Enhancing medical data security using tiny encryption algorithm and least significant bit steganography

• Published in: AIP conference proceedings Vol. 2796; no. 1
• Main Authors: Bansal, Malti, Sirpal, Varun, Jain, Tanmaya, Ujjwal, Nangia, Uma
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Melville American Institute of Physics 14.07.2023
• Subjects: Algorithms; Cryptography; Data integrity; Electronic health records; Health care; Health services; Social security; Steganography
• ISSN: 0094-243X; 1551-7616
• DOI: 10.1063/5.0149166

Data is the new oil of today. With this, data security becomes highly imperative. This is even more true for healthcare institutions since patient data is crucial for their correct treatment by doctors. In the absence of patient data, lives cannot be saved and this results in a hospital being unable to deliver quality healthcare services. Medical data in the form of Electronic Health Records (EHRs) contains data including, but not limited to, medical history of patient and family, diagnosis reports such as X-Ray, Ultrasound, Blood Tests, etc., unique identification documents such as social security numbers, passport, and financial information such as bank account number, signature, etc. In the past, one data breach for a healthcare institution cost upwards of $2 million on an average. This clearly shows the severity of the issueat hand. However, due to the advancement by attackers in their attack strategies, it is of utmost importance to increase the security with which medical data is being transported. Healthcare institutions usually apply only one security measure such as firewalls, cryptography, or steganography in their system. This is not sufficient in today’s scenario. In this paper, we have proposed a framework for enhancing medical data security using a combination of cryptography and steganography. In Section-1, we have given an introduction to cryptography, steganography and their types. In Section-2, we have explained the working of the Tiny Encryption Algorithm (TEA), the code for the same written in C and results using known test vectors. In Section-3, we have described our proposed framework for enhancing medical data security, employing TEA and Least Significant Bit (LSB) Steganography to achieve the same. The programming for the same has been performed in Python. Lastly, in Section-4, we have given a brief conclusion and the future prospects for the current work.