Data Security in the Cloud Using pTree-based Homomorphic Intrinsic Data Encryption System
Abstract
Cloud usage for storing data and performing operations has gained immense
popularity in recent times. However, there are concerns that uploading data to the cloud
increases the chances of unauthorized parties accessing it. One way to secure data from
unauthorized access is to encrypt it. Even if the data is hacked, the hackers will not be
able to retrieve any information from the data without knowing the ‘Key’ to decrypt it.
But when data needs to be used for services such as data analytics, it must be in its
original, non-encrypted form. Decrypting the data makes it vulnerable again, which is
why Homomorphic Encryption could be the solution to this problem. In this encryption
method, the analytical engine can use the encrypted data to perform analysis, where the
analysis result will also be in decrypted form. Only authorized users can access the results
using the ‘Key.’ This research proposal proposes a method called pHIDES to enhance
data security in the cloud. The pHIDES (pTree-based Homomorphic Intrinsic Data
Encryption System) represents data in pTree (Predicate tree) format, a data mining-ready
data structure proven to manipulate a large volume of data effectively. The concept of
Homomorphic Encryption (HME) along with pHIDES is discussed in our research, along
with the algorithmic execution to analyze the effectiveness of the algorithm used to
encrypt data in the cloud.