Audio steganography based on least significant bits algorithm with 4D grid multi-wing hyper-chaotic system

Although variety in hiding methods used to protect data and information transmitted via channels but still need more robustness and difficulty to improve protection level of the secret messages from hacking or attacking. Moreover, hiding several medias in one media to reduce the transmission time and band of channel is the important task and define as a gain channel. This calls to find other ways to be more complexity in detecting the secret message. Therefore, this paper proposes cryptography/steganography method to hide an audio/voice message (secret message) in two different cover medias: audio and video. This method is use least significant bits (LSB) algorithm combined with 4D grid multi-wing hyper-chaotic (GMWH) system. Shuffling of an audio using key generated by GMWH system and then hiding message using LSB algorithm will provide more difficulty of extracting the original audio by hackers or attackers. According to analyses of obtained results in the receiver using peak signal-to-noise ratio (PSNR)/mean square error (MSE) and sensitivity of encryption key, the proposed method has more security level and robustness. Finally, this work will provide extra security to the mixture base of crypto-steganographic methods.

Self embedding digital watermark using hybrid method against compression attack

<p>In the modern time interacting with digital world become standard life activity, human need a way to protect properties as individuals or corporals, and we do that by embedding a digital mark to the target, and this technique call digital watermarking. But there still is a chance to manipulate or even remove this marks we embed for protection with various attacks like adding noises, compression-decompression or bits manipulations, and that why companions, individuals, laboratories are still developing new methods to embed this marks and make them more robust and more hard to detect for others. There are so many methods for digital watermarking, so we chose the least significant bits watermarking (LSB-watermarking) to provide an invisible digital watermarking, and on top of that we proceed with the blind LSB-watermarking method so that we don't get bind to the original image, and for our attack we chose compression joint photographic experts group (JPEG) compression because it’s the most used method for image and videos compression along with singular value decomposition (SVD) to make our mark as robust as possible. And the results we gain from our method are promising and it did give as high quality digital watermarking.</p>

Robust image data hiding method based on multiple backups and pixel bit weight

Digital images are easily corrupted by attacks during transmission and most data hiding methods have limitations in resisting cropping and noise attacks. Aiming at this problem, we propose a robust image data hiding method based on multiple backups and pixel bit weight (PBW). Especially multiple backups of every pixel bit are pre-embedded into a cover image according to a reference matrix. Since different pixel bits have different weights, the most significant bits (MSBs) occupy more weights on the secret image than those of the least significant bits (LSBs). Accordingly, some backups of LSBs are substituted by the MSBs to increase the backups of MSBs so that the quality of the extracted secret image can be improved. Experimental results show that the proposed algorithm is robust to cropping and noise attacks for secret image.

A Hybrid Radix-4 and Approximate Logarithmic Multiplier for Energy Efficient Image Processing

Multiplication is an essential image processing operation commonly implemented in hardware DSP cores. To improve DSP cores’ area, speed, or energy efficiency, we can approximate multiplication. We present an approximate multiplier that generates two partial products using hybrid radix-4 and logarithmic encoding of the input operands. It uses the exact radix-4 encoding to generate the partial product from the three most significant bits and the logarithmic approximation with mantissa trimming to approximate the partial product from the remaining least-significant bits. The proposed multiplier fills the gap between highly accurate approximate non-logarithmic multipliers with a complex design and less accurate approximate logarithmic multipliers with a more straightforward design. We evaluated the multiplier’s efficiency in terms of error, energy (power-delay-product) and area utilisation using NanGate 45 nm. The experimental results show that the proposed multiplier exhibits good area utilisation and energy consumption and behaves well in image processing applications.

Analytical cryptanalysis upon N = p2q utilizing Jochemsz-May strategy

This paper presents a cryptanalytic approach on the variants of the RSA which utilizes the modulus N = p2q where p and q are balanced large primes. Suppose e∈Z+ satisfying gcd(e, ϕ(N)) = 1 where ϕ(N) = p(p − 1)(q − 1) and d < Nδ be its multiplicative inverse. From ed − kϕ(N) = 1, by utilizing the extended strategy of Jochemsz and May, our attack works when the primes share a known amount of Least Significant Bits(LSBs). This is achievable since we obtain the small roots of our specially constructed integer polynomial which leads to the factorization of N. More specifically we show that N can be factored when the bound δ<119−294+18γ. Our attack enhances the bound of some former attacks upon N = p2q.

New Jochemsz–May Cryptanalytic Bound for RSA System Utilizing Common Modulus N = p2q

This paper describes an attack on the Rivest, Shamir and Adleman (RSA) cryptosystem utilizing the modulus N=p2q where p and q are two large balanced primes. Let e1,e2<Nγ be the integers such that d1,d2<Nδ be their multiplicative inverses. Based on the two key equations e1d1−k1ϕ(N)=1 and e2d2−k2ϕ(N)=1 where ϕ(N)=p(p−1)(q−1), our attack works when the primes share a known amount of least significant bits (LSBs) and the private exponents share an amount of most significant bits (MSBs). We apply the extended strategy of Jochemsz–May to find the small roots of an integer polynomial and show that N can be factored if δ<1110+94α−12β−12γ−130180γ+990α−180β+64. Our attack improves the bounds of some previously proposed attacks that makes the RSA variant vulnerable.

Any-Precision Deep Neural Networks

We present Any-Precision Deep Neural Networks (Any- Precision DNNs), which are trained with a new method that empowers learned DNNs to be flexible in any numerical precision during inference. The same model in runtime can be flexibly and directly set to different bit-width, by trun- cating the least significant bits, to support dynamic speed and accuracy trade-off. When all layers are set to low- bits, we show that the model achieved accuracy compara- ble to dedicated models trained at the same precision. This nice property facilitates flexible deployment of deep learn- ing models in real-world applications, where in practice trade-offs between model accuracy and runtime efficiency are often sought. Previous literature presents solutions to train models at each individual fixed efficiency/accuracy trade-off point. But how to produce a model flexible in runtime precision is largely unexplored. When the demand of efficiency/accuracy trade-off varies from time to time or even dynamically changes in runtime, it is infeasible to re-train models accordingly, and the storage budget may forbid keeping multiple models. Our proposed framework achieves this flexibility without performance degradation. More importantly, we demonstrate that this achievement is agnostic to model architectures. We experimentally validated our method with different deep network backbones (AlexNet-small, Resnet-20, Resnet-50) on different datasets (SVHN, Cifar-10, ImageNet) and observed consistent results.

ACO Based Variable Least Significant Bits Data Hiding in Edges Using IDIBS Algorithm

This work presents a double asymmetric data hiding technique. The first asymmetry is created by hiding secret data in the complex region of the cover image and keep the smooth region unaffected. Then another asymmetry is developed by hiding a different number of secret bits in the various pixels of the complex region. The proposed technique uses the ant colony optimization (ACO) based technique for the classification of complex and smooth region pixels. Then, the variable least significant bits (VLSB) data hiding framework is used to hide secret bits in the complex region of the cover image. A distance-based substitution technique, namely increasing distance increasing bits substitution algorithm, is used to ensure the asymmetry in the number of hidden bits. The double asymmetric framework enhances the security of the hidden secret data and makes the retrieval of hidden information difficult for unauthorized users. The algorithm results in high-quality stego images, and the hidden information does not attract the human visual system (HVS).