Dynamic Block Level Error Recovery to Trust Multimedia Data for E-learning Cloud Based Storage Services

The purpose of the study is to design a cloud storage service to detect the maximum probability of disrupted data blocks in a timely manner for any dynamic changes of multimedia data that does not affect the cloud environment. In the current scenario, the cloud environment must gain significant quality of service for data traversing from cloud to users. The e-learning cloud based system is always a night mare because of its security constraints as cloud application service don’t give high percent of guarantee on data loss in secured layer of cloud environment. The user data stored on cloud always demands on how their private information is kept safe. This study focuses mainly on cloud data storage security for e-learning system, which has always been an important aspect of quality service. To make sure the correctness of users data within the cloud, an adaptable and effective methodology has been developed by handling dynamic data operations on the cloud data and recovery techniques are embedded by using forward error correcting algorithms applied to an e-learning web application. This extensive analysis shows that the end result which achieves blocks level data inclusion, deletion and searching dynamically along with recovery of data for malicious data modification attacks.