Scaling Attacks Research Articles

Medical Image Authentication Method Based on the Wavelet Packet and Energy Entropy

The transmission of digital medical information is affected by data compression, noise, scaling, labeling, and other factors. At the same time, medical data may be illegally copied and maliciously tampered with without authorization. Therefore, the copyright protection and integrity authentication of medical information are worthy of attention. In this paper, based on the wavelet packet and energy entropy, a new method of medical image authentication is designed. The proposed method uses the sliding window to measure the energy of the detail information. In the time–frequency data distribution, the local details of the data are mined. The complexity of energy is quantitatively described to highlight the valuable information. Based on the energy weight, the local energy entropy is constructed and normalized. The adjusted entropy value is used as the feature vector of the authentication information. A series of experiments show that the authentication method has good robustness against shearing attacks, median filtering, contrast enhancement, brightness enhancement, salt-and-pepper noise, Gaussian noise, multiplicative noise, image rotation, scaling attacks, sharpening, JPEG compression, and other attacks.

Inverse Interpolation and Its Application in Robust Image Steganography

Traditional steganography methods are usually designed on a lossless channel; thus, messages are often not extracted correctly from an image transmitted over a lossy channel that includes attacks such as scaling. To address this issue, in recent years, the field of robust steganography has emerged. In this paper, the process of image scaling by interpolation is first observed and serves as the basis for proposing the idea of inverse interpolation. Subsequently, the idea of constructing an inverse interpolation equation set is proposed to solve the problem of intersectional blocks during the inverse interpolation process. Then, the scaling factor’s valid range of inverse interpolation is analyzed. Next, the inverse interpolation is successfully applied in robust image steganography. A method that combines antiscaling and antidetection is proposed. Afterward, actual tests on the top 9 mobile phone brands with 28 models and 2 social communication apps that are currently popular in China are done. The scaling factor’s valid range of the proposed method is verified to match the actual lossy channel. The experimental results show that the proposed method achieves a reliable extraction of embedded messages for common interpolation scaling attacks while maintaining high statistical detection resistance.

Fully distributed event-triggered secure consensus of general linear multi-agent systems under sequential scaling attacks

In this article, the secure consensus problem is studied for a general linear multi-agent system, where a fully distributed event-triggered scheme is introduced to increase the feasibility and improve the scalability of the control protocol. Firstly, an edge-based sequential scaling attack is formulated with constraints on the attack duration and the frequency, which includes multiplicative deception attacks and DoS attacks as a particular situation when the scaling factor is equal to 0. Then a fully distributed event-triggered control protocol is designed, in which the global information is no longer needed. Sufficient conditions related to triggering parameters, the scaling factor, the attack duration and attack frequency are derived ensuring the asymptotic consensus of MAS. Furthermore, the impact of the triggering parameters and the scaling factor on the attack duration and the attack frequency are also discussed. The Zeno behavior is proved not to happen. Finally, two simulation examples based on unmanned intelligent vehicles are conducted to verify the results.

Dynamic event-based finite-horizon [formula omitted] secure consensus control of a class of nonlinear multi-agent systems

In this paper, we investigate the H∞ consensus control issue for nonlinear multi-agent systems (MASs) subject to multiple attacks over a finite time interval. A novel and comprehensive model to characterize the multiple attacks is presented that includes denial-of-service (DoS) attacks, scaling attacks and replay attacks. With the hope of easing the communication burdens, we implement a dynamic event-triggered scheme to schedule the process of data sharing among the individual subsystems, which helps judge if the collected data should be shared to neighboring agents for control input update. The aim of the proposed problem is to develop an output feedback strategy to meet the desired H∞ consensus performance despite the existence of multiple attacks. Some conditions are presented for the solvability of the investigated problem, and the feedback gains are obtained via certain convex optimization algorithms. The proposed theoretical result is finally demonstrated by virtue of two illustrative simulation examples.

