Data Security Framework for Protecting Data in Transit and Data at Rest in the Cloud

Percy Nathan Swanzy, Arnold Mashud Abukari, E. Ansong
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Abstract

Data stored in the cloud is particularly vulnerable to attacks, especially when at rest or in transit. This makes the security of data in the cloud in terms of its integrity, confidentiality and availability a major security concern. While existing studies on cloud data security have garnered attention from cybersecurity researchers, there has been limited focus on developing a comprehensive data security framework that integrates both technical and social measures. The general objective of the study was to develop a data security framework for protecting data at rest and data in transit in the cloud. The qualitative research approach was chosen using interviews, archival records and physical artefacts as the source of data for the study. Using the purposive sampling technique, ten cyber security experts within the banking sector with not less than five years of practice were selected. Thematic analysis was used in analysing the collected data which led to the identification of the factors for the development of the framework. The study developed the framework for protecting data at rest and data in motion in the cloud based on the encryption technologies, installation of firewalls and antivirus as well as access control techniques. First Homomorphic encryption technologies were implemented in the framework to secure both storage devices and web connections. Other security factors were installation of firewall and antivirus. The findings revealed that access and usage control strategies integrate user identification and authentication. Additionally, these strategies incorporate safeguards for confidentiality, data integrity, and non-repudiation, securing both data-at-rest and data-in-motion. The findings also indicated that audit trails provide electronic records that offer security support documentation and history that is used to authenticate operational actions and mitigate challenges with non-compliance. Additionally, the findings emphasized the importance of social strategies such as staff training and industry collaboration in enhancing data security. These strategies aim to raise awareness of security threats and inform best practices for securing organizational data. The study recommends that banks consider both technical and social aspects when implementing data protection security measures especially implementing homomorphic encryption to secure data and implement Cyber Security training policies.
保护云中传输数据和静态数据的数据安全框架
存储在云中的数据特别容易受到攻击,尤其是在静止或传输过程中。因此,云数据在完整性、保密性和可用性方面的安全性成为一个主要的安全问题。虽然有关云数据安全的现有研究已引起网络安全研究人员的关注,但在制定一个综合技术和社会措施的全面数据安全框架方面,关注点还很有限。本研究的总体目标是开发一个数据安全框架,以保护云中的静态数据和传输中的数据。本研究选择了定性研究方法,使用访谈、档案记录和实物作为数据来源。采用目的性抽样技术,选取了银行业内从业不少于五年的十名网络安全专家。在分析收集到的数据时采用了主题分析法,从而确定了制定框架的因素。研究基于加密技术、安装防火墙和杀毒软件以及访问控制技术,制定了保护云中静态数据和动态数据的框架。首先在框架中采用了同态加密技术,以确保存储设备和网络连接的安全。其他安全因素包括安装防火墙和杀毒软件。研究结果表明,访问和使用控制策略整合了用户识别和身份验证。此外,这些战略还包括保密性、数据完整性和不可抵赖性的保障措施,以确保静态数据和动态数据的安全。调查结果还表明,审计跟踪提供电子记录,提供安全支持文件和历史记录,用于验证操作行为和减少违规挑战。此外,调查结果还强调了员工培训和行业合作等社会战略在加强数据安全方面的重要性。这些战略旨在提高对安全威胁的认识,并为确保组织数据安全的最佳做法提供信息。研究建议银行在实施数据保护安全措施时,同时考虑技术和社会两个方面,特别是实施同态加密以确保数据安全,并实施网络安全培训政策。
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