Research Paper
Optimized data hiding based steganography approach to secure the confidential information in smart grid
The standard electrical power grid is integrated with information and communication technologies in a smart grid (ICT). Such integration empowers electrical utility providers and consumers to increase the efficiency and availability of the power system and allows customers' needs to be continually monitored, controlled, and managed. A smart grid is a massive, complicated network made up of millions of linked objects and organizations. With such a large network comes a slew of security problems and flaws. Cryptography and steganography algorithms have been applied to give security in SG. The steganography algorithm hides the important data in the cover media to provide imperceptibility to the attacker. Image is the most essential cover media in steganography. The least significant bit (LSB) method is used to hide the confidential information in the cover image. The hiding process provides variability in the cover image. In this paper, an optimized data hiding method is proposed to reduce the variability. The proposed method has two phases. In the first phase, the confidential information bits are matched with LSB bits of a cover image pixel. For matching purposes, an original or complemented form of confidential information bits is matched with cover image pixel and if a match is found then the index is determined. In the second phase, the indexes are hidden in the cover image in an optimal way using the JAYA optimization algorithm. The optimization algorithm searches the optimal starting point in the cover image for index hiding. After searching the optimal starting pixel, hide the index using the k-bits LSB method. The proposed method is simulated in MATLAB and performance analysis is done using various parameters. The simulation outcomes represent that the presented method is better than existing methods.
Published by: Angrej Singh, Puneet Jain
Author: Angrej Singh
Paper ID: V7I6-1292
Paper Status: published
Published: December 15, 2021
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