An effective cloud computing model enhancing privacy in cloud computing

被引:1
作者
Chawki, Mohamed [1 ,2 ]
机构
[1] Naif Arab Univ Secur Sci NAUSS, Riyadh, Saudi Arabia
[2] Naif Arab Univ Secur Sci NAUSS, Riyadh 11452, Saudi Arabia
来源
INFORMATION SECURITY JOURNAL | 2024年 / 33卷 / 06期
关键词
Cloud computing; GDPR; hacking; personal data; privacy; SECURITY; IDENTITY;
D O I
10.1080/19393555.2024.2307637
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cloud computing revolutionizes global software, system, infrastructure, and storage accessibility, offering flexibility and cost-effectiveness. This paper explores the pivotal intersection of cloud computing and privacy, presenting a model to enhance cloud privacy. Beginning with an insightful introduction, the paper conducts a comprehensive exploration. A meticulous literature review addresses data privacy intricacies in the cloud context. The study navigates international dimensions of personal data processing, revealing global implications beyond geographical boundaries. Delving into cloud computing's impact on user privacy, it emphasizes the delicate balance between convenience and safeguarding sensitive information. The examination of inherent cloud computing challenges, both technical and legal. A deep dive into recent privacy concerns is complemented by dissecting legal challenges, emphasizing the General Data Protection Regulation's (GDPR) far-reaching impact on the cloud industry. Contributions include a legal and technological overview, technologies for privacy protection, and a global legal framework. The paper identifies challenges and offers information on resolving legal intricacies. Proposed strategies provide a roadmap for industry stakeholders to ensure compliance and mitigate risks. The manuscript concludes with a future perspective on cloud computing's evolving landscape, offering insights into shaping technological advancements.
引用
收藏
页码:635 / 658
页数:24
相关论文
共 65 条
[11]  
Dimitrova M. M., 2022, THESIS
[12]   Security Threats, Defense Mechanisms, Challenges, and Future Directions in Cloud Computing [J].
El Kafhali, Said ;
El Mir, Iman ;
Hanini, Mohamed .
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING, 2022, 29 (01) :223-246
[13]   A hybrid model of Internet of Things and cloud computing to manage big data in health services applications [J].
Elhoseny, Mohamed ;
Abdelaziz, Ahmed ;
Salama, Ahmed S. ;
Riad, A. M. ;
Muhammad, Khan ;
Sangaiah, Arun Kumar .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2018, 86 :1383-1394
[14]   The convergence of IoT and distributed ledger technologies (DLT): Opportunities, challenges, and solutions [J].
Farahani, Bahar ;
Firouzi, Farshad ;
Luecking, Markus .
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2021, 177
[15]   GDPR and the cloud: examining readability deficiencies in cloud computing providers' privacy policies [J].
Gao, Lei ;
Eller, C. Kevin ;
Eggers, Austin F. .
POLICY STUDIES, 2023, 44 (06) :832-854
[16]  
Gauthier Francois, 2023, IEEE Transactions on Signal and Information Processing over Networks, P736, DOI [10.1109/tsipn.2023.3325963, 10.1109/TSIPN.2023.3325963]
[17]   Implementing GDPR-Compliant Surveys Using Blockchain [J].
Goncalves, Ricardo Martins ;
da Silva, Miguel Mira ;
da Cunha, Paulo .
FUTURE INTERNET, 2023, 15 (04)
[18]  
Gupta Rishabh, 2022, IEEE Networking Letters, V4, P217, DOI [10.1109/lnet.2022.3215248, 10.1109/LNET.2022.3215248]
[19]  
Gupta Rishabh, 2022, IEEE Networking Letters, V4, P174, DOI [10.1109/lnet.2022.3200724, 10.1109/LNET.2022.3200724]
[20]   Intuitionistic Fuzzy Similarity-Based Information Measure in the Application of Pattern Recognition and Clustering [J].
Gupta, Rakhi ;
Kumar, Satish .
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS, 2022, 24 (05) :2493-2510