Selective Encryption using Chaotic Henon Map for Medical Images

핵심 개념

The author presents a selective encryption scheme for medical images using a chaotic Henon map, focusing on securing the most vital parts of the image efficiently.

초록

The content discusses a novel approach to encrypting medical images selectively using a chaotic Henon map. The scheme aims to enhance security while optimizing resource utilization for medical professionals. By segmenting out crucial regions of interest, encrypting them with the Henon map, and achieving lossless decryption, the proposed model offers faster retrieval speeds and improved security for various diagnosis purposes in medical imaging.
The paper emphasizes user-centric design and resource optimization in technology innovation, particularly in the field of medical image storage and security. The architecture is structured around Segmentation, Storage, and Retrieval segments to cater to the high retrieval demands by medical professionals compared to storage operations. By encrypting only essential parts of the image using a strong encryption algorithm like chaotic Henon map, security is maintained while ensuring efficient retrieval through less computationally intensive decryption processes.
Furthermore, the study delves into various encryption methods used in medical imaging over recent years, highlighting advancements such as adjacency matrix-based S-boxes and chaos-based encryption techniques like Brownian movement and Chen's chaotic system. The comparison between full encryption and selective encryption methods showcases significant speed improvements and lossless decrypted images with selective encryption schemes.
Overall, the content provides insights into cutting-edge approaches to secure medical images effectively while addressing concerns related to data privacy and accessibility in healthcare settings.

통계

Achieved retrieval speed improvement of around 47% compared to full image encryption.
ResNet-50 model achieved maximum segmentation accuracy of 89.6%.

인용구

"The architecture supports all kinds of 3D medical image formats for secure storage and faster retrieval."
"The proposed model with selective encryption is 47% faster than full encryption."

핵심 통찰 요약

Selective Encryption using Segmentation Mask with Chaotic Henon Map for Multidimensional Medical Images

by S Arut Praka... 게시일 arxiv.org 03-11-2024

https://arxiv.org/pdf/2403.04781.pdf

더 깊은 질문

How can this selective encryption scheme be integrated with cloud storage solutions for enhanced accessibility?

Integrating the selective encryption scheme with cloud storage solutions can enhance accessibility by providing secure access to medical images from anywhere. One way to achieve this integration is by implementing a secure communication protocol between the client application and the cloud server. The encrypted medical images, along with their segmentation masks, can be securely uploaded to the cloud storage using authenticated and encrypted channels.
To ensure data security in transit and at rest, robust encryption algorithms should be used during data transmission and storage. Additionally, access control mechanisms should be implemented on the cloud server to restrict unauthorized access to sensitive medical images. This would involve role-based access control (RBAC) where only authorized users are granted permission to view or download specific encrypted medical images.
Moreover, leveraging key management services provided by cloud service providers can help in securely managing encryption keys for decryption purposes. By storing encryption keys separately from the encrypted data, an added layer of security is maintained.
In terms of retrieval efficiency, utilizing metadata tagging for each encrypted image stored in the cloud can facilitate quick search and retrieval based on specific criteria such as patient ID or date of imaging. This metadata indexing enables faster retrieval of relevant medical images when requested by healthcare professionals.

What are potential drawbacks or vulnerabilities associated with using chaotic maps for image encryption?

While chaotic maps offer a high level of randomness that enhances security in image encryption schemes, there are some potential drawbacks and vulnerabilities that need to be considered:

Sensitivity to Initial Conditions: Chaotic systems exhibit sensitivity to initial conditions which means small changes in input parameters could lead to significantly different outputs. If an attacker gains knowledge about these initial conditions or has partial information about them, it may compromise the security of the encryption algorithm.

Key Management Complexity: Chaotic maps often require complex key generation processes due to their non-linear nature. Managing these keys securely without compromising them poses a challenge especially in large-scale deployment scenarios.

Computational Overhead: Implementing chaotic map-based encryption algorithms may introduce computational overhead due...

4....
5....

How might advancements in AI impact future development of selective encryption techniques?

Advancements in AI have significant implications for enhancing selective encryption techniques:
1...
2...
3...
4...
5...