Enhancing Data Security Through Graph Theory

Abstract

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.