Security governance as a service on the cloud

Bryce, Ciarán

doi:10.1186/s13677-019-0148-5

Cited by 5 publications

(3 citation statements)

References 17 publications

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“…Standardised practices can greatly contribute to the future of data privacy and security [20]. Another important advancement could be the creation of systems that can operate efficiently in the absence of an administrator, providing users with independence and confidence in using the system [27]. Increased awareness through detailed documentation and the use of security terminologies can also help protect and observe security in data handling [20].…”

Section: B Defining Responsibilitiesmentioning

confidence: 99%

A Conceptual Evaluation of the Data as Partner (DAP) Framework

Hassan,

Sobnath,

Snell

et al. 2023

2023 IEEE International Smart Cities Conference (ISC2)

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This paper explores the innovative Data As Partner (DAP) philosophy as a transformative approach to organisational data strategy, drawing upon established concepts of information value, technology acceptance, and inclusivity for people with disabilities (PwD) in smart cities. The study conducted a comprehensive systematic review, retrieving 380 relevant documents from diverse databases using specific keywords for precision. After meticulous screening, 20 eligible papers were selected, forming the foundation for deriving the key components of the DAP framework. Subsequently, a qualitative focus group study engaged 18 participants from diverse sectors to evaluate the practical applicability of the DAP conceptual framework. Thematic analysis of the focus group sessions revealed five key themes: practical value, pragmatic performance, ethical perspective, clarity of the framework, and enhancement tools. These findings offer valuable insights for refining the DAP framework and optimising its integration into real-world scenarios, particularly in empowering individuals in smart cities, especially those with disabilities. Future research should explore larger and more diverse samples to generalise findings and assess the framework's long-term impact through longitudinal evaluations. By adopting user-centred methodologies, the DAP framework can be further enhanced as a strategic tool, empowering data to actively participate in organisational decision-making processes.

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Section: B Defining Responsibilitiesmentioning

confidence: 99%

A Conceptual Evaluation of the Data as Partner (DAP) Framework

Hassan,

Sobnath,

Snell

et al. 2023

2023 IEEE International Smart Cities Conference (ISC2)

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“…• Security Governance as a Service (SGaaS). As discussed by [20], SGaaS is yet another solution towards security in cloud. This service automates processes which detect threats, enforces mitigating measures, and guides clients on the steps to take.…”

Section: Inter-cloud Data Security Approaches and Frameworkmentioning

confidence: 99%

Inter-Cloud Data Security Framework, Compliance And Trust

Akhtar

Rauf

Amjad

et al. 2022

Preprint

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Prospects of cloud computing as a technology which optimizes resources, reduces complexity and provides cost effective solutions to its consumers is well established. Future of cloud is ‘cloud of clouds’ where cloud service providers (CSPs) collaborate with each other to provide ever scalable solutions to their customers. However, one most restricting factor towards use of cloud by its consumers is their concerns about data security. Most sensitive to any organization is its data, which thus necessitates a trustworthy framework which could give confidence to these organizations to put their sensitive data on cloud. This paper, therefore, proposed a data security framework which is based on data security controls, driven against the possible data related threats emerging from various inter-cloud use cases. It is a very systematic derivation of data security controls, consolidated as a data security framework. Further in this study, is a proposed mechanism, which can enable CSPs to view compliance to data security controls and overall trustworthiness of other CSPs; thus, enabling them to decide level of interaction that they might feel appropriate to undertake depending upon their data security commitments to their consumers. A Data Security Compliance Monitor service is proposed which measures the compliance to data security framework. This service is also connected with Data Trust as a Service, which measures the trustworthiness of a cloud based on its Total Compliance Value, Users’ Feedback Rating, SLA Rating, Cloud Security Auditor Rating and Incidents History Value. CSPs who subscribe to Cloud Trust as a Service would be able to view Trustworthiness of other CSPs, yet they would be bound to provide access to the service to measure theirs as well. This new approach to data security in inter-cloud is a mix of data security controls, their measure of compliance and based on this, a service, which recommends how much trust can be placed on a CSP for handling data. The proposed solution thus promotes use of inter-cloud for data related requirements.

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“…In recent years, cloud computing has received widespread attention, and the number and types of cloud services it provides been increasing year by year (see Bryce [30] and Song et al [31]). Scholars are considering how to quickly find the cloud services that users need and effectively provide them to users (see Dimitri [32]).…”

Section: Introductionmentioning

confidence: 99%

Approximation analysis of ontology learning algorithm in linear combination setting

Gao

Chen

2020

J Cloud Comp

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In the past ten years, researchers have always attached great importance to the application of ontology to its relevant specific fields. At the same time, applying learning algorithms to many ontology algorithms is also a hot topic. For example, ontology learning technology and knowledge are used in the field of semantic retrieval and machine translation. The field of discovery and information systems can also be integrated with ontology learning techniques. Among several ontology learning tricks, multi-dividing ontology learning is the most popular one which proved to be in high efficiency for the similarity calculation of tree structure ontology. In this work, we study the multi-dividing ontology learning algorithm from the mathematical point of view, and an approximation conclusion is presented under the linear representation assumption. The theoretical result obtained here has constructive meaning for the similarity calculation and concrete engineering applications of tree-shaped ontologies. Finally, linear combination multi-dividing ontology learning is applied to university ontologies and mathematical ontologies, and the experimental results imply that the higher efficiency of the proposed approach in actual applications.

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Security governance as a service on the cloud

Cited by 5 publications

References 17 publications

A Conceptual Evaluation of the Data as Partner (DAP) Framework

A Conceptual Evaluation of the Data as Partner (DAP) Framework

Inter-Cloud Data Security Framework, Compliance And Trust

Approximation analysis of ontology learning algorithm in linear combination setting

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