Artificial Intelligence Security: Threats and Countermeasures

In recent years, with rapid technological advancement in both computing hardware and algorithm, Artificial Intelligence (AI) has demonstrated significant advantage over human being in a wide range of fields, such as image recognition, education, autonomous vehicles, finance, and medical diagnosis. However, AI-based systems are generally vulnerable to various security threats throughout the whole process, ranging from the initial data collection and preparation to the training, inference, and final deployment. In an AI-based system, the data collection and pre-processing phase are vulnerable to sensor spoofing attacks and scaling attacks, respectively, while the training and inference phases of the model are subject to poisoning attacks and adversarial attacks, respectively. To address these severe security threats against the AI-based systems, in this article, we review the challenges and recent research advances for security issues in AI, so as to depict an overall blueprint for AI security. More specifically, we first take the lifecycle of an AI-based system as a guide to introduce the security threats that emerge at each stage, which is followed by a detailed summary for corresponding countermeasures. Finally, some of the future challenges and opportunities for the security issues in AI will also be discussed.

Security weakness of dynamic watermarking-based detection for generalised replay attacks

Dynamic watermarking (DW)-based detection methods can effectively detect replay attacks, however these detection methods cannot achieve the desired effectiveness for generalised replay attacks (GRAs). The objectiveness of this paper is to investigate security weakness of DW-based detection for GRAs. Firstly, unlike replaying history data from replay attacks, data accuracy compromised by GRAs is analysed, where their characteristics are similar to that compromised by replay attacks, and the current data are distorted by typical GRAs such as injection, replacement and scaling attacks. Secondly, considering the corresponding hidden Markov models of different types of GRAs, the stealthiness is quantified by auto covariance of residuals and cross covariance between residuals and watermarking signals. It is found that if both auto and cross covariance keep unchanged or increase along with watermarking intensity increasing, GRAs cannot be detected effectively. Thirdly, after DW-based detection is invalid for GRAs, it is proved that the stability of closed-loop systems for open-loop unstable dynamics will be destroyed, or the admissible system state bounds can be crossed within a finite time. Finally, experiments are operated on a networked inverted pendulum platform, and experimental results confirm security weakness of DW-based detection for GRAs.

Multiplicative Watermarking Method with the Visual Saliency Model Using Contourlet Transform

We have proposed an image adaptive watermarking method by using contourlet transform. Firstly, we have selected high-energy image blocks as the watermark embedding space through segmenting the original image into nonoverlapping blocks and designed a watermark embedded strength factor by taking advantage of the human visual saliency model. To achieve dynamic adjustability of the multiplicative watermark embedding parameter, the relationship between watermark embedded strength factor and watermarked image quality is developed through experiments with the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM), respectively. Secondly, to detect the watermark information, the generalized Gaussian distribution (GGD) has been utilized to model the contourlet coefficients. Furthermore, positions of the blocks selected, watermark embedding factor, and watermark size have been used as side information for watermark decoding. Finally, several experiments have been conducted on eight images, and the results prove the effectiveness of the proposed watermarking approach. Concretely, our watermarking method has good imperceptibility and strong robustness when against Gaussian noise, JPEG compression, scaling, rotation, median filtering, and Gaussian filtering attack.

Adaptive Video Watermarking against Scaling Attacks Based on Quantization Index Modulation

Video watermarking plays a vital role in protecting the video copyright. The quantization-based methods are widely used in the existing watermarking algorithms, owing to their low computational complexity and completely blind extraction. However, most of them work poorly in resisting scaling attacks, by which the quantization value may fall outside the original quantization interval. For addressing this issue, an adaptive quantization index modulation method is proposed. The property that is associated with the ratio of the DC coefficient before and after scaling the video resolution motivates us to select the DC coefficient as the quantization value and set the size of the quantization interval by the video resolution to maintain the synchronization between them before and after scaling. Moreover, a strategy taking advantage of the high decoding reliability of the QRCode is proposed to terminate the extraction in advance, and both the embedding and the extracting process are performed in the spatial domain, which all contribute to further enhance the execution efficiency. The experimental results show that our algorithm outperforms the state-of-the-art method in terms of imperceptibility, robustness, and computational cost.

