CHAPTER ONE

INTRODUCTION

1. 1. Background of the Study

Since the rise of the Internet one of the most important factors of information technology and communication has been the security of information. Cryptography was created as a technique for securing the secrecy of communication and many different methods have been developed to encrypt and decrypt data in order to keep the message secret. Unfortunately, it is sometimes not enough to keep the contents of a message secret, it may also be necessary to keep the existence of the message secret. The technique used to implement this, is called steganography. Steganography is the art and science of invisible communication (Bin, 2011). This is accomplished through hiding information in other information, thus hiding the existence of the communicated information. The word steganography is derived from the Greek words “stegos” meaning “cover” and “grafia” meaning “writing” defining it as “covered writing”. In image steganography the information is hidden exclusively in images (Morkel, 2005).

The idea and practice of hiding information has a long history. In Histories, the Greek historian Herodotus writes of a nobleman, Histaeus, who needed to communicate with his son-in-law in Greece. He shaved the head of one of his most trusted slaves and tattooed the message onto the slave’s scalp. When the slave’s hair grew back the slave was dispatched with the hidden message (Silman, 2001). In the Second World War the Microdot technique was developed by the Germans. Information, especially photographs, was reduced in size until it was the size of a typed period. Extremely difficult to detect, a normal cover message was sent over an insecure channel with one of the periods on the paper containing hidden information (Morkel, 2005).

Today steganography is mostly used on computers with digital data being the carriers and networks being the high-speed delivery channels. Steganography differs from cryptography in the sense that where cryptography focuses on keeping the contents of a message secret, steganography focuses on keeping the existence of a message secret. Steganography is the science of hiding information whose goal is to hide even the existence of secret messages in an innocent-like cover image, called the stego-image. Against steganography, steganalysis is the science of detecting the existence of hidden messages in a stego-image (Joo, 2010).

Steganalysis and steganography are the two different sides of the same coin. Steganography tries to hide messages in plain sight while steganalysis tries to detect their existence or even more to retrieve the embedded data. Both steganography and steganalysis received a great deal of attention, especially from law enforcement. While cryptography in many countries is being outlawed or limited, cyber criminals or even terrorists are extensively using steganography to avoid being arrested with encrypted incriminating material in their possession. Therefore, understanding the ways that messages can be embedded in a digital medium in most cases in digital images, and knowledge of state-of-the-art methods to detect hidden information, is essential in exposing criminal activity. Digital image steganography is growing in use and application. Many powerful and robust methods of steganography and steganalysis have been presented in many literatures over the last few years (Karampidis, 2018).

By investigating the flaws of many steganographic methods, steganalysis researchers have studied to design steganalysis methods to defeat steganography. As a result, efficient steganalysis methods such as least significant bit which are specific to each steganography method have been developed. However, these approaches have required human intervention to determine their flaws and its time consuming to analyze steganography methods. Also, universal steganalysis methods applicable to all kinds of steganography methods are still required to be studied (Kim, 2017).

1. 2. Statement of the Problem

According to government officials, terrorists use to hide secret information of their targets in images, which is quite evident that terrorist cells use steganography to conceal information and secretly communicate information among themselves. This is rumored to be a common technique used by Boko-Haram and other terrorist groups. This is been achieved by posting an encrypted image on a website or through an email for download by another terrorist cell and using the same Steganography program, the terrorist cell could then reveal the message with plans for a new attack.

Furthermore, the confidentiality of patient’s medical records such as patient’s bio data and test results has been a challenge, thus with the aid of a deep learning steganalysis technique patient’s record could be encrypted on their photographs or x-ray scans. On the other hand, the secrecy of some specific press information has also been a major challenge to the practice of journalism. Thus, the need for a deep learning steganalysis technique.

1.3     Aim and Objectives of the Study

The aim of this project work is to design and implement a hidden message extraction system using deep learning steganalysis technique. The specific objectives include;

i. To review related literatures pointing to hidden message extraction using different steganalysis techniques.

ii. To design and implement a software that allows the detection of hidden message on an image using deep learning.

iii. To design and implement a software that allows the extraction of hidden messages on an image using deep learning.

1.4     Significance of Study.

This research work will help in tackling the problems involve in other methods of steganalysis which requires human intervention by using convolutional neural network.

The Steganalysis using deep convolutional neural network is relevant in the following ways;

i.   The Steganalysis using deep convolutional neural network will aid in carrying out digital forensic investigation.

ii.  The designed software will be useful to law enforcement agencies in unveiling terrorist communication concealed in images via steganography.

iii. The proposed system will be also relevant in medical imaging, and journalism

1.5     Scope of the Study

This research is centered on detecting and extracting hidden messages, embedded on images by using convolutional neural network as a deep learning steganalysis technique. The CNN based steganalysis will be based on image steganalysis only.

1.6     Definition of Terms

TERRORIST CELL: is a group of usually 3 to 5 members of a terrorist group to insure operational security to the end that members of adjacent terrorist cells usually don't know each other or the identity of their leadership.

COMMUNICATION: Communication is the act of conveying meanings from one entity or group to another through the use of mutually understood signs, symbols, and semiotic rules.

CRYPTOGRAPHY: Cryptography or cryptology is the practice and study of techniques for secure communication in the presence of third parties called adversaries.

DATA EXTRACTION: is the act or process of retrieving data out of (usually unstructured or poorly structured) data sources for further data processing or data storage (data migration).

DECRYPTION: Decryption is generally the reverse process of encryption. It is the process of decoding the data which has been encrypted into a secret format.

 DEEP LEARNING: Deep learning is an artificial intelligence function that imitates the workings of the human brain in processing data and creating patterns for use in decision making.

ENCRYPTION: Encryption is the process of encoding a message or information in such a way that only authorized parties can access it and those who are not authorized cannot.

IMAGE: a representation of the external form of a person or thing in art.

CONVOLUTIONAL NEURAL NETWORK: In deep learning a convolutional neural network is a class of deep neural networks, most commonly applied to analyzing visual imagery. CNNs are regularized versions of multilayer perceptrons.

MESSAGE: Message is a verbal, written, or recorded communication sent to or left for a recipient who cannot be contacted directly.

PARAMETRIC MODEL: a parametric model or parametric family or finite-dimensional model is a particular class of statistical models. Specifically, a parametric model is a family of probability distributions that has a finite number of parameters.

STEGANALYSIS: is the study of detecting messages hidden using steganography; this is analogous to cryptanalysis applied to cryptography.

STEGANOGRAPHY: Steganography is the practice of concealing a file, message, image, or video within another file, message, image, or video.

TECHNIQUE: a way of carrying out a particular task, especially the execution or performance of an artistic work or a scientific procedure.

TEXT: text is any object that can be "read", whether this object is a work of literature, a street sign, an arrangement of buildings on a city block, or styles of clothing. It is a coherent set of signs that transmits some kind of informative message.