Angielski
In the design and development of the novel reliable and efficient security features for the secure cloud access, various schemes were proposed based on the real-time data collected from the authenticated reliable sources. The research was majorly focused on the security issues in private cloud, where an important security threats and mitigation measures were presented and suggested that private cloud security is at risk. It is understood that, the usage of multi-level biometric samples for the secure access will yields the best results in data leaks. To accomplish the authentication procedures, a novel Multi-level Biometric Authentication for Private Cloud Security mechanism was proposed and implemented. To improve the biometric authentication accuracy, DOST features was taken into consideration, where classification accuracy was improved, which in turn strengthen the authentication mechanism of the private cloud servers. A new integrated Bio-cryptic DOST feature extraction mechanism was developed and implemented successfully with high level of accuracy, which treated as the highest level of authentication process with 98% accuracy than previous procedures.
