Due to technology advancement, smart visual sensing required in terms of data transfer capacity, energy-efficiency, security, and computational-efficiency. The high-quality image transmission in visual sensor networks (VSNs) consumes more space, energy, transmission delay which may experience the various security threats. Image compression is a key phase of visual sensing systems that needs to be effective. This motivates us to propose a fast and efficient intelligent image transmission module to achieve the energy-efficiency, minimum delay, and bandwidth utilization. Compressive sensing (CS) introduced to speedily compressed the image to reduces the consumption of energy, time minimization, and efficient bandwidth utilization. However, CS cannot achieve security against the different kinds of threats. Several methods introduced since the last decade to address the security challenges in the CS domain, but efficiency is a key requirement considering the intelligent manufacturing of VSNs. Furthermore, the random variables selected for the CS having the problem of recovering the image quality due to the accumulation of noise. Thus concerning the above challenges, this paper introduced a novel one-way image transmission module in multiple input multiple output that provides secure and energy-efficient with the CS model. The secured transmission in the CS domain proposed using the security matrix which is called a compressed secured matrix and perfect reconstruction with the random matrix measurement in the CS. Experimental results outwards that the intelligent module provides energy-efficient, secured transmission with low computational time as well as a reduced bit error rate.

Visual sensor intelligent module based image transmission in industrial manufacturing for monitoring and manipulation problems

Comprehensive Survey of Image Steganography: Techniques, Evaluations, and Trends in Future Research

The manufacturing of intelligent and secure visual data transmission over the wireless sensor network is key requirement nowadays to many applications. The two-way transmission of image under a wireless channel needed image must compatible along channel characteristics such as band width, energy-efficient, time consumption and security because the image adopts big space under the device of storage and need a long time that easily undergoes cipher attacks. Moreover, Quizzical the problem for the additional time under compression results that, the secondary process of the compression followed through the acquisition consumes more time.,Hence, for resolving these issues, compressive sensing (CS) has emerged, which compressed the image at the time of sensing emerges as a speedy manner that reduces the time consumption and saves bandwidth utilization but fails under secured transmission. Several kinds of research paved path to resolve the security problems under CS through providing security such as the secondary process.,Thus, concerning the above issues, this paper proposed the Corvus corone module two-way image transmission that provides energy efficiency along CS model, secured transmission through a matrix of security under CS such as inbuilt method, which was named as compressed secured matrix and faultless reconstruction along that of eminent random matrix counting under CS.,Experimental outputs shows intelligent module gives energy efficient, secured transmission along lower computational timing also decreased bit error rate.

Manufacturing intelligent Corvus corone module for a secured two way image transmission under WSN

Book review: Applied cryptography: Protocols, algorithms, and source code in C

Recently, a lot of research has been done in chaotic cryptography field using different kinds of chaotic systems, like chaotic maps, which are being considered as one of the secure and efficient methods to protect confidential information. This article highlights that the main cryptography requirements demand that the new embedded cryptosystems have to be more efficient and secure, it means that they must be faster and offer greater security. For instance, the new cryptosystems require to be compatible with the new telecommunication protocols and, in addition, to be efficient in energy consumption. In this manner, this article introduces a process to improve the randomness of five chaotic maps that are implemented on a PIC-microcontroller. The improved chaotic maps are tested to encrypt digital images in a wireless communication scheme, particularly on a machine-to-machine (M2M) link, via ZigBee channels. We show that function mod 255 improves the randomness of the pseudo-random number generators (PRNG), which is verified performing NIST SP 800-22 statistical tests, histograms, phase-plane analysis, entropy, correlation of adjacent pixels, differential attacks, and using digital images of size 256 × 256 and 512 × 512 pixels. A comparative analysis is presented versus related works that also use chaotic encryption and classic algorithms, such as: AES, DES, 3DES and IDEA. The security analysis confirms that the proposed process to improve the randomness of chaotic maps, is appropriate to implement an encryption scheme that is secure and robust against several known attacks and other statistical tests. Finally, it was experimentally verified that this chaotic encryption scheme can be used in practical applications such as M2M and Internet of things (IoT).

