A Holistic Secure Communication Mechanism Using a Multilayered Cryptographic Protocol to Enhanced Security
Source abstract
Abstract
In an era characterized by digital pervasiveness and rapidly expanding datasets, ensuring the integrity and reliability of information is paramount. As cyber threats evolve in complexity, traditional cryptographic methods face increasingly sophisticated challenges. This article initiates an exploration into these challenges, focusing on key exchanges (encompassing their variety and subtleties), scalability, and the time metrics associated with various cryptographic processes. We propose a novel cryptographic approach underpinned by theoretical frameworks and practical engineering. Central to this approach is a thorough analysis of the interplay between Confidentiality and Integrity, foundational pillars of information security. Our method employs a phased strategy, beginning with a detailed examination of traditional cryptographic processes, including Elliptic Curve Diffie-Hellman (ECDH) key exchanges. We also delve into encrypt/decrypt paradigms, signature generation modes, and the hashes used for Message Authentication Codes (MACs). Each process is rigorously evaluated for performance and reliability. To gain a comprehensive understanding, a meticulously designed simulation was conducted, revealing the strengths and potential improvement areas of various techniques. Notably, our cryptographic protocol achieved a confidentiality metric of 9.13 in comprehensive simulation runs, marking a significant advancement over existing methods. Furthermore, with integrity metrics at 9.35, the protocol’s resilience is further affirmed. These metrics, derived from stringent testing, underscore the protocol’s efficacy in enhancing data security.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Chaos-based Image/Signal Encryption · Cryptographic Implementations and Security · Cryptography and Data Security
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (43)
Show source-provided references
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