JAIS (Journal of Applied Intelligent System)
Vol. 8 No. 3 (2023): Journal of Applied Intelligent System

Message Hiding Using the Least Significant Bit Method with Shifting Hill Cipher Security

Mahendra, Syafrie Naufal (Unknown)
Budiman, Fikri (Unknown)



Article Info

Publish Date
21 Apr 2025

Abstract

Technological developments go hand in hand with advances in digital messaging. In protecting the confidentiality of the message, it is necessary to double secure the data. This security can be done with a combination of steganography and cryptographic techniques. Steganography algorithm which is a technique for hiding messages well, one of which is Least Significant Bit (LSB). The LSB algorithm is a simple method because it only converts the value of the last bit in a message with the inserted message bit, which is a convenience of the LSB algorithm, but it becomes vulnerable to message theft attacks if not combined with other algorithms for security. So it is necessary to increase security. This research developed a combination method of LSB algorithm for steganography technique with Hill Cipher algorithm for cryptographic technique, Hill Cipher was developed with shifting (shifting) 2 (two) characters. With the development of this method, hackers will find it difficult to crack messages, and is expected to improve the performance of the algorithm in affecting image quality and travel time in running the algorithm. The results of this study will be tested using several evaluation tools MSE, PSNR, BER, CER, AE, and Entropy. With the development of this method, hackers will find it difficult to decipher messages, and from the results of this experiment has been able to improve the performance of the algorithm in maintaining image quality and can shorten travel time in running the algorithm.

Copyrights © 2023






Journal Info

Abbrev

JAIS

Publisher

Subject

Description

Journal of Applied Intelligent System (JAIS) is published by LPPM Universitas Dian Nuswantoro Semarang in collaboration with CORIS and IndoCEISS, that focuses on research in Intelligent System. Topics of interest include, but are not limited to: Biometric, image processing, computer vision, ...