Randomness improvement of chaotic maps for image encryption in a wireless communication scheme using PIC-microcontroller via Zigbee channels

Steganography is used to hide a secret message within a cover image, thereby yielding a stego image such that even the trace of the presence of secret information is wiped out. The purpose of steganography is to maintain secret communication between two users. Steganography has several technical challenges namely high hiding capacity and imperceptibility. In this paper we propose a modern steganographic technique with Integer Wavelet transform (IWT) and double key to achieve high hiding capacity, high security and good visual quality. Here cover image is converted in to wavelet transform co-efficients and the coefficients are selected randomly by using Key-1 for embedding the data. Key-2 is used to calculate the number of bits to be embedded in the randomly selected coefficients. Finally the Optimum Pixel Adjustment Process (OPAP) is applied to the stego image to reduce the data embedding error.

Wave (let) decide choosy pixel embedding for stego

Cryptography is a method for secure communication by hiding information with secret keys so that only authorised users can read and process it. Efficient random sequence generators provide robust cipher design for cryptographic applications; further, these sequences are used for data encryption. In this paper, the highly chaotic nature of hybrid chaos maps and neural network is combined to build a random number generator for cryptographic applications. A custom neural network with a user-defined layer transfer function is built to increase the generator’s randomness. In this work, the two-hybrid chaotic map’s control parameters and iteration value are designed as a layer transfer function to obtain high randomness. Colour image encryption is performed with the extracted sequences and deoxyribonucleic acid encoding technique. Various tests like NIST, attractor test and correlation are applied to the generator to show the degree of randomness. Simulation analysis such as keyspace, key sensitivity, statistical, differential analysis, and chosen-plaintext attack shows the encryption algorithm’s strength.

Colour image encryption based on customized neural network and DNA encoding

Steganography conceals the secret information inside the cover medium. There are two types of steganography techniques available practically. They are spatial domain steganography and Transform domain steganography. The objectives to be considered in the steganography methods are high capacity, imperceptibility and robustness. In this paper, a Color image steganography in transform domain is proposed. Reversible Integer Haar wavelet transform is applied to the R, G and B planes separately and the data is embedded in a random manner. Random selection of wavelet coefficients is based on the graph theory. This proposed system uses three different keys for embedding and extraction of the secret data, where key1(Subband Selection - SB) is used to select the Wavelet subband for embedding, key2(Selection of Co-effecients-SC) is used to select the co-efficients randomly and key3 (Selection of Bit length-SB) is used to select the number of bits to be embedded in the selected co-efficients. This method shows good imperceptibility, High capacity and Robustness.

High security image steganography using IWT and graph theory

Modern day information age is enriched with the advanced network communication expertise but unfortunately at the same time encounters infinite security issues when dealing with secret and/or private information. The storage and transmission of the secret information become highly essential and have led to a deluge of research in this field. In this paper, an optimistic effort has been taken to combine graceful graph along with integer wavelet transform (IWT) to implement random image steganography for secure communication. The implementation part begins with the conversion of cover image into wavelet coefficients through IWT and is followed by embedding secret image in the randomly selected coefficients through graph theory. Finally stegoimage is obtained by applying inverse IWT. This method provides a maximum of 44 dB peak signal to noise ratio (PSNR) for 266646 bits. Thus, the proposed method gives high imperceptibility through high PSNR value and high embedding capacity in the cover image due to adaptive embedding scheme and high robustness against blind attack through graph theoretic random selection of coefficients.

/pdf/a-graph-theory-practice-on-transformed-image-a-random-image-3so6unwroc.pdf

V. Thanikaiselvan

Papers

Wave (let) decide choosy pixel embedding for stego

Colour image encryption based on customized neural network and DNA encoding

High security image steganography using IWT and graph theory

A Graph Theory Practice on Transformed Image: A Random Image Steganography

Comparative analysis of integer wavelet transforms in reversible data hiding using threshold based histogram modification