An Experimental Analysis on Independent Component Analysis Signcryption Algorithm Video Steganography

INTRODUCTION

Video Steganography is a mechanism for hiding multimedia data into a multimedia file. The multimedia data which is to be embedded into another file is referred to as a plain data or a message and the multimedia file which is used to hide the message is referred to as cover of the plain data. In this proposed system Steganography as a tool is utilized for face recognition to improve the security and to enhance identification of similar faces. Signcryption is a unique authentication method to identify a person who accesses a computer system. The proposed method was compared with the existing algorithms to assess the efficiency of our system. The experimental results with the different algorithm and different file formats showed a better performance. As an improvement, in this system a new recognition system using PCASA within Video Steganography is used.

Steganography is the exercise of concealing valuable information within audio of video file which cannot be seen by normal users. It confuses people because both cryptography and steganography look as similar in the sense that they are used to protect the information. However, steganography is hiding information without knowing others. If anybody tried to see the multimedia with the intention of knowing the hidden data, it cannot be viewed by them. The statement steganography has a Greek origin. It is a combination of steganos and graptos. ‗Steganos‘ means covered, ‗graptos‘ means writing. It allows concealing a message or any digital information into either audio or video file. It exploits the human perception. Steganalysis in Steganography technique we used to transmit a secret message from a sender to a receiver in such a way that only receiver can read the existence message no intermediate person can read the message. In steganography we can hide the information in the form of image, text, audio and video. In old time, we protected data by hiding it on the back of wax and writing tables. Steganography is a security technique for long transmission. To hide secret information or data in images, there are number of steganography techniques in which some are easy while other are complex all of them have their strong and weak points.

Signcryption is one of cryptography methods which can perform the functions of both digital unique user signature and encryption. These tools can ensure the primary properties of information security such as confidentiality, integrity and reducing redundancy. In Data hiding in audio signal, video signal text and JPEG Images: In this paper the author introduced a robust method of imperceptible text, audio, video and image hiding. They provide an efficient method for hiding the data

An earlier method of digital sign has three different functionalities these are: signature gathering, digitalization, and encryption. The problems of these traditional methods are low efficiency and high cost absorption method. The integration cost is also high. Signcryption is a new cryptographic technique that is worth fulfilling those functionalities in a single step. It reduces the computational costs and solves communication problems. The normal signcryption method uses a single session key which is reusable for several encryption methods. The problem of the single session key causes low security when a plain text model is chosen. This is the reason for choosing a random session key for a hybrid encryption scheme.

Figure 1 Block diagram of ICASA Figure 3.1 illustrates the block diagram of ICASA. There are nine important stages. 1. Capture of video 2. Face detection 3. Collection of different postures of face 4. Test signcrypted images when face is already exists 5. Comparison with existing image 6. Features extraction 7. Eigen faces 8. Nearest eigen classifiers 9. Reorganization statistics. Clearly, for any non-Gaussian distribution, largest variances would not correspond to PCA basis vectors. Independent Component Analysis (ICA) minimizes both second-order and higherorder dependencies in the input data and attempts to find the basis along which the data (when projected onto them) are statistically independent. Here provided two architectures of ICA for face recognition task: Architecture I – statistically independent basis images (ICA1 in our experiments) and Architecture II – factorial code representation (ICA2 in our experiments), with an addition of signcryption algorithm.

Use case diagram explores the functions of the system and the variety of users of the system. The main components of the use case diagram: 1. Actor: It represents the variety of users of the system. Classifications of the actors are primary, secondary, off-stage. a. Primary actor – The person who demands the service of the system is considered as the primary actor. b. Secondary actor – is the provider of the service directly to the customer or user. c. Off-stage actor – is the person or system who acts as an intermediary in between the service request actor, the service to do the service, is considered as the supportive actor. In the system, profounded in this research work, users are considered as the primary actors to get the service from the system. ICASA system is considered as the secondary actor. The signature recognizer is the supportive actor. The encryption system is the off-stage actor. A fundamental problem in neural network research, as well as in many other disciplines, is finding a suitable representation of multivariate data, i.e. random vectors. For reasons of computational and conceptual simplicity, the representation is often sought as a linear transformation of the original data. In other words, each component of the representation is a linear combination of the original variables. Well-known linear transformation methods include principal component analysis, factor analysis, and projection pursuit. Independent component analysis syncryption algorithm (ICASA) is a redeveloped method in which the goal is to find a linear representation of nongaussian data so that the components are statistically independent, or as independent as possible. 2. Use cases: Use cases are the text which depicts the common services of the system. The role of each actor is: User (primary actor) – request entry of the service of the system. ICASA (secondary actor) – provides the service for recognition of the right user. Signature recognizer (supportive actor) – receives the user‘s signature. Encryption system (off-stage actor) – encrypts the data. Six use cases are derived from Figure 2. They are: 1. Login – is the process that is used by the user to enter into the system by giving their data. 2. Capture video – is the process for getting the face posture of the user; system automatically will take the video clip. 3. Get sign – is the process of the system that requests the signature from the user. 4. Match data – is the process of the system for checking the new input with the existing one. 6. Update trained set – This is the process wherein, whenever a user enters into the system, the system will update the different face postures.

