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Signal Advance, Inc. (OTC: SIGL) today announced a new milestone in the evolution of cybersecurity: successful validation of its Analog Guard® encryption platform as resistant to advanced artificial intelligence (AI) decryption models. The breakthrough supports Signal Advance’s mission to deliver next-generation, physics-based cybersecurity solutions designed to defend against both AI-driven and quantum-era threats. Listen to CEO Now!
As IBM (NYSE: IBM) recently explained on its Think Blog, “AI is the overarching system. Machine learning is a subset of AI. Deep learning is a subfield of machine learning, and neural networks make up the backbone of deep learning algorithms.” In independent tests, two leading machine-learning models failed to detect any identifiable patterns, keys, or correlations within Analog Guard®-encrypted data—demonstrating complete AI resistance and a prediction accuracy of just 50%, equivalent to random guessing.
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“Even advanced neural networks couldn’t identify which key or message was behind the data,” said Chris Hymel, Ph.D., CEO of Signal Advance. “Analog Guard® represents a fundamental shift—its analog-domain architecture makes it inherently secure from digital and AI-based attacks.”
By replacing conventional math-based encryption with physics-based signal modulation, Analog Guard® removes the predictable structures AI depends on, providing hardware-level protection for government, defense, and industrial systems.
With new patents secured, NSF engagement underway, and expanded AI-resistance testing planned, Signal Advance (OTC: SIGL) is advancing Analog Guard® toward commercialization and strategic partnerships in 2026, positioning itself as an emerging U.S. leader in next-generation cybersecurity innovation.