A survey on security issues and solutions at different layers of Cloud computing

Cloud computing offers scalable on-demand services to consumers with greater flexibility and lesser infrastructure investment. Since Cloud services are delivered using classical network protocols and formats over the Internet, implicit vulnerabilities existing in these protocols as well as threats introduced by newer architectures raise many security and privacy concerns. In this paper, we survey the factors affecting Cloud computing adoption, vulnerabilities and attacks, and identify relevant solution directives to strengthen security and privacy in the Cloud environment

Designing Human-Centered Collective Intelligence

Human-Centered Collective Intelligence (HCCI) is an emergent research area that seeks to bring together major research areas like machine learning, statistical modeling, information retrieval, market research, and software engineering to address challenges pertaining to deriving intelligent insights and solutions through the collaboration of several intelligent sensors, devices and data sources. An archetypal contextual CI scenario might be concerned with deriving affect-driven intelligence through multimodal emotion detection sources in a bid to determine the likability of one movie trailer over another. On the other hand, the key tenets to designing robust and evolutionary software and infrastructure architecture models to address cross-cutting quality concerns is of keen interest in the “Cloud” age of today. Some of the key quality concerns of interest in CI scenarios span the gamut of security and privacy, scalability, performance, fault-tolerance, and reliability. I present recent advances in CI system design with a focus on highlighting optimal solutions for the aforementioned cross-cutting concerns. I also describe a number of design challenges and a framework that I have determined to be critical to designing CI systems. With inspiration from machine learning, computational advertising, ubiquitous computing, and sociable robotics, this literature incorporates theories and concepts from various viewpoints to empower the collective intelligence engine, ZOEI, to discover affective state and emotional intent across multiple mediums. The discerned affective state is used in recommender systems among others to support content personalization. I dive into the design of optimal architectures that allow humans and intelligent systems to work collectively to solve complex problems. I present an evaluation of various studies that leverage the ZOEI framework to design collective intelligence

Cloud Security in 21st Century: Current Key Issues in Service Models on Cloud Computing and how to overcome them

Cloud computing is a disruptive innovation which offers new ways to increase capacity and capabilities of the organization’s IT infrastructure. In last few years cloud computing has taken computing industry by storm and many organizations are using cloud computing services to increase the efficiency, decrease their IT budgets and play an important role in defining the IT strategy of their business. Cloud computing offers various benefits such as scalability, elasticity, reducing IT expenditure considerably. Moreover, the architecture of such a utility computing consists of service models and deployment models which have been explained in the paper .Security is a key concern in all the web applications when they start interacting with applications in the public domain. The purpose of this paper is to provide the key security issues in service models of Cloud computing: Infrastructure-as-a-Service, Software-as-a-service and Platform-as-as-service. Finally, the paper will discuss some of the solutions been offered by cloud service providers for the following service models: Software as a service (SaaS), Platform as a service (PaaS) and Infrastructure as a Service (IaaS)

Security comparison of ownCloud, Nextcloud, and Seafile in open source cloud storage solutions

Cloud storage has become one of the most efficient and economical ways to store data over the web. Although most organizations have adopted cloud storage, there are numerous privacy and security concerns about cloud storage and collaboration. Furthermore, adopting public cloud storage may be costly for many enterprises. An open-source cloud storage solution for cloud file sharing is a possible alternative in this instance. There is limited information on system architecture, security measures, and overall throughput consequences when selecting open-source cloud storage solutions despite widespread awareness. There are no comprehensive comparisons available to evaluate open-source cloud storage solutions (specifically owncloud, nextcloud, and seafile) and analyze the impact of platform selections. This thesis will present the concept of cloud storage, a comprehensive understanding of three popular open-source features, architecture, security features, vulnerabilities, and other angles in detail. The goal of the study is to conduct a comparison of these cloud solutions so that users may better understand the various open-source cloud storage solutions and make more knowledgeable selections. The author has focused on four attributes: features, architecture, security, and vulnerabilities of three cloud storage solutions ("ownCloud," "Nextcloud," and "Seafile") since most of the critical issues fall into one of these classifications. The findings show that, while the three services take slightly different approaches to confidentiality, integrity, and availability, they all achieve the same purpose. As a result of this research, the user will have a better understanding of the factors and will be able to make a more informed decision on cloud storage options