A ROBUST STEGO-CRYPTOGRAPHIC ANTI-PHISHING FRAMEWORK
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Bowley, Nathanael Timothy
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Abstract
Phishing attacks manipulate victims through impersonation, often mimicking brand logos and digital identities. Primitive anti-phishing solutions lack accuracy and protection, while modern solutions suffer from biased supervised learning models, constant labeled data requirements, and more recently, generative adversarial perturbations, threatening artificial-intelligence (AI) and logo detection reliability.
The objective of this thesis is to design and develop a novel anti-phishing scheme using a stego-cryptographic approach. We present two novel eukaryotic immune system inspired algorithms: the Image Obfuscation Algorithm, which obfuscates images, and the Image Elucidation Algorithm, which elucidates them. Our framework further implements cryptography for sender verification, and intentionality for robust security.
Our zero-AI framework identifies legitimate senders with perfect accuracy and F-score, eliminating false positives and negatives to categorizes all 310,893 samples across 11 simulated conditions. Image quality metrics confirm our obfuscation and elucidation algorithm effectiveness. Additionally, original images restore identically for clients, laying a foundation for zero-day phishing detection.
Description
This thesis explores a novel anti-phishing framework that uses no artificial intelligence and instead relies on steganography and cryptography to function. We also identify the new security goal of intentionality to ensure messages are intentionally sent to targets to aid in preventing targeted and generalized phishing attacks. Our primary focus is email-based phishing, however this framework is robust enough to be applicable to other domains. The contents of this thesis are patent pending, or perhaps patented by the time of reading.
Keywords
phishing, social engineering, anti-phishing, steganography, cryptography, fraud, email security, MHC Framework, MHC file format, computer science, microbiology inspired, obfuscation, elucidation, zero-AI, digital identity, zero-day phishing, phishing detection