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Stereoisomers

Stereoisomers

On the basis of mirror symmetry, stereoisomers of an organic molecule can be further classified into diastereomers and enantiomers. Diastereomers are stereoisomers that are not mirror images of each other. Substituted alkenes, such as the cis and trans isomers of 2-butene, are diastereomers, as these molecules exhibit different spatial orientations of their constituent atoms, are not mirror images of each other, and do not interconvert. Here, the interconversion is suppressed due to...

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Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

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Published on: February 12, 2014

Security-oriented steganographic payload allocation for multi-remote sensing images.

Tian Wu¹, Xuan Hu¹, Chunnian Liu²

¹Digital Literacy and Skills Enhancement Research Center, Jiangxi Province Philosophy and Social Science Key Research Base, School of Public Policy and Administration, Nanchang University, Nanchang, 330031, China.

Scientific Reports

|February 27, 2024

Summary

This summary is machine-generated.

This study enhances multi-image steganography security by using a pre-trained network to analyze remote sensing image texture complexity. An adaptive payload allocation strategy maximizes embedding capacity while ensuring security against steganalysis.

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Area of Science:

Computer Science
Information Security
Remote Sensing

Background:

Multi-image steganography conceals data in multiple carriers, with remote sensing images favored for their complex texture.
Current methods often focus on individual image complexity, potentially compromising overall security.
Effective steganography relies on optimal cover selection and payload distribution.

Purpose of the Study:

To introduce a security-focused approach for steganographic payload allocation in multi-image remote sensing.
To enhance the resilience of multi-image steganography against steganalysis.
To improve both security and capacity in steganographic systems using remote sensing data.

Main Methods:

Utilized a steganalysis pre-trained network to quantify texture complexity and correlate it with security in remote sensing images.
Developed an adaptive payload allocation strategy for multiple images.
Embedded payloads near each image's maximum steganographic capacity while maintaining embedding security.

Main Results:

The proposed methodology demonstrates superior performance in cover selection and payload allocation.
Achieved enhanced undetectability against contemporary steganalysis tools.
Quantified texture complexity directly linked to improved security in steganographic embedding.

Conclusions:

The security-oriented approach significantly fortifies multi-image steganography.
Adaptive payload allocation balances capacity and security effectively.
The method offers a robust solution for secure information hiding in remote sensing imagery.