Hiding Signals in Noise Using Quantum Randomness
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Solution Overview
Problem
Existing technologies face challenges in securely transmitting data and protecting computer instructions from malware sabotage, particularly in maintaining privacy and resisting malware attacks.
Innovation Solution
The use of quantum randomness to generate unpredictable stable instructions and random noise, allowing data and machine instructions to be hidden within the noise, thereby protecting against malware and ensuring secure transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data is transmitted through communication systems, then information can be shared between parties, but privacy and security against eavesdropping deteriorate
Solution Approach 1:
The patent converts the harmful effect of noise (which normally degrades signal quality) into a beneficial cryptographic tool. By deliberately introducing random noise and hiding data within this noise, the system achieves perfect secrecy. The noise that was previously considered a disturbance becomes the very mechanism that protects the data from eavesdroppers, transforming a harmful factor into a protective one.
Solution Approach 2:
The patent introduces an intermediary substance - random noise - that mediates between the data to be transmitted and the communication channel. This noise intermediary carries the hidden data while simultaneously obscuring it from eavesdroppers. The noise acts as a carrier that provides both transmission functionality and security protection.
2Reliability
If computer instructions are made stable to resist malware changes, then security against malware sabotage improves, but the ability to detect and measure instructions deteriorates
Solution Approach 1:
The patent applies local quality by making different parts of the machine instructions have different properties. The critical stable instructions are made structurally stable and resistant to small changes, while dummy instructions maintain normal variability. This creates a local distinction where stability is concentrated in specific instruction locations that need protection, allowing the system to resist malware while maintaining overall detectability and measurability of instructions.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach achieves arbitrarily close to perfect secrecy in data transmission and provides a cryptographically stable machine resistant to malware sabotage, using current TCP/IP infrastructure and quantum random number generators.
Implementation Method 1
use quantum randomness to generate unpredictable stable instructions and use quantum randomness to generate noise such that the program instructions are hidden in the noise
Data Source
AI summary
A new machine procedure and electronic circuitry are provided that hide one or more signals inside noise. In an embodiment, a random nonce helps unpredictably move the hiding locations of the signals. In an embodiment, the quantum complexity is related to the complexity of Grover's algorithm so that the hiding procedure is resistant to quantum computers. In some embodiments, public keys are hidden in the noise. In some embodiments, quantum randomness generates random noise and a random nonce, using photonic emission with a light emitting diode, and flip-flops.In other embodiments, our machine procedures and circuits use robustness, unpredictably and variability to hinder malware infection. In some embodiments, our machine instruction opcodes are randomized. The computing behavior of our machine is structurally stable (invariant) to small changes made to its machine instructions. Our invention expands the engineering method of stability to a cryptographically stable machine that is resistant to malware sabotage by an adversary.