The compressive strength of concrete retrofitted with wind ash and steel slag pozzolans with a water-cement based polymers

Freeze and thaw phenomena in cold regions are the main cause of severe damage to concrete structures. Alkaliactivated slag repair mortars, which are introduced as a suitable material for the replacement of Portland cement, can be used as the protective coating for these damaged structures. The mechanical properties and durability of this coating layer should be studied. In this study, the mechanical properties and durability of alkali-activated slag repair mortars with silica fume (SF) participation as inorganic additives against freeze-thaw and salt scaling attacks have been investigated. In order to evaluate the effects of alkaline activators type, the ratio of these solutions to Pozzolan (Pozz), and the use of SF as a substitute base material, these three factors were considered as the main variables to produce 12 alkali-activated slag mortar mixtures. To investigate their mechanical properties, compressive strength, tensile adhesion strength, and drying shrinkage tests were conducted. Also, mortar specimen length change, compressive strength loss, weight loss, and dynamic elastic modulus were measured to evaluate the durability features against freeze-thaw and salt scaling attacks. According to the results, in addition to higher compressive strength and adhesion resistance of alkali-activated slag repair mortars, these mortars showed at least 30% better durability against freeze-thaw and salt scaling attacks than cement-based repair mortar. Also, alkali-activated slag mixtures containing potassium hydroxide, alkaline solution (AS) to Pozz ratio of 0.7, and SF had the best mechanical properties and frost resistance among all mixtures.

Mechanical properties and durability of alkali-activated slag repair mortars containing silica fume against freeze-thaw cycles and salt scaling attack

Freeze and thaw phenomena in cold regions are the main cause of severe damage to concrete structures. Alkaliactivated slag repair mortars, which are introduced as a suitable material for the replacement of Portland cement, can be used as the protective coating for these damaged structures. The mechanical properties and durability of this coating layer should be studied. In this study, the mechanical properties and durability of alkali-activated slag repair mortars with silica fume (SF) participation as inorganic additives against freeze-thaw and salt scaling attacks have been investigated. In order to evaluate the effects of alkaline activators type, the ratio of these solutions to Pozzolan (Pozz), and the use of SF as a substitute base material, these three factors were considered as the main variables to produce 12 alkali-activated slag mortar mixtures. To investigate their mechanical properties, compressive strength, tensile adhesion strength, and drying shrinkage tests were conducted. Also, mortar specimen length change, compressive strength loss, weight loss, and dynamic elastic modulus were measured to evaluate the durability features against freeze-thaw and salt scaling attacks. According to the results, in addition to higher compressive strength and adhesion resistance of alkali-activated slag repair mortars, these mortars showed at least 30% better durability against freeze-thaw and salt scaling attacks than cement-based repair mortar. Also, alkali-activated slag mixtures containing potassium hydroxide, alkaline solution (AS) to Pozz ratio of 0.7, and SF had the best mechanical properties and frost resistance among all mixtures.

Secure Event-Triggered Consensus Control of Linear Multiagent Systems Subject to Sequential Scaling Attacks.

This article investigates secure consensus of linear multiagent systems under event-triggered control subject to a scaling deception attack. Different from probabilistic models, a sequential scaling attack is considered, in which specific attack properties, such as the attack duration and frequency, are defined. Moreover, to alleviate the utilization of communication resources, distributed static and dynamic event-triggered control protocols are proposed and analyzed, respectively. This article aims at providing a resilient event-triggered framework to defend a kind of sequential scaling attack by exploring the relationship among the attack duration and frequency, and event-triggered parameters. First, the static event-triggered control is studied, and sufficient consensus conditions are derived, which impose constraints on the attack duration and frequency. Second, a state-based auxiliary variable is introduced in the dynamic event-triggered scheme. Under the proposed dynamic event-triggered control, consensus criteria involving triggering parameters, attack constraints, and system matrices are obtained. It proves that the Zeno behavior can be excluded. Moreover, the impacts of the scaling factor, triggering parameters, and attack properties are discussed. Finally, the effectiveness of the proposed event-triggered control mechanisms is validated by two examples.

Medical image security authentication method based on wavelet reconstruction and fractal dimension

In this article, based on wavelet reconstruction and fractal dimension, a medical image authentication method is implemented. According to the local and global methods, the regularity of the mutation structure in the carrier information is analyzed through a measurement defined in the medical image transformation domain. To eliminate the redundancy of the reconstructed data, the fractal dimension is used to reduce the attributes of the reconstructed wavelet coefficients. According to the singularity of the fractal dimension of the block information, the key features are extracted and the fractal feature is constructed as the authentication feature of the images. The experimental results show that the authentication scheme has good robustness against attacks, such as JPEG compression, multiplicative noise, salt and pepper noise, Gaussian noise, image rotation, scaling attack, sharpening, clipping attack, median filtering, contrast enhancement, and brightness enhancement.

