2018 International Conference on Innovations in Information Technology (IIT)最新文献_第4页

Big Data Quality Assessment Model for Unstructured Data 面向非结构化数据的大数据质量评估模型

2018 International Conference on Innovations in Information Technology (IIT) Pub Date : 2018-11-01 DOI: 10.1109/INNOVATIONS.2018.8605945

Ikbal Taleb, M. Serhani, R. Dssouli

{"title":"Big Data Quality Assessment Model for Unstructured Data","authors":"Ikbal Taleb, M. Serhani, R. Dssouli","doi":"10.1109/INNOVATIONS.2018.8605945","DOIUrl":"https://doi.org/10.1109/INNOVATIONS.2018.8605945","url":null,"abstract":"Big Data has gained an enormous momentum the past few years because of the tremendous volume of generated and processed Data from diverse application domains. Nowadays, it is estimated that 80% of all the generated data is unstructured. Evaluating the quality of Big data has been identified to be essential to guarantee data quality dimensions including for example completeness, and accuracy. Current initiatives for unstructured data quality evaluation are still under investigations. In this paper, we propose a quality evaluation model to handle quality of Unstructured Big Data (UBD). The later captures and discover first key properties of unstructured big data and its characteristics, provides some comprehensive mechanisms to sample, profile the UBD dataset and extract features and characteristics from heterogeneous data types in different formats. A Data Quality repository manage relationships between Data quality dimensions, quality Metrics, features extraction methods, mining methodologies, data types and data domains. An analysis of the samples provides a data profile of UBD. This profile is extended to a quality profile that contains the quality mapping with selected features for quality assessment. We developed an UBD quality assessment model that handles all the processes from the UBD profiling exploration to the Quality report. The model provides an initial blueprint for quality estimation of unstructured Big data. It also, states a set of quality characteristics and indicators that can be used to outline an initial data quality schema of UBD.","PeriodicalId":319472,"journal":{"name":"2018 International Conference on Innovations in Information Technology (IIT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126426444","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: 25

STIDes Revisited - Tackling Global Time Shifts and Scaling 重新访问STIDes -处理全局时间偏移和缩放

2018 International Conference on Innovations in Information Technology (IIT) Pub Date : 2018-11-01 DOI: 10.1109/INNOVATIONS.2018.8605951

Marc Haßler, André Pomp, Christian Kohlschein, Tobias Meisen

引用次数: 2

Trust-Based Data Controller for Personal Information Management 基于信任的个人信息管理数据控制器

2018 International Conference on Innovations in Information Technology (IIT) Pub Date : 2018-11-01 DOI: 10.1109/INNOVATIONS.2018.8605979

Upul Jayasinghe, G. Lee, Áine MacDermott

引用次数: 4

IoT Applications: From Mobile Agents to Microservices Architecture 物联网应用:从移动代理到微服务架构

2018 International Conference on Innovations in Information Technology (IIT) Pub Date : 2018-11-01 DOI: 10.1109/INNOVATIONS.2018.8605967

Tasneem Salah, M. Zemerly, C. Yeun, M. Al-Qutayri, Yousof Al-Hammadi

{"title":"IoT Applications: From Mobile Agents to Microservices Architecture","authors":"Tasneem Salah, M. Zemerly, C. Yeun, M. Al-Qutayri, Yousof Al-Hammadi","doi":"10.1109/INNOVATIONS.2018.8605967","DOIUrl":"https://doi.org/10.1109/INNOVATIONS.2018.8605967","url":null,"abstract":"Internet of Things (IoT) is still grabbing the attention of researchers, developers, and organizations. This is due to the rapid increase of connected devices and the major advances seen in information and communication technologies every day. IoT refers to the network of interactive physical and virtual devices connected globally which includes smartphones, sensors, and robots. IoT devices require software adaptation as they are in continuous transition. Mobile Agents can offer adaptable composition for IoT systems. Mobile agents can be used to enable interoperability and global intelligence with smart objects in the Internet of Things. However, mobile agents come with many security concerns in which security protocols can be relatively heavy for IoT devices to handle. As a response, microservice architecture emerged and quickly became a widely used solution. The aim of this architecture is to break the application into a set of smaller independent services. It also allows developers and organizations to have the ability for frequent updates on their services. Studies in the last year showed a massive interest in microservice architectures in the context of IoT and cloud computing solutions. This paper offers a review of how microservices can replace mobile agents and be able to act as agents in IoT systems and highlight the benefits that can be obtained from this solution.","PeriodicalId":319472,"journal":{"name":"2018 International Conference on Innovations in Information Technology (IIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130222240","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

