الفهرس 
SteganographyOnly 14 pages are availabe for public view
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Abstract
Nowadays, long-distance communication security is a serious issue, in particular when highly confidential information is exchanged or stored over a public network like the internet. Several options have been put forth to ensure secure data transmission, among which cryptography (encryption) and steganography systems are now widely used, and they frequently go hand in hand.
Steganography is the art and science of rendering data unnotice- able. It uses media coverage to hide secret information, such as text, images, videos, audios, and DNA structures. Obviously, cryptography makes data unreadable or hides the meaning of data, while steganog- raphy hides the existence of data. This means that cryptography is secret writing, while steganography is covert writing, and this is a substantial difference between them.
In some real-life applications, such as spying, the major issue with cryptography is that, even with a powerful cryptography method, once a file is encrypted, it seems to be a random stream of bytes. In the world of computers, random bytes are extremely uncommon and are thus relatively simple to spot in a flow of trillions of structured bytes.
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Hence, the importance of using steganography arises in these applica- tions.
The objective of this thesis is to investigate and debate the signifi- cance of steganography in real-life applications. As well as presenting some relevant details on steganography and its various types. Also discussing the significance of using bio-inspired searching algorithms in steganography. This encouraged us to develop an enhanced bio- inspired algorithm and apply it to image steganography to identify the suitable positions to conceal confidential information.
This thesis contains five chapters and a list of the most important references pertinent to the topics covered. A brief overview of each chapter is summarized as follows.
Chapter 1 provides a historical overview of steganography and some basic concepts. In addition, the steganography classifications and the properties that assess any steganography approach are in- cluded. Furthermore, the steganography types and challenges that face steganography are presented. Moreover, a brief overview of ste- ganalysis and some stego-attacks are presented. Finally, some steganog- raphy applications are demonstrated, along with a special case known
as medical image.
Chapter 2 gives a brief overview of digital images and their use in image steganography. Subsequently, the major image steganography techniques are as well covered, with a focus on the spatial domain technique. Additionally, common metrics that are used to assess the efficiency of image steganography approaches are introduced. Finally, some related works and challenges of image steganography are pre- sented.
Chapter 3 contains an introduction to bio-inspired searching algo- rithms. Moreover, the behavior of bees in nature, its algorithm, its block diagram, and some of its applications are presented. In addition, the cuckoo bird’s behaviour, its algorithm, and its block diagram are presented, along with some of its applications. At the end, the crow’s food-gathering behaviour, its algorithm, its block diagram, and some of its applications are covered.
In Chapter 4, the suggested modifications to the crow search algo- rithm, NECSA, and its block diagram are explained. As well, the pro- posed steganography approach, SNECSA, the extraction algorithm, and their block diagrams are demonstrated. Furthermore, the prac-
tical analysis of the modifications and parameter settings are given. Then, comparisons between CSA, SNECSA, and some previous tech- niques in both gray and color images are presented. Our results show that the proposed approach outperforms others with respect to peak signal-to-noise ratio, bit error rate, and number of pixel changes. In gray images, the average peak signal-to-noise ratios achieved by the proposed approach are approximately 76.25 dB, 73.47 dB, and 71 dB. While in color images, the achieved values are 83.76 dB, 80.9 dB, and
78.7 dB in color images on the tested data set. Additionally, the pro- posed approach has been applied in medical image application and proven its efficiency. Finally, the ability to resist stego-attacks, along with the limitations and implications of this work, are highlighted.
Lastly, Chapter 5 gives a conclusion to this thesis. We summarize the obtained results by proposing a new algorithm for hiding informa- tion based on improving the search algorithm of the crow while high- lighting the efficiency of its results compared to others. The chapter also suggests a few possible directions for future studies in this area.