Abstract: Cloud computing has emerged as a powerful paradigm that provides scalable, flexible, and cost-effective solutions for handling vast amounts of data storage, processing, and accessibility. As cloud services gain increasing adoption among businesses and individuals, the paramount concern becomes data security. The "Data Security Model for Cloud Computing" project has been devised to tackle the critical challenges of safeguarding sensitive information stored and processed within cloud environments.

This research project introduces a comprehensive data security model meticulously designed to ensure the confidentiality, integrity, and availability of data in cloud computing environments. The proposed model encompasses multiple layers of security measures, addressing both technical and administrative aspects to shield data from unauthorized access, data breaches, and other potential threats. The first layer concentrates on access control mechanisms, employing Role-based access control (RBAC) and attribute-based access control (ABAC) to restrict data access solely to authorized users. Additionally, multi-factor authentication (MFA) is integrated to add an extra layer of security, mitigating the risk of unauthorized access due to compromised credentials. The second layer emphasizes data encryption techniques, securing all data at rest, in transit, and during processing using robust encryption algorithms. This ensures that even if an unauthorized entity gains access to the data, it remains incomprehensible without the appropriate decryption keys. The third layer centers on data integrity and auditing, utilizing digital signatures and hashing algorithms to verify data integrity, enabling prompt detection of any unauthorized modifications to data. Regular audits are conducted to monitor and analyze user activities, facilitating the timely identification of potential security breaches. The fourth layer addresses physical security at the data centers, implementing access controls, surveillance systems, and intrusion detection mechanisms to safeguard the physical infrastructure hosting cloud services. The fifth layer focuses on security in virtualization and isolation, deploying hypervisor-based virtual machine isolation and containerization technologies to ensure a strong separation between different cloud tenants, effectively preventing data leakage between them. Furthermore, the proposed data security model thoroughly considers legal and compliance aspects by examining data residency and data sovereignty regulations, ensuring data is stored in compliant locations and adheres to relevant laws. To validate the effectiveness of the proposed model, a prototype implementation is developed and tested in a simulated cloud environment, conducting extensive performance evaluations to assess the overhead introduced by security measures and optimize the model for real-world cloud deployments. In conclusion, the "Data Security Model for Cloud Computing" project presents a robust and holistic approach to address the data security challenges associated with cloud computing. By integrating access controls, data encryption, data integrity verification, physical security measures, and compliance considerations, the model aims to instill confidence in cloud users regarding the protection of their sensitive data. As cloud adoption continues to grow, this research serves as a valuable contribution to enhancing data security and trust in cloud computing environments.

Keywords: Data Security, Cloud Computing, Model, Confidentiality, Integrity, Availability, Access Control, Role- Based Access Control (RBAC), Attribute-Based Access Control (ABAC), Multi-Factor Authentication (MFA),Data Encryption, Encryption Algorithms, Data at Rest, Data in Transit, Data Processing, Digital Signatures, Hashing Algorithms, Auditing, User Activities, Security Breaches, Physical Security, Data Centers, Virtualization, Isolation.

| DOI: 10.17148/IARJSET.2023.10796