Development of a system to detect hidden information in a document using steganography software
Steganography is the art of hiding secret information in plain sight. Manipulating the least significant bit (LSB) of the image’s pixel values is one of the most popular steganographic embedding method. This report documents the steps and development process of a software system that implements a si...
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sg-ntu-dr.10356-745642023-07-07T17:57:11Z Development of a system to detect hidden information in a document using steganography software Wuan, Neng Jie Chan Chee Keong School of Electrical and Electronic Engineering DRNTU::Engineering Steganography is the art of hiding secret information in plain sight. Manipulating the least significant bit (LSB) of the image’s pixel values is one of the most popular steganographic embedding method. This report documents the steps and development process of a software system that implements a signature-based steganalysis approach based on Patterns of Pixel Differences and Random Embedding. Like other blind steganalysis attempts, there will be inherent uncertainties and does not guarantee 100% detection rates. The accuracy of detection depends on the trained Support Vector Machine (SVM) model used, and therefore, accuracy hinges on the type of training data and test images used. Ultimately, there is no universal model that can provide effective classification for any type of image. Bachelor of Engineering 2018-05-21T09:07:21Z 2018-05-21T09:07:21Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/74564 en Nanyang Technological University 75 p. application/pdf |
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DRNTU::Engineering Wuan, Neng Jie Development of a system to detect hidden information in a document using steganography software |
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Steganography is the art of hiding secret information in plain sight. Manipulating the least significant bit (LSB) of the image’s pixel values is one of the most popular steganographic embedding method. This report documents the steps and development process of a software system that implements a signature-based steganalysis approach based on Patterns of Pixel Differences and Random Embedding. Like other blind steganalysis attempts, there will be inherent uncertainties and does not guarantee 100% detection rates. The accuracy of detection depends on the trained Support Vector Machine (SVM) model used, and therefore, accuracy hinges on the type of training data and test images used. Ultimately, there is no universal model that can provide effective classification for any type of image. |
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Chan Chee Keong |
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Chan Chee Keong Wuan, Neng Jie |
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Final Year Project |
author |
Wuan, Neng Jie |
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Wuan, Neng Jie |
title |
Development of a system to detect hidden information in a document using steganography software |
title_short |
Development of a system to detect hidden information in a document using steganography software |
title_full |
Development of a system to detect hidden information in a document using steganography software |
title_fullStr |
Development of a system to detect hidden information in a document using steganography software |
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Development of a system to detect hidden information in a document using steganography software |
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development of a system to detect hidden information in a document using steganography software |
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2018 |
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http://hdl.handle.net/10356/74564 |
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1772829175745347584 |