IIT 2018 Copyright Page IIT 2018版权页面

2018 International Conference on Innovations in Information Technology (IIT) Pub Date : 2018-11-01 DOI: 10.1109/innovations.2018.8605962

引用次数: 0

Clone-Resistant Entities for Vehicular Security 车辆安全的抗克隆实体

2018 International Conference on Innovations in Information Technology (IIT) Pub Date : 2018-11-01 DOI: 10.1109/INNOVATIONS.2018.8606035

Ayoub Mars, W. Adi

{"title":"Clone-Resistant Entities for Vehicular Security","authors":"Ayoub Mars, W. Adi","doi":"10.1109/INNOVATIONS.2018.8606035","DOIUrl":"https://doi.org/10.1109/INNOVATIONS.2018.8606035","url":null,"abstract":"Vehicular environment is exposed to many security threats such as illegal copying of software $mathrm {I}mathrm {P},$ counterfeiting of electronic and mechatronic components, and illegal tampering of digital data inside electronic control units (ECUs). The reason is mainly because ECUs are often easily to clone. Physical Unclonable Functions (PUFs) were proposed to be used in many applications such as secure memory-less key storage and devices identification. However, their usage for automotive security is still very limited due to their inconsistency and high implementation cost and complexity. This paper presents a novel VANET security architecture embedding a new consistent digital clone-resistant technology called Secret Unknown Cipher SUC as a physical security anchor. The paper addresses two sample use cases in software update and V2X link protocols fulfilling VANET security architecture and requirements. A secure Over-The-Air software update, and secure V2X communication demonstrate the efficiency of the proposed SUC technology. Since SUC concept is using pure consistent digital structures, it fits perfectly as a low-cost and robust technology in future vehicular IoT environment over the long lifetime of vehicular entities.","PeriodicalId":319472,"journal":{"name":"2018 International Conference on Innovations in Information Technology (IIT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124483234","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: 7

Migrating from SQL to NOSQL Database: Practices and Analysis 从SQL迁移到NOSQL数据库:实践与分析

2018 International Conference on Innovations in Information Technology (IIT) Pub Date : 2018-11-01 DOI: 10.1109/INNOVATIONS.2018.8606019

Fatima Yassine, M. Awad

引用次数: 8

Correlation Analysis of Popularity and Interoperability in Open Source Projects 开源项目中流行度与互操作性的相关性分析

2018 International Conference on Innovations in Information Technology (IIT) Pub Date : 2018-11-01 DOI: 10.1109/INNOVATIONS.2018.8605970

F. Shamsi, Sarah Bamatraf, Talal Rahwan, Z. Aung, D. Svetinovic

引用次数: 0

Predicting Employee Attrition using Machine Learning 使用机器学习预测员工流失

2018 International Conference on Innovations in Information Technology (IIT) Pub Date : 2018-11-01 DOI: 10.1109/INNOVATIONS.2018.8605976

Sarah S. Alduayj, K. Rajpoot

{"title":"Predicting Employee Attrition using Machine Learning","authors":"Sarah S. Alduayj, K. Rajpoot","doi":"10.1109/INNOVATIONS.2018.8605976","DOIUrl":"https://doi.org/10.1109/INNOVATIONS.2018.8605976","url":null,"abstract":"The growing interest in machine learning among business leaders and decision makers demands that researchers explore its use within business organisations. One of the major issues facing business leaders within companies is the loss of talented employees. This research studies employee attrition using machine learning models. Using a synthetic data created by IBM Watson, three main experiments were conducted to predict employee attrition. The first experiment involved training the original class-imbalanced dataset with the following machine learning models: support victor machine (SVM) with several kernel functions, random forest and K-nearest neighbour (KNN). The second experiment focused on using adaptive synthetic (ADASYN) approach to overcome class imbalance, then retraining on the new dataset using the abovementioned machine learning models. The third experiment involved using manual undersampling of the data to balance between classes. As a result, training an ADASYN-balanced dataset with KNN (K = 3) achieved the highest performance, with 0.93 F1-score. Finally, by using feature selection and random forest, F1-score of 0.909 was achieved using 12 features out of a total of 29 features.","PeriodicalId":319472,"journal":{"name":"2018 International Conference on Innovations in Information Technology (IIT)","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124355478","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: 56

IIT 2018 Author Index IIT 2018作者索引

2018 International Conference on Innovations in Information Technology (IIT) Pub Date : 2018-09-01 DOI: 10.1109/innovations.2018.8605983

引用次数: 0