Chaotic Spreading Sequence for Spread Spectrum Modulation in Stochastic Wireless Channels

In wireless communication system, spread spectrum techniques have been widely used because of the advantages like robustness against interference and noise, low probability of intercept, realization of Code Division Multiple Access (CDMA) and so on. One of the key aspects in such methods is the generation of the spreading sequence which continues to be challenging issue. This paper proposes a scheme for generating binary sequences from chaotic logistic map for use in Direct Sequence Spread Spectrum (DS SS) system in fading environment. The main advantages of such usage are increased security of the data transmission and ease of generation of a extended numbers of chaotic sequences. Generally to spread the bandwidth of the transmitting signals, pseudo-noise (PN) sequences, Gold sequences have been used extensively. We have generated a binary spreading sequences using logistic map. A comparison between Gold sequences and proposed sequences in faded environment have been derived. It is clearly seen that our sequences are comparable and even superior to Gold sequences in several key aspects such as bit error rate (BER), computational time and mutual information for three different spreading code lengths. Therefore, the proposed sequences can be effectively used as spreading sequences in high data rate modulation schemes.Keywords: Logistic map code, Gold code, BER, DS SS.Cite as: Katyayani Kashyap, Manash Pratim Sarma, Kandarpa Kumar Sarma, “Chaotic Spreading Sequence for Spread Spectrum Modulation in Stochastic Wireless Channels†ADBU J.Engg.Tech., 1(2014) 0011402(5pp

Application of Stochastic Diffusion for Hiding High Fidelity Encrypted Images

Cryptography coupled with information hiding has received increased attention in recent years and has become a major research theme because of the importance of protecting encrypted information in any Electronic Data Interchange system in a way that is both discrete and covert. One of the essential limitations in any cryptography system is that the encrypted data provides an indication on its importance which arouses suspicion and makes it vulnerable to attack. Information hiding of Steganography provides a potential solution to this issue by making the data imperceptible, the security of the hidden information being a threat only if its existence is detected through Steganalysis. This paper focuses on a study methods for hiding encrypted information, specifically, methods that encrypt data before embedding in host data where the ‘data’ is in the form of a full colour digital image. Such methods provide a greater level of data security especially when the information is to be submitted over the Internet, for example, since a potential attacker needs to first detect, then extract and then decrypt the embedded data in order to recover the original information. After providing an extensive survey of the current methods available, we present a new method of encrypting and then hiding full colour images in three full colour host images with out loss of fidelity following data extraction and decryption. The application of this technique, which is based on a technique called ‘Stochastic Diffusion’ are wide ranging and include covert image information interchange, digital image authentication, video authentication, copyright protection and digital rights management of image data in general

On the Application of PSpice for Localised Cloud Security

The work reported in this thesis commenced with a review of methods for creating random binary sequences for encoding data locally by the client before storing in the Cloud. The first method reviewed investigated evolutionary computing software which generated noise-producing functions from natural noise, a highly-speculative novel idea since noise is stochastic. Nevertheless, a function was created which generated noise to seed chaos oscillators which produced random binary sequences and this research led to a circuit-based one-time pad key chaos encoder for encrypting data. Circuit-based delay chaos oscillators, initialised with sampled electronic noise, were simulated in a linear circuit simulator called PSpice. Many simulation problems were encountered because of the nonlinear nature of chaos but were solved by creating new simulation parts, tools and simulation paradigms. Simulation data from a range of chaos sources was exported and analysed using Lyapunov analysis and identified two sources which produced one-time pad sequences with maximum entropy. This led to an encoding system which generated unlimited, infinitely-long period, unique random one-time pad encryption keys for plaintext data length matching. The keys were studied for maximum entropy and passed a suite of stringent internationally-accepted statistical tests for randomness. A prototype containing two delay chaos sources initialised by electronic noise was produced on a double-sided printed circuit board and produced more than 200 Mbits of OTPs. According to Vladimir Kotelnikov in 1941 and Claude Shannon in 1945, one-time pad sequences are theoretically-perfect and unbreakable, provided specific rules are adhered to. Two other techniques for generating random binary sequences were researched; a new circuit element, memristance was incorporated in a Chua chaos oscillator, and a fractional-order Lorenz chaos system with order less than three. Quantum computing will present many problems to cryptographic system security when existing systems are upgraded in the near future. The only existing encoding system that will resist cryptanalysis by this system is the unconditionally-secure one-time pad encryption

