Engineering Commons^™

Cloud-Based Machine Learning And Sentiment Analysis, Emmanuel C. Opara

Electronic Theses and Dissertations

The role of a Data Scientist is becoming increasingly ubiquitous as companies and institutions see the need to gain additional insights and information from data to make better decisions to improve the quality-of-service delivery to customers. This thesis document contains three aspects of data science projects aimed at improving tools and techniques used in analyzing and evaluating data. The first research study involved the use of a standard cybersecurity dataset and cloud-based auto-machine learning algorithms were applied to detect vulnerabilities in the network traffic data. The performance of the algorithms was measured and compared using standard evaluation metrics. The second …

Leveraging Cloud-Based Nfv And Sdn Platform Towards Quality-Driven Next-Generation Mobile Networks, Hassan Hawilo

Electronic Thesis and Dissertation Repository

Network virtualization has become a key approach for Network Service Providers (NSPs) to mitigate the challenge of the continually increasing demands for network services. Tightly coupled with their software components, legacy network devices are difficult to upgrade or modify to meet the dynamically changing end-user needs. To virtualize their infrastructure and mitigate those challenges, NSPs have started to adopt Software Defined Networking (SDN) and Network Function Virtualization (NFV). To this end, this thesis addresses the challenges faced on the road of transforming the legacy networking infrastructure to a more dynamic and agile virtualized environment to meet the rapidly increasing demand …

Data Security And Privacy In Smart Grid, Yue Tong

Doctoral Dissertations

This dissertation explores novel data security and privacy problems in the emerging smart grid.

The need for data security and privacy spans the whole life cycle of the data in the smart grid, across the phases of data acquisition, local processing and archiving, collaborative processing, and finally sharing and archiving. The first two phases happen in the private domains of an individual utility company, where data are collected from the power system and processed at the local facilities. When data are being acquired and processed in the private domain, data security is the most critical concern. The key question is …