| Title | Forensic Digital Data Tamper Detection Using Image Steganography and S-Des |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Senkyire, Isaac Baffour, Marful, Emmanuel Addai, Mensah, Eric Adjei |
| Conference Name | 2021 International Conference on Cyber Security and Internet of Things (ICSIoT) |
| Keywords | Ciphers, composability, cryptographic, Encryption, Forensics, Internet of Things, least significant bit, Metrics, privacy, pubcrawl, S-DES, Stakeholders, steganography, steganography detection, Task Analysis |
| Abstract | In this current age, stakeholders exchange legal documents, as well as documents that are official, sensitive and confidential via digital channels[1]. To securely communicate information between stakeholders is not an easy task considering the intentional or unintentional changes and possible attacks that can occur during communication. This paper focuses on protecting and securing data by hiding the data using steganography techniques, after encrypting the data to avoid unauthorized changes or modification made by adversaries to the data through using the Simplified Data Encryption Technique. By leveraging on these two approaches, secret data security intensifies to two levels and a steganography image of high quality is attained. Cryptography converts plaintext into cipher text (unreadable text); whereas steganography is the technique of hiding secret messages in other messages. First encryption of data is done using the Simplified Data Encryption Standard (S-DES) algorithm after which the message encrypted is embedded in the cover image by means of the Least Significant Bit (LSB) approach. |
| DOI | 10.1109/ICSIoT55070.2021.00020 |
| Citation Key | senkyire_forensic_2021 |
Forensic Digital Data Tamper Detection Using Image Steganography and S-Des