm optimization method to improve the dICA performance, in which PSO is used instead of the gradient approach for learning dICA. The results of PSO-dICA method confirm our idea in classification experiments compared to other methods. Using proposed method on Yale B dataset, gives an average classification accuracy of 92.169% compared with an accuracy of 91.322% using when dICA and accuracy of 89.77% compared with ICA and accuracy of 86.18% using PCA and also accuracy of 84.76% using LDA.","PeriodicalId":205768,"journal":{"name":"2016 6th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130668515","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: 5