Ensuring The Safety of Cloud Computing, A Trusted Cloud Service Framework
Keywords:
Cloud Computing, Trusted Cloud Service Framework (TCSF), Weighted Attribute Authority (WAA), Central Authority (CA)Abstract
Cloud computing became critical for modern information systems, giving configurable computing ability to users via the internet. While cloud computing provides scalability, elasticity, and cost efficiencies, challenges remain regarding the cloud-based data. This paper proposes the Trusted Cloud Service Framework (TCSF) with multi- authority weighted attribute-based encryption (W- ABE) and symmetric encryption using AES-256 and a conjoined sanctioning scheme with a Central Authority (CA) and Weighted Attribute Authority (WAA). The framework attempts to provide a solution to various concerns regarding Multi-Tenant Trust, Identity Management, and Access Control Data Security. The authors implemented a prototype system in Java and the authors provide Experimental Data Improvement in Encryption on Throughput, Improvement in Metric Resource Consumption, and Improvement in Being Resistant to Insider Threats, Collusion (i.e.). Based on the obtained empirical data, the authors show that TCSF is better than other systems, baseline CP-ABE and HABE systems, and remains effective for cases where the system needs to be used for online cloud data. The results obtained of the TCSF in cloud computing protections show the TCSF system provides a solution that is effective and increases the security of the system for users. Cloud TCSF provides an effective moderate system in data centres.
References
D. L. Fithri, A. P. Utomo, and F. Nugraha, “Implementation of SaaS cloud computing services on e-learning applications (case study: PGRI foundation school),” J. Phys.: Conf. Ser., vol. 1430, no. 1, p. 012049, 2020.
D. Mrozek, “A review of cloud computing technologies for comprehensive microRNA analyses,” Comput. Biol. Chem., vol. 88, p. 107365, 2020.
C. V. B. Murthy, M. L. Shri, S. Kadry, and S. Lim, “Blockchain-based cloud computing: Architecture and research challenges,” IEEE Access, vol. 8, pp. 205190–205205, 2020.
P. Loubière and L. Tomassetti, “Towards cloud computing,” in TORUS 1: Toward an Open Resource Using Services—Cloud Computing for Environmental Data, 2020, pp. 179–189.
K. Alshouiliy and D. P. Agrawal, “Confluence of 4G LTE, 5G, fog, and cloud computing and understanding security issues,” in Fog/Edge Computing for Security, Privacy, and Applications. Cham, Switzerland: Springer, 2021, pp. 3–32.
A. Kumar, R. Krishnamurthi, A. Nayyar, K. Sharma, V. Grover, and E. Hossain, “A novel smart healthcare design, simulation, and implementation using healthcare 4.0 processes,” IEEE Access, vol. 8, pp. 118433–118471, 2020.
J. K. Jeevitha and G. Athisha, “A novel scheduling approach to improve the energy efficiency in cloud computing data centers,” J. Ambient Intell. Humaniz. Comput., vol. 12, no. 6, pp. 6639–6649, 2021.
J. Kaur and B. K. Sidhu, “Task scheduling in cloud computing using various techniques,” Int. J. Adv. Res. Comput. Sci., vol. 8, no. 5, 2017.
N. Sadhasivam and P. Thangaraj, “Design of an improved PSO algorithm for workflow scheduling in cloud computing environment,” Intell. Autom. Soft Comput., vol. 23, no. 3, pp. 493–500, 2017.
S. Munguti and E. Opiyo, “Factors influencing the adoption of cloud computing in software development companies in Kenya,” Int. Acad. J. Inf. Syst. Technol., vol. 2, no. 1, pp. 126–144, 2018.
S. R. Gundu, C. A. Panem, and A. Thimmapuram, “Real-time cloud-based load balance algorithms and an analysis,” SN Comput. Sci., vol. 1, pp. 1–9, 2020.
S. Liu, K. Yue, H. Yang, L. Liu, X. Duan, and T. Guo, “The research on SaaS model based on cloud computing,” in Proc. 2nd IEEE Int. Conf. Adv. Inf. Manage., Commun., Electron. Autom. Control (IMCEC), 2018, pp. 1959–1962.
F. Hadi, Z. Aliouat, and S. Hammoudi, “Efficient platform as a service (PaaS) model on public cloud for CBIR system,” Ingénierie des Systèmes d’Information, vol. 25, no. 2, pp. 215–225, 2020.
S. Malla and K. Christensen, “HPC in the cloud: Performance comparison of function as a service (FaaS) vs infrastructure as a service (IaaS),” Internet Technol. Lett., vol. 3, no. 1, p. e137, 2020.
A. S. Al-Ahmad and H. Kahtan, “Cloud computing review: Features and issues,” in Proc. Int. Conf. Smart Comput. Electron. Enterprise (ICSCEE), 2018, pp. 1–5.
A. Cohen and N. Nissim, “Trusted detection of ransomware in a private cloud using machine learning methods leveraging meta-features from volatile memory,” Expert Syst. Appl., vol. 102, pp. 158–178, 2018.
L. M. Abualigah and A. Diabat, “A novel hybrid antlion optimization algorithm for multi-objective task scheduling problems in cloud computing environments,” Cluster Comput., vol. 24, no. 1, pp. 205–223, 2021.
R. V. Patel, D. Bhoi, and C. S. Pawar, “Security hazards, attacks and prevention techniques in cloud computing: A detailed review,” 2020.
V. Hassija, V. Chamola, V. Saxena, D. Jain, P. Goyal, and B. Sikdar, “A survey on IoT security: Application areas, security threats, and solution architectures,” IEEE Access, vol. 7, pp. 82721–82743, 2019.
A. Ahmed, R. Latif, S. Latif, H. Abbas, and F. A. Khan, “Malicious insiders attack in IoT-based multi-cloud e-healthcare environment: A systematic literature review,” Multimedia Tools Appl., vol. 77, no. 17, pp. 21947–21965, 2018.
N. Moustafa, “A systemic IoT–fog–cloud architecture for big-data analytics and cyber security systems,” in Secure Edge Computing: Applications, Techniques and Challenges, 2021, p. 41.
V. Sailakshmi, “Analysis of cloud security controls in AWS, Azure, and Google Cloud,” 2021.
D. P. Moreno Alarcon, J. F. Vautier, G. Hernandez, and F. Guarnieri, “Systems thinking in risk management by preventive and detective controls as an ago-antagonistic systems approach in the French nuclear sector,” HAL, 2019.
P. S. Suryateja, “Threats and vulnerabilities of cloud computing: A review,” Int. J. Comput. Sci. Eng., vol. 6, no. 3, pp. 297–302, 2018.
A. Saravanan, S. S. Bama, S. Kadry, and L. K. Ramasamy, “A new framework to alleviate DDoS vulnerabilities in cloud computing,” Int. J. Electr. Comput. Eng., vol. 9, no. 5, 2019.