Image robust adaptive steganography adapted to lossy channels in open social networks

Currently, the demand for covert communication in open social networks brings new opportunities and challenges to existing image steganography technology in terms of robustness and security. To this end, an image robust adaptive steganography is proposed with robustness against multiple image processing attacks and detection resistance. First, a robust embedding domain with theoretical foundation and optimal invisibility is constructed based on the compression resistance principle. Then, utilizing the robust image abstraction and saliency measurement, the embedding channel is selected to avoid modifications in smooth regions and enhance visual quality. On this basis, the proposed method is given combining with error-correcting and STC codes to realize message embedding with minimum costs and improve extraction accuracy. Lastly, after parameters discussion and selection, the performance experiments are conducted compared with previous representative steganography algorithms, concerning robustness and detection resistance, and the fault tolerance is deduced, thereby providing the recommended coding parameters to improve message extraction integrity. The experimental results show that the proposed method can realize message extraction with high accuracy after JPEG compression, Gaussian noising, and scaling attacks, while holding comparable detection resistance to adaptive steganography against statistical features, which indicates its application prospect for covert communication in open lossy channels.

A secure and robust video steganography scheme for covert communication in H.264/AVC

The proposed scheme utilized H.264/AVC video format for steganography which is the most common video standard at present. The scheme employed Discrete Wavelet Transform (DWT) on the Region of Interest (ROI) based on multiple moving objects tracking. After tracking multiple objects, each object is embedded with different secret images to improve the capacity. Multiple object tracking helps in achieving robustness and security; in addition, secret data is encrypted before embedding to provide a high level of security. The proposed scheme is tested on numerous video sequences by evaluating both subjective and objective metrics. Different metrics employed for objective evaluation involves Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Structural Similarity (SSIM) Index, Normalized Cross Correlation (NCC) and Bit Error Rate (BER). However, subjective evaluation is carried out by visual inspection. Additionally, the proposed scheme has been tested against noise, compression, frame rate change and scaling attacks to ensure robustness. Further, the security performance has been analysed by testing against three existing steganalysis techniques and histogram analysis. The main aim of the paper is to focus on robustness and security without compromising hiding capacity and imperceptibility. The reckoning result proves not only high robustness and security but also improves imperceptibility and capacity.

Digital media zero watermark copyright protection algorithm based on embedded intelligent edge computing detection.

With the rapid development of computer technology and network communication technology, copyright protection caused by widely spread digital media has become the focus of attention in various fields. For digital media watermarking technology research emerge in endlessly, but the results are not ideal. In order to better realize the copyright identification and protection, based on the embedded intelligent edge computing detection technology, this paper studies the zero watermark copyright protection algorithm of digital media. Firstly, this paper designs an embedded intelligent edge detection module based on Sobel operator, including image line buffer module, convolution calculation module and threshold processing module. Then, based on the embedded intelligent edge detection module, the Arnold transform of image scrambling technology is used to preprocess the watermark, and finally a zero watermark copyright protection algorithm is constructed. At the same time, the robustness of the proposed algorithm is tested. The image is subjected to different proportion of clipping and scaling attacks, different types of noise, sharpening and blur attacks, and the detection rate and signal-to-noise ratio of each algorithm are calculated respectively. The performance of the watermark image processed by this algorithm is evaluated subjectively and objectively. Experimental data show that the detection rate of our algorithm is the highest, which is 0.89. In scaling attack, the performance of our algorithm is slightly lower than that of Fourier transform domain algorithm, but it is better than the other two algorithms. The Signal to Noise Ratio of the algorithm is 36.854% in P6 multiplicative noise attack, 39.638% in P8 sharpening edge attack and 41.285% in fuzzy attack. This shows that the algorithm is robust to conventional attacks. The subjective evaluation of 33% and 39% of the images is 5 and 4. The mean values of signal to noise ratio, peak signal to noise ratio, mean square error and mean absolute difference are 20.56, 25.13, 37.03 and 27.64, respectively. This shows that the watermark image processed by this algorithm has high quality. Therefore, the digital media zero watermark copyright protection algorithm based on embedded intelligent edge computing detection is more robust, and its watermark invisibility is also very superior, which is worth promoting.

