Research Article
Secure Data Deduplication System with Cyber Security Multikey
Management in Cloud Storage
R. Nandha Kumar,
1
T. Sathiya,
2
Harish Chandra Mohanta ,
3
Sayed Sayeed Ahmad ,
4
Ankit Kumar ,
5
Ghalib H. Alshammri ,
6
and Henry Kwame Atiglah
7
1
Department of Computer Science and Applications, Vivekanandha College of Arts and Sciences for Women (Autonomous),
Tiruchengode, Tamil Nadu, India
2
Department of CSE, Sona College of Technology, Salem, Tamil Nadu, India
3
Department of Electronics and Communication Engineering, Centurion University of Technology and Management, Gajapati,
Odisha, India
4
College of Engineering and Computing, Al Ghurair University, Dubai, UAE
5
Department of Computer Engineering and Applications, GLA University Mathura, Mathura 281406, Uttar Pradesh, India
6
Department of Computer Science, Community College, King Saud University, Riyadh 11437, Saudi Arabia
7
Department of Electrical & Electronics Engineering, Tamale Technical University, Tamale, Ghana
Correspondence should be addressed to Henry Kwame Atiglah; hkatiglah@tatu.edu.gh
Received 17 April 2022; Revised 29 June 2022; Accepted 5 July 2022; Published 12 August 2022
Academic Editor: Mukesh Soni
Copyright © 2022 R. Nandha Kumar et al. is is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Object detection is essential in a video surveillance system. To recognize an item in a movie, we first examine each picture pixel by
pixel. e Secure Data Deduplication system in segmentation is the process of separating distinct picture components into pixels
in digital image processing. e performance of segmentation is influenced by irregular and/or poor lighting. ese characteristics
have a significant impact on the video surveillance system’s real-time object detection process. A multikey management system
based on a modified ResNet model is presented in this research (M-ResNet). Cyber security is a suggested algorithm application
that is used to improve images that are influenced by a lack of light. e experimental findings reveal a significant improvement in
detecting objects in the video stream as compared to the present technique output and modification architecture of the ResNet
model. e suggested model achieves superior results in measures like precision, recall, and pixel accuracy, as well as a decent
increase in object recognition.
1. Introduction
Indexing of fingerprints identifies duplicate and nonduplicate
data chunks after the chunking and fingerprinting steps of the
deduplication system. An earlier deduplication technique stores
the complete chunk fingerprint index in memory for quick
redundant data identification. However, due to the exponentially
expanding index size of the deduplication system, fast increasing
data volume results in a high number of fingerprints created,
which overflows the RAM capacity. As a result, frequent access
to low-speed storage drives for fingerprint-index search dras-
tically limits throughput. Some data deduplication systems have
limited accessing throughput to the on-disk fingerprint index,
resulting in a significant performance bottleneck. Random ac-
cesses to the on-disk index are substantially slower than those to
the on-RAM index. However, the additional hardware costs
associated with on-RAM indexing have grown too high. e
texture of the fingerprint image is stored on the hard disc of the
system, which improves the training and testing process. On the
other hand, on-disk fingerprint indexing lowers RAM overhead
costs for deduplication indexing. Flash-based indexing strategies
raise the hardware expenses of deduplication systems. Cluster
deduplication technologies provide scalability for vast storage
systems at the expense of a low deduplication ratio or need more
resources to achieve a high deduplication ratio. To improve
storage space efficiency, deduplication technology is mostly used
Hindawi
Security and Communication Networks
Volume 2022, Article ID 9790398, 11 pages
https://doi.org/10.1155/2022/9790398