Components of the class diagrams are i) Classes – Real time group of objects. ii) Aggregations – Collection of classes under one group. iii) Generalization – General group name of combined sub groups. iv) Specialization-Special group name of specific sub groups. v) Inheritance-Relaying the attributes and behavior to its sub classes. vi) Cardinality – Number of connectivity in the cardinal way. vii) Modality - Availability of connectivity. viii) Multiplicity - Number of connectivities belongs to its classes. ix) Role name - Name of the behavior. x) Attributes - Qualities in nature. xi) Functions – Methods to do its works. xii) Accessibility – Mode of visibility and retrieval authenticity. a) Classes and their structure and behavior – Class names are indicated at the top of the class diagram as users, video, and sign. Each rectangle box indicates the attributes and behavior of the class. It has three compartments. The top compartment indicates the name of the class or object. The middle compartment indicates characteristics, qualities, attributes of the class. The bottom compartment indicates the functionalities of the class.

If more than one class is needed for connection with another class, the middle agent is considered as association class. Aggregation allows a combination of several classes. Figure 3 shows the dependency between the classes by messages over an arrow. Multiple and multi-level inheritance can also be denoted by hollow arrows. c) Multiplicity and navigation indicators – Multiplicity is one of the characteristics of the class diagram used to denote the number of relationships. Navigation indicators are used to indicate the directions of the message passing by arrow. d) Role names – Most of the class names are created by the role names.

Figure 3 illustrates relationship between user, video and sign. Figure 5 Class diagram2 Figures 3and 4 illustrate the attributes and functions of the objects. of the system and its behavior. Components of the activity diagrams are: Swim lanes: They assign the proper path of space for the objects by dividing such objects over lines. States of the action: Represent the actions of the entities as in the system flow steps. Action flows: The flow of actions is represented by arrows with its respective responsibilities. Object flows: It controls the action states. Figure 6 Activity diagram Figure 6 illustrates the entire range of activities of the PCASA system. The filled circle represents the start of the process. The rounded rectangle symbol represents activities. The diagonal symbol represents decision making conditional statements. The solid arrows represent the flow of the process. Rounded filled circle represents that the activities are halted.

The sequence diagram is used to pass the messages in between two classes or objects. It mainly concentrates on classes and the inter communication of its works by message passing. • These diagrams focus on classes and the messages they exchange to accomplish some desired behavior. • Sequence diagrams are a type of interaction diagrams. They have the following components: Class roles: Represents play roles of an object. Activation: Represent the time during which an object is performing an operation. Messages: Represent communication between objects.

Figure 7 Sequence diagram - Scenario 1 Scenario 2: If existing user comes

Figure 7 explains the scenario of a new user entering the system. Figure 8 explains the scenario of an existing system user‘s log in. Figure 9 illustrates the activity when the same user comes in but in a different style. Figure 10 illustrates the activity when an entirely different user looks like the existing one. The sequence diagram demonstrates the interactions between the user and the system. Rectangle boxes are represented by the objects. The solid arrow which carries message from left to right request the service to the system. Dotted arrow represents responses from the system. Messages are explained by the functions of each object.

Scenario 4: If different user, looking as existing one

In order to enhance the security of the system proposed, the system enables signcryption for the given user‘s data. PCASA generates the signcrypted images. The given signature is fragmented into several parts and is stored into the eigen faces. Then, the system will generate the DSC. The following sections illustrate signcryption on video steganography. To create signcrypted images, following steps are carried out by the PCASA system.

In order to manipulate the signcrypted image, we need a sample signature of the user. Figure 11 shows the sample user‘s signatures. To get user signature, system needs drawing tablet.

Figure 12 Fragmented signature image Figure 12 shows the fragmented signature images of given input image as shown in Figure 13. This input image has been cropped into four parts shown as Figures 14, 15, 16and 17. Figure 13 Input image Figure 14 Part 1 Figure 15 Part 2 Figure 16 Part 3

The scrambled parts of the signature have been embedded into existing captured images using ICASA. Hereafter, it will be called as signcrypted image.

Figure 18 shows the signcrypted image. Fragmented signature has been stored into corresponding user‘s video clipping.

Input and output files are look as same. There is no variation in between the file size. Figure 19 Before video steganography (3.66MB) Figure 20 After video steganography (3.66MB) Figures 19 and 20 show the sample input, output video clippings. These are looking as identical. However, persons with technical knowledge will

Steganography is an art work to conceal the data into a multimedia file. The purpose of using a multimedia file after than any other file is to accommodate a huge amount of information. The experimental results of the proposed system which we get from ICASA. Thus, the user has been identified using ICASA successfully without any distortion on the picture. Resultant output shows that the file size of both input and output are same. Thus the research work has been done to achieve a secure and unique face recognition system by innovative way of using signcryption and video steganography.

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Research Scholar, Shri Venkateshwara University, Uttar Pradesh