IoT-Based Multi-Dimensional Chaos Mapping System for Secure and Fast Transmission of Visual Data in Smart Cities

A “smart city” sends data from many sensors to a cloud server for local authorities and the public to connect. Smart city residents communicate mostly through images and videos. Many image security algorithms have been proposed to improve locals’ lives, but a high-class redundancy method with a small space requirement is still needed to acquire and protect this sensitive data. This paper proposes an IoT-based multi-dimensional chaos mapping system for secure and fast transmission of visual data in smart cities, which uses the five dimensional Gauss Sine Logistic system to generate hyper-chaotic sequences to encrypt images. The proposed method also uses pixel position permutation and Singular Value Decomposition with Discrete fractional cosine transform to compress and protect the sensitive image data. To increase security, we use a chaotic system to construct the chaotic sequences and a diffusion matrix. Furthermore, numerical simulation results and theoretical evaluations validate the suggested scheme’s security and efficacy after compression encryption.publishedVersio

Utility of Experimental Design in Automatic Target Recognition Performance Evaluation

This research investigates current practices in test and evaluation of classification algorithms, and recommends improvements. We scrutinize the evaluation of automatic target recognition algorithms and rationalize the potential for improvements in the accepted methodology. We propose improvements through the use of an experimental design approach to testing. We demonstrate the benefits of improvements by simulating algorithm performance data and using both methodologies to generate evaluation results. The simulated data is varied to test the sensitivity of the benefits to a broad set of outcomes. The opportunities for improvement are threefold. First, the current practice of \u27one-at-a-time factor variation (only one factor is varied in each test condition) fails to capture the effect of multiple factors. Next, the coarse characterization of data misses the opportunity to reduce the estimate of noise in test through the observation of uncontrolled factors. Finally, the lack of advanced data reduction and analysis tools renders analysis and reporting tedious and inefficient. This research addresses these shortcomings and recommends specific remedies through factorial testing, detailed data characterization, and logistic regression. We show how these innovations improve the accuracy and efficiency of automatic target recognition performance evaluation

Entropy in Image Analysis III

Image analysis can be applied to rich and assorted scenarios; therefore, the aim of this recent research field is not only to mimic the human vision system. Image analysis is the main methods that computers are using today, and there is body of knowledge that they will be able to manage in a totally unsupervised manner in future, thanks to their artificial intelligence. The articles published in the book clearly show such a future

Digital Signal Processing (Second Edition)

