Homomorphic Image Encryption via Pixel Sub-Value Segmentation
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Solution Overview
Problem
Existing image encryption methods are inadequate in providing robust security against sophisticated cyber attacks, particularly in protecting images from unauthorized visualization, information extraction, and alteration during transmission and storage.
Innovation Solution
A distributed homomorphic image encryption method that transforms original images into encoded 'cipher' images by determining pixel intensity values as sums of sub-values, applying encryption functions to these sub-values, and creating multiple encrypted images using different keys, making it difficult to break the encryption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional image encryption methods are used, then the encryption process is simple and fast, but the security against sophisticated cyber attacks is insufficient
Solution Approach 1:
The patent divides the original image into multiple encrypted images by decomposing pixel intensity values into sub-values and applying different encryption functions to each sub-value. This segmentation approach increases security because attackers must compromise multiple encrypted images and their corresponding keys to reconstruct the original image, rather than breaking a single encryption scheme.
Solution Approach 2:
The patent transitions from single-image encryption to multi-image encryption by adding a dimensional aspect to the encryption process. Each pixel's intensity is split into sub-values that are encrypted separately into different encrypted images, creating a multi-dimensional security structure that resists traditional attack vectors.
2Reliability
If multiple encrypted images are created using different keys, then the difficulty in breaking encryption increases, but the complexity of the encryption process increases
Solution Approach 1:
The encryption process segments the original image into multiple encrypted images, each protected by a different key. This segmentation allows the system to achieve higher security through multiple layers of encryption while maintaining a structured process that can be systematically implemented.
Solution Approach 2:
The patent changes the parameter of pixel intensity values by decomposing them into sub-values and applying different encryption functions with different keys. This parameter transformation enables multiple encrypted images to be generated from a single original image, increasing security while following a defined mathematical process.
3Reliability
If pixel intensity values are decomposed into sub-values and encrypted separately, then resistance to histogram and entropy analysis attacks improves, but the computational complexity increases
Solution Approach 1:
The patent segments pixel intensity values into sub-values and encrypts them separately into different encrypted images. This segmentation effectively resists histogram and entropy analysis attacks because the statistical properties of the original image are distributed across multiple encrypted images, making statistical analysis infeasible.
Solution Approach 2:
By transforming the encryption from a single-image approach to a multi-image approach, the patent adds a dimensional layer that disperses the computational and statistical analysis burden across multiple images, thereby resisting attacks that rely on analyzing single-image properties.
Data Source
AI summary
Encryption of an image is achieved through application of a homomorphic encryption function to produce cipher images for each image. Encryption is performed individually on sub-values of a pixel's intensity value, wherein the pixel's intensity value can be described as a sum of the smaller numerical sub-values. The encrypted values for each sub-value form encrypted images that can be transferred or stored on insecure media. Separate encryption approaches can be applied to individual sets of the numerical sub-values to improve security.