Enhancing Data Security Through Graph Theory - Das, Laxmiparbati; Mishra, Samikshya; Mehar, Sujit (International Journal on Advanced Computer Engineering and Communication Technology, 2023)
Sharing private data over unsecured channels poses a grave risk, as it can be intercepted by unauthorized entities, compromising its privacy. Consequently, the development of a cryptosystem that ensures the confidentiality, integrity, and authenticity of transmitted data has become an imperative necessity. Extensive efforts have been dedicated to this endeavor, yet the robustness and performance of many proposed cryptosystems vary considerably. Safeguarding information has been a cornerstone of human existence since ancient times, with cryptography emerging as a vital technique for securing message transmission and data protection. Additionally, graph theory plays a significant role in data security. Numerous encryption and decryption techniques are available within cryptography to render text unintelligible to adversaries. Cryptography finds wide-ranging applications, including e-commerce, electronic communications, business transactions, financial information transmission, and ATM card security, impacting various aspects of daily life. By concealing sensitive information, cryptography ensures privacy and security through mathematical techniques. A cryptographic scheme is considered secure if it remains unbreakable within a reasonable timeframe, even when adversaries are aware of the algorithm and key size. In this paper, we propose an algorithm that utilizes the adjacent matrix representation of graphs to derive encryption and decryption keys, thereby contributing to the advancement of secure data transmission methods.