This book provides an account of the mathematical background, computational methods and software engineering associated with digital signal processing. The aim has been to provide the reader with the mathematical methods required for signal analysis which are then used to develop models and algorithms for processing digital signals and finally to encourage the reader to design software solutions for Digital Signal Processing (DSP). In this way, the reader is invited to develop a small DSP library that can then be expanded further with a focus on his/her research interests and applications. There are of course many excellent books and software systems available on this subject area. However, in many of these publications, the relationship between the mathematical methods associated with signal analysis and the software available for processing data is not always clear. Either the publications concentrate on mathematical aspects that are not focused on practical programming solutions or elaborate on the software development of solutions in terms of working ‘black-boxes’ without covering the mathematical background and analysis associated with the design of these software solutions. Thus, this book has been written with the aim of giving the reader a technical overview of the mathematics and software associated with the ‘art’ of developing numerical algorithms and designing software solutions for DSP, all of which is built on firm mathematical foundations. For this reason, the work is, by necessity, rather lengthy and covers a wide range of subjects compounded in four principal parts. Part I provides the mathematical background for the analysis of signals, Part II considers the computational techniques (principally those associated with linear algebra and the linear eigenvalue problem) required for array processing and associated analysis (error analysis for example). Part III introduces the reader to the essential elements of software engineering using the C programming language, tailored to those features that are used for developing C functions or modules for building a DSP library. The material associated with parts I, II and III is then used to build up a DSP system by defining a number of ‘problems’ and then addressing the solutions in terms of presenting an appropriate mathematical model, undertaking the necessary analysis, developing an appropriate algorithm and then coding the solution in C. This material forms the basis for part IV of this work. In most chapters, a series of tutorial problems is given for the reader to attempt with answers provided in Appendix A. These problems include theoretical, computational and programming exercises. Part II of this work is relatively long and arguably contains too much material on the computational methods for linear algebra. However, this material and the complementary material on vector and matrix norms forms the computational basis for many methods of digital signal processing. Moreover, this important and widely researched subject area forms the foundations, not only of digital signal processing and control engineering for example, but also of numerical analysis in general. The material presented in this book is based on the lecture notes and supplementary material developed by the author for an advanced Masters course ‘Digital Signal Processing’ which was first established at Cranfield University, Bedford in 1990 and modified when the author moved to De Montfort University, Leicester in 1994. The programmes are still operating at these universities and the material has been used by some 700++ graduates since its establishment and development in the early 1990s. The material was enhanced and developed further when the author moved to the Department of Electronic and Electrical Engineering at Loughborough University in 2003 and now forms part of the Department’s post-graduate programmes in Communication Systems Engineering. The original Masters programme included a taught component covering a period of six months based on two semesters, each Semester being composed of four modules. The material in this work covers the first Semester and its four parts reflect the four modules delivered. The material delivered in the second Semester is published as a companion volume to this work entitled Digital Image Processing, Horwood Publishing, 2005 which covers the mathematical modelling of imaging systems and the techniques that have been developed to process and analyse the data such systems provide. Since the publication of the first edition of this work in 2003, a number of minor changes and some additions have been made. The material on programming and software engineering in Chapters 11 and 12 has been extended. This includes some additions and further solved and supplementary questions which are included throughout the text. Nevertheless, it is worth pointing out, that while every effort has been made by the author and publisher to provide a work that is error free, it is inevitable that typing errors and various ‘bugs’ will occur. If so, and in particular, if the reader starts to suffer from a lack of comprehension over certain aspects of the material (due to errors or otherwise) then he/she should not assume that there is something wrong with themselves, but with the author

Efficient simultaneous encryption and compression of digital videos in computationally constrained applications

