A secure messaging application using steganography and AES encryption a dual-layer secure messaging system
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2025.16.2.12Keywords:
Steganography, Secure messaging, Data hiding, LSB method, AES encryption, Privacy, Hidden communication.Dimensions Badge
Issue
Section
License
Copyright (c) 2025 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This research involves the development of a secure messaging application with the capability to send messages inside images oraudiofiles using the practice called steganography. In this application, a person can secretly communicate in such a way that nooneisawareoftheexistenceof the hidden message. The application uses the Least Significant Bit (LSB) method to hide the messages while encrypting the messages. To provide greater security, AES encryption is used before hiding the messages, thus forcing both sender and receiver to decrypt the message using a shared key. This two-layer approach of steganography and encryption creates this application highly appropriate for people with communication controls or monitored at some level because it gives confidentiality for the message privacy.Abstract
How to Cite
Downloads
Similar Articles
- A. Sathya, M. S. Mythili, MOHCOA: Multi-objective hermit crab optimization algorithm for feature selection in sentiment analysis of Covid-19 Twitter datasets , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Swetha Rajkumar, Jayaprasanth Devakumar, LSTM based data driven fault detection and isolation in small modular reactors , The Scientific Temper: Vol. 14 No. 01 (2023): The Scientific Temper
- L. Amudavalli, K. Muthuramalingam, Energy-efficient location-based routing protocol for wireless sensor networks using teaching-learning soccer league optimization (TLSLO) , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Ritu Nagila, Abhishek Kumar Mishra, Ashish Nagila, Role of big data in enhancing lung cancer prediction and treatment , The Scientific Temper: Vol. 16 No. 04 (2025): The Scientific Temper
- C. Muruganandam, V. Maniraj, A Self-driven dual reinforcement model with meta heuristic framework to conquer the iot based clustering to enhance agriculture production , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Nilesh M. Patil, P M. Krishna, G. Deena, C Harini, R.K. Gnanamurthy, Romala V. Srinivas, Exploring real-time patient monitoring and data analytics with IoT-based smart healthcare monitoring , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- S. Vanaja, Hari Ganesh S, Application of data mining and machine learning approaches in the prediction of heart disease – A literature survey , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Shiny Bridgette I, Rexlin Jeyakumari S, Fuzzy inventory model with warehouse limits and carbon emission , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- MRINAL CHANDRA, DEVELOPMENT OF METHOD FOREXTRACTIVE SPECTROPHOTOMETRIC DETERMINATION OF COPPER(II) WITH N-BENZOYL THIOUREATHIOSEMICARBONZONE(MAAPHE) AS AN ANALYTICAL REAGENT , The Scientific Temper: Vol. 8 No. 1&2 (2017): The Scientific Temper
- N. Saranya, M. Kalpana Devi, A. Mythili, Summia P. H, Data science and machine learning methods for detecting credit card fraud , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
<< < 8 9 10 11 12 13 14 15 16 17 > >>
You may also start an advanced similarity search for this article.

