Big Data Privacy Context: Literature Effects On Secure Informational Assets

This article's objective is the identification of research opportunities in the current big data privacy domain, evaluating literature effects on secure informational assets. Until now, no study has analyzed such relation. Its results can foster science, technologies and businesses. To achieve these objectives, a big data privacy Systematic Literature Review (SLR) is performed on the main scientific peer reviewed journals in Scopus database. Bibliometrics and text mining analysis complement the SLR. This study provides support to big data privacy researchers on: most and least researched themes, research novelty, most cited works and authors, themes evolution through time and many others. In addition, TOPSIS and VIKOR ranks were developed to evaluate literature effects versus informational assets indicators. Secure Internet Servers (SIS) was chosen as decision criteria. Results show that big data privacy literature is strongly focused on computational aspects. However, individuals, societies, organizations and governments face a technological change that has just started to be investigated, with growing concerns on law and regulation aspects. TOPSIS and VIKOR Ranks differed in several positions and the only consistent country between literature and SIS adoption is the United States. Countries in the lowest ranking positions represent future research opportunities.Comment: 21 pages, 9 figure

Advanced Cloud Privacy Threat Modeling

Privacy-preservation for sensitive data has become a challenging issue in cloud computing. Threat modeling as a part of requirements engineering in secure software development provides a structured approach for identifying attacks and proposing countermeasures against the exploitation of vulnerabilities in a system . This paper describes an extension of Cloud Privacy Threat Modeling (CPTM) methodology for privacy threat modeling in relation to processing sensitive data in cloud computing environments. It describes the modeling methodology that involved applying Method Engineering to specify characteristics of a cloud privacy threat modeling methodology, different steps in the proposed methodology and corresponding products. We believe that the extended methodology facilitates the application of a privacy-preserving cloud software development approach from requirements engineering to design

Systematic Review on Security and Privacy Requirements in Edge Computing: State of the Art and Future Research Opportunities

Edge computing is a promising paradigm that enhances the capabilities of cloud computing. In order to continue patronizing the computing services, it is essential to conserve a good atmosphere free from all kinds of security and privacy breaches. The security and privacy issues associated with the edge computing environment have narrowed the overall acceptance of the technology as a reliable paradigm. Many researchers have reviewed security and privacy issues in edge computing, but not all have fully investigated the security and privacy requirements. Security and privacy requirements are the objectives that indicate the capabilities as well as functions a system performs in eliminating certain security and privacy vulnerabilities. The paper aims to substantially review the security and privacy requirements of the edge computing and the various technological methods employed by the techniques used in curbing the threats, with the aim of helping future researchers in identifying research opportunities. This paper investigate the current studies and highlights the following: (1) the classification of security and privacy requirements in edge computing, (2) the state of the art techniques deployed in curbing the security and privacy threats, (3) the trends of technological methods employed by the techniques, (4) the metrics used for evaluating the performance of the techniques, (5) the taxonomy of attacks affecting the edge network, and the corresponding technological trend employed in mitigating the attacks, and, (6) research opportunities for future researchers in the area of edge computing security and privacy

Calm before the storm: the challenges of cloud computing in digital forensics

Cloud computing is a rapidly evolving information technology (IT) phenomenon. Rather than procure, deploy and manage a physical IT infrastructure to host their software applications, organizations are increasingly deploying their infrastructure into remote, virtualized environments, often hosted and managed by third parties. This development has significant implications for digital forensic investigators, equipment vendors, law enforcement, as well as corporate compliance and audit departments (among others). Much of digital forensic practice assumes careful control and management of IT assets (particularly data storage) during the conduct of an investigation. This paper summarises the key aspects of cloud computing and analyses how established digital forensic procedures will be invalidated in this new environment. Several new research challenges addressing this changing context are also identified and discussed