This thesis is concerned with the secure video transmission over open and wireless network channels. This would facilitate adequate interaction in computationally constrained applications among trusted entities such as in disaster/conflict zones, secure airborne transmission of videos for intelligence/security or surveillance purposes, and secure video communication for law enforcing agencies in crime fighting or in proactive forensics. Video content is generally too large and vulnerable to eavesdropping when transmitted over open network channels so that compression and encryption become very essential for storage and/or transmission. In terms of security, wireless channels, are more vulnerable than other kinds of mediums to a variety of attacks and eavesdropping. Since wireless communication is the main mode in the above applications, protecting video transmissions from unauthorized access through such network channels is a must. The main and multi-faceted challenges that one faces in implementing such a task are related to competing, and to some extent conflicting, requirements of a number of standard control factors relating to the constrained bandwidth, reasonably high image quality at the receiving end, the execution time, and robustness against security attacks. Applying both compression and encryption techniques simultaneously is a very tough challenge due to the fact that we need to optimize the compression ratio, time complexity, security and the quality simultaneously. There are different available image/video compression schemes that provide reasonable compression while attempting to maintain image quality, such as JPEG, MPEG and JPEG2000. The main approach to video compression is based on detecting and removing spatial correlation within the video frames as well as temporal correlations across the video frames. Temporal correlations are expected to be more evident across sequences of frames captured within a short period of time (often a fraction of a second). Correlation can be measured in terms of similarity between blocks of pixels. Frequency domain transforms such as the Discrete Cosine Transform (DCT) and the Discrete Wavelet Transform (DWT) have both been used restructure the frequency content (coefficients) to become amenable for efficient detection. JPEG and MPEG use DCT while JPEG2000 uses DWT. Removing spatial/temporal correlation encodes only one block from each class of equivalent (i.e. similar) blocks and remembering the position of all other block within the equivalence class. JPEG2000 compressed images achieve higher image quality than JPEG for the same compression ratios, while DCT based coding suffer from noticeable distortion at high compression ratio but when applied to any block it is easy to isolate the significant coefficients from the non-significant ones. Efficient video encryption in computationally constrained applications is another challenge on its own. It has long been recognised that selective encryption is the only viable approach to deal with the overwhelming file size. Selection can be made in the spatial or frequency domain. Efficiency of simultaneous compression and encryption is a good reason for us to apply selective encryption in the frequency domain. In this thesis we develop a hybrid of DWT and DCT for improved image/video compression in terms of image quality, compression ratio, bandwidth, and efficiency. We shall also investigate other techniques that have similar properties to the DCT in terms of representation of significant wavelet coefficients. The statistical properties of wavelet transform high frequency sub-bands provide one such approach, and we also propose phase sensing as another alternative but very efficient scheme. Simultaneous compression and encryption, in our investigations, were aimed at finding the best way of applying these two tasks in parallel by selecting some wavelet sub-bands for encryptions and applying compression on the other sub-bands. Since most spatial/temporal correlation appear in the high frequency wavelet sub-bands and the LL sub-bands of wavelet transformed images approximate the original images then we select the LL-sub-band data for encryption and the non-LL high frequency sub-band coefficients for compression. We also follow the common practice of using stream ciphers to meet efficiency requirements of real-time transmission. For key stream generation we investigated a number of schemes and the ultimate choice will depend on robustness to attacks. The still image (i.e. RF’s) are compressed with a modified EZW wavelet scheme by applying the DCT on the blocks of the wavelet sub-bands, selecting appropriate thresholds for determining significance of coefficients, and encrypting the EZW thresholds only with a simple 10-bit LFSR cipher This scheme is reasonably efficient in terms of processing time, compression ratio, image quality, as well was security robustness against statistical and frequency attack. However, many areas for improvements were identified as necessary to achieve the objectives of the thesis. Through a process of refinement we developed and tested 3 different secure efficient video compression schemes, whereby at each step we improve the performance of the scheme in the previous step. Extensive experiments are conducted to test performance of the new scheme, at each refined stage, in terms of efficiency, compression ratio, image quality, and security robustness. Depending on the aspects of compression that needs improvement at each refinement step, we replaced the previous block coding scheme with a more appropriate one from among the 3 above mentioned schemes (i.e. DCT, Edge sensing and phase sensing) for the reference frames or the non-reference ones. In subsequent refinement steps we apply encryption to a slightly expanded LL-sub-band using successively more secure stream ciphers, but with different approaches to key stream generation. In the first refinement step, encryption utilized two LFSRs seeded with three secret keys to scramble the significant wavelet LL-coefficients multiple times. In the second approach, the encryption algorithm utilises LFSR to scramble the wavelet coefficients of the edges extracted from the low frequency sub-band. These edges are mapped from the high frequency sub-bands using different threshold. Finally, use a version of the A5 cipher combined with chaotic logistic map to encrypt the significant parameters of the LL sub-band. Our empirical results show that the refinement process achieves the ultimate objectives of the thesis, i.e. efficient secure video compression scheme that is scalable in terms of the frame size at about 100 fps and satisfying the following features; high compression, reasonable quality, and resistance to the statistical, frequency and the brute force attack with low computational processing. Although image quality fluctuates depending on video complexity, in the conclusion we recommend an adaptive implementation of our scheme. Although this thesis does not deal with transmission tasks but the efficiency achieved in terms of video encryption and compression time as well as in compression ratios will be sufficient for real-time secure transmission of video using commercially available mobile computing devices