Secure Dynamic Cloud-based Collaboration with Hierarchical Access

In recent years, the Cloud has emerged as an attractive way of hosting and delivering services over the Internet. This has resulted in a renewed focus on information security in the case where data is stored in the virtual space of the cloud and is not physically accessible to the customer. Through this thesis the boundaries of securing data in a cloud context, while retaining the benefits of the cloud, are explored. The thesis addresses the increasing security concerns of migrating to the cloud andutilising it for data storage.The research of this thesis is divided into three separate areas: securing data in an untrusted cloud environment, ensuring data access control in the cloud, and securing data outside the cloud in the user's environment. Each area is addressed by separate conceptual designs. Together these comprise a secure dynamic cloud-based collaboration environment with hierarchical access. To further validate the conceptual designs, proof of concept prototypes have been constructed.The conceptual designs have been devised by exploring and extending the boundaries of existing secure data-storage schemes, and then combining these with well-known security principles and cutting-edge research within the field of cryptography. The results of this thesis are feasible conceptual designs for a cloud-based dynamic collaboration environment. The conceptual designs address the challenges of secure cloud-based storage and allow the benefits of cloud-based storage to be utilised. Furthermore, this thesis provides a solid foundation for further work within this field

A Framework for Uncertain Cloud Data Security and Recovery Based on Hybrid Multi-User Medical Decision Learning Patterns

Machine learning has been supporting real-time cloud based medical computing systems. However, most of the computing servers are independent of data security and recovery scheme in multiple virtual machines due to high computing cost and time. Also, this cloud based medical applications require static security parameters for cloud data security. Cloud based medical applications require multiple servers to store medical records or machine learning patterns for decision making. Due to high Uncertain computational memory and time, these cloud systems require an efficient data security framework to provide strong data access control among the multiple users. In this work, a hybrid cloud data security framework is developed to improve the data security on the large machine learning patterns in real-time cloud computing environment. This work is implemented in two phases’ i.e. data replication phase and multi-user data access security phase. Initially, machine decision patterns are replicated among the multiple servers for Uncertain data recovering phase. In the multi-access cloud data security framework, a hybrid multi-access key based data encryption and decryption model is implemented on the large machine learning medical patterns for data recovery and security process. Experimental results proved that the present two-phase data recovering, and security framework has better computational efficiency than the conventional approaches on large medical decision patterns

D:A4.1 Socio-economic impact assessment

The executive summary ends with six concise recommendations for facilitating more accountability for data management in cloud ecosystems: 1. Provide a stronger legal base for and enforcement of data protection and accountable behavior; 2. Facilitate independent auditing of responsible data stewardship; 3. Increase public awareness of the need for accountability; 4. Balance existing information asymmetries via partnerships; 5. Focus on larger enterprises working in the public sector first, as these can serve as an example for other types of businesses; 6. Demonstrate how A4Cloud tools and mechanisms can be turned into a business model in order to encourage greater uptake and use

Elastic Business Process Management: State of the Art and Open Challenges for BPM in the Cloud

With the advent of cloud computing, organizations are nowadays able to react rapidly to changing demands for computational resources. Not only individual applications can be hosted on virtual cloud infrastructures, but also complete business processes. This allows the realization of so-called elastic processes, i.e., processes which are carried out using elastic cloud resources. Despite the manifold benefits of elastic processes, there is still a lack of solutions supporting them. In this paper, we identify the state of the art of elastic Business Process Management with a focus on infrastructural challenges. We conceptualize an architecture for an elastic Business Process Management System and discuss existing work on scheduling, resource allocation, monitoring, decentralized coordination, and state management for elastic processes. Furthermore, we present two representative elastic Business Process Management Systems which are intended to counter these challenges. Based on our findings, we identify open issues and outline possible research directions for the realization of elastic processes and elastic Business Process Management.Comment: Please cite as: S. Schulte, C. Janiesch, S. Venugopal, I. Weber, and P. Hoenisch (2015). Elastic Business Process Management: State of the Art and Open Challenges for BPM in the Cloud. Future Generation Computer Systems, Volume NN, Number N, NN-NN., http://dx.doi.org/10.1016/j.future.2014.09.00

