An Efficient Provable Data Possession Scheme based on Counting Bloom Filter for Dynamic Data in the Cloud Storage

Cloud services have become a trend, because many companies are supplying various cloud services that reflect the needs of users. However, as cloud services increase, security problems, such as saved data spills and data modulation, also increase. This paper focuses on the problem of data integrity. A PDP (Provable Data Possession) scheme has the disadvantage of time overheads, because dynamic data needs additional processing time. To solve the problem, this paper examines the use of a Counting Bloom Filter for updating data. This technique is more efficient than using PDP when changing part of the data in a simulation. The result is more effective if the saved data changes part of the dynamic data.