Abstract:
The ever-increasing volume of data generated
from various sources, including the Internet of
Things (IoT) and digital channels, presents a
significant challenge for organizations. This rapid
growth often necessitates offloading data analysis
to the cloud due to limitations on local server
capacity. However, security concerns arise when
analyzing sensitive data in the cloud environment.
Traditional encryption methods, while effective in
protecting data at rest, require decryption prior to
analysis,
potentially
exposing
sensitive
information. On the other hand, Homomorphic
Encryption (HE) is gaining popularity as it –
offers a solution by enabling computations to be
performed directly on encrypted data. This paper
investigates the effectiveness of homomorphic
encryption on big data through descriptive and
diagnostic analyses. Result suggest that this
approach is better in terms of execution time and
is particularly well-suited for big data analytics
due to its inherent scalability.
