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Araujo, Istteffanny Isloure (2023) Investigations of eavesdropping with steganography over digital data files. Doctoral thesis, London Metropolitan University.
Protecting sensitive infonnation is crucial for individuals and businesses. Steganography conceals data within other data, making it an effective means of safeguarding confidential communication, data security, and copyright materials. However, current Steganography algorithms have weaknesses, such as high detectability, distortion, and low-capacity issues, that must be addressed to enhance their effectiveness. These weaknesses play a crucial role in regulating the strength of Steganography methods, as detectability, distortion, and capacity are common conditions that considerably impact the algorithm's security to protect confidential communication, data security, and copyright materials.
This study proposes an enhanced steganography technique that improves data security and capacity. It identifies weaknesses in existing algorithms and suggests a distributed approach that is simple, low-cost, and agile. The study also analyses data manipulation and embedding processes in different files and for different purposes and proposes a new framework scheme called DSoBMP. The results can help forensic analysts detect secret content and raise awareness about protecting against eavesdropping data on devices. The study has been published in four international peer-reviewed journals and used as a stepping stone to collaborate in a worldwide book publication.
Our proposed steganography technique uses Discrete Cosine Transform to distribute data randomly among sub-generated files, increasing capacity and decreasing the likelihood of detection. We encrypt the secret message using MD5 or RCA encryption for added protection and use BMP files for improved reliability. We have incorporated RSA and RC4 encryption methods to increase security and address capacity concerns further. Our DSoBMP-1 method has successfully minimised issues while doubling capacity improvements through larger BMP matrix breakdowns. Our technique has improved capacity by 100%.
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