Framework for Security Transparency in Cloud Computing

The migration of sensitive data and applications from the on-premise data centre to a cloud environment increases cyber risks to users, mainly because the cloud environment is managed and maintained by a third-party. In particular, the partial surrender of sensitive data and application to a cloud environment creates numerous concerns that are related to a lack of security transparency. Security transparency involves the disclosure of information by cloud service providers about the security measures being put in place to protect assets and meet the expectations of customers. It establishes trust in service relationship between cloud service providers and customers, and without evidence of continuous transparency, trust and confidence are affected and are likely to hinder extensive usage of cloud services. Also, insufficient security transparency is considered as an added level of risk and increases the difficulty of demonstrating conformance to customer requirements and ensuring that the cloud service providers adequately implement security obligations. The research community have acknowledged the pressing need to address security transparency concerns, and although technical aspects for ensuring security and privacy have been researched widely, the focus on security transparency is still scarce. The relatively few literature mostly approach the issue of security transparency from cloud providers’ perspective, while other works have contributed feasible techniques for comparison and selection of cloud service providers using metrics such as transparency and trustworthiness. However, there is still a shortage of research that focuses on improving security transparency from cloud users’ point of view. In particular, there is still a gap in the literature that (i) dissects security transparency from the lens of conceptual knowledge up to implementation from organizational and technical perspectives and; (ii) support continuous transparency by enabling the vetting and probing of cloud service providers’ conformity to specific customer requirements. The significant growth in moving business to the cloud – due to its scalability and perceived effectiveness – underlines the dire need for research in this area. This thesis presents a framework that comprises the core conceptual elements that constitute security transparency in cloud computing. It contributes to the knowledge domain of security transparency in cloud computing by proposing the following. Firstly, the research analyses the basics of cloud security transparency by exploring the notion and foundational concepts that constitute security transparency. Secondly, it proposes a framework which integrates various concepts from requirement engineering domain and an accompanying process that could be followed to implement the framework. The framework and its process provide an essential set of conceptual ideas, activities and steps that can be followed at an organizational level to attain security transparency, which are based on the principles of industry standards and best practices. Thirdly, for ensuring continuous transparency, the thesis proposes an essential tool that supports the collection and assessment of evidence from cloud providers, including the establishment of remedial actions for redressing deficiencies in cloud provider practices. The tool serves as a supplementary component of the proposed framework that enables continuous inspection of how predefined customer requirements are being satisfied. The thesis also validates the proposed security transparency framework and tool in terms of validity, applicability, adaptability, and acceptability using two different case studies. Feedbacks are collected from stakeholders and analysed using essential criteria such as ease of use, relevance, usability, etc. The result of the analysis illustrates the validity and acceptability of both the framework and tool in enhancing security transparency in a real-world environment

Enhancing Cloud Security and Privacy: The Cloud Audit Problem

Publisher PD

Comparative Analysis of Data Security and Cloud Storage Models Using NSL KDD Dataset

Cloud computing is becoming increasingly important in many enterprises, and researchers are focusing on safeguarding cloud computing. Due to the extensive variety of service options it offers, A significant amount of interest from the scientific community has been focused on cloud computing. The two biggest problems with cloud computing are security and privacy. The key challenge is maintaining privacy, which expands rapidly with the number of users. A perfect security system must efficiently ensure each security aspect. This study provides a literature review illustrating the security in the cloud with respect to privacy, integrity, confidentiality and availability, and it also provides a comparison table illustrating the differences between various security and storage models with respect to the approaches and components of the models offered. This study also compares Naïve Bayes and SVM on the accuracy, recall and precision metrics using the NSL KDD dataset