High-SNR steganography for digital audio signal in the wavelet domain

Imperceptible, robust, and embedding capacity are three main requirements for the steganography of digital audio signal. To enhance them, this study presents a novel steganography for digital audio signal in the wavelet domain. Since the performance of imperceptible and robust are usually in term of signal-to-noise ratio (SNR) and bit-error-rate (BER), we propose a quantization-based optimization model to maximize SNR and reduce BER in embedding secret message. In the proposed model, quantization technique with unknow coefficients of discrete wavelet transform (DWT) is rewritten as the first constraint. The adjustment of scaling DWT coefficients is considered as the second constraint. At the same time, signal-to-noise ratio (SNR) is converted into a performance index. In solving this model, we use matrix operations and Lagrange multiplier to obtain optimal DWT coefficients and scaling factors. Moreover, the invariant feature of the scaling factors against amplitude scaling attack is proved. In extraction, secret message can be detected without original audio signal. Experimental results show that the proposed steganography has high SNR and strong robustness against many malicious attacks when comparing to some exiting methods.

A robust video watermarking scheme based on Laplacian pyramid, SVD, and DWT with improved robustness towards geometric attacks via SURF

In this paper, a new robust and secure video watermarking scheme based on discrete Wavelet Transform (DWT), singular value decomposition (SVD), and Laplacian pyramid is proposed for copyright protection applications. The main contributions of this work are: 1) Increasing watermark robustness towards common signal processing attacks by separating the watermark image into a high-frequency image and a low-frequency image using laplacian pyramid. Then, the singular values of each of the low-frequency watermark image and the high-frequency watermark image are hidden in two different DWT subbands of the original video frame. Separating the watermark and hiding its two parts in two different subbands of the DWT of the video frame makes it robust towards noise, filtering, and compression attacks. 2) Improving the quality of the extracted watermarks via correcting the received watermarked videos using SURF points when those videos are geometrically attacked, mainly by rotation, scaling, and shear attacks. 3) Increasing security and avoiding false positive problems (FPP) associated with SVD by using perceptual image hashing in the proposed scheme. Through experimental results and comparisons to other techniques, the proposed scheme has shown very high imperceptibility for the tested watermarked videos in terms of peak signal to noise ratio (PSNR). Also, the proposed scheme has demonstrated high watermark robustness towards various types of attacks, and an improvement in the quality of the extracted watermarks from 4 to 20 dB compared to other techniques.

Imperceptible and Secure Blind Image Watermarking using Spread Spectrum Scheme with Adaptive Embedding Strength

Watermarking is the way toward concealing advanced mystery data in a picture. The best in class watermark implanting plans with the assistance of spread range and quantization, experiences Host Signal Interference (HSI) and scaling assaults, separately. They fixed the inserting parameter, which is hard to consider both power and subtlety for all pictures. This paper takes care of the issues by proposing a visually impaired watermarking strategy, Spread Spectrum Scheme with Adaptive Embedding Strength (SSAES). Their adaptiveness originates from the proposed Adaptive Embedding Strategy (AEP), which expands the installing quality or quantization limit by ensuring the Peak Signal-to-Noise Ratio (PSNR) of the host picture.SSAES includes free of HSI by calculating in the earlier information about HSI. We present a thought called mistake limit to hypothetically dissect the exhibition of our proposed techniques in detail. Further, to improve the security of the watermarked picture, the DCT coefficients are exposed to stage based encryption. This will improve the security of a watermarked picture. The test results reliably exhibit that SSAES outflank the best in class strategies regarding intangibility, power, computational expense, and flexibility. Along these lines the proposed course of action of picture watermarking routs the drawbacks of host signal impedance security ambushes and scaling attack.

Robust and accurate detection of image copy-move forgery using PCET-SVD and histogram of block similarity measures

Many block-based detection methods for image copy-move forgery have been reported. However, their performance degrades significantly under different geometric attacks such as rotation and scaling. In this paper, we propose a novel robust and accurate detection scheme for image copy-move forgery. It mainly consists of three steps: firstly, a suspicious image is divided into overlapping circular blocks, and polar complex exponential transform (PCET) is employed to extract geometric invariant feature of each block. Next, singular value decomposition (SVD) is applied to the coefficient matrix composed of extracted geometric invariant moments for dimension reduction. Meanwhile, the histogram of block similarity measures is adopted to estimate the optimal similarity threshold. Finally, the calculated similarity threshold is used for block matching process and consequently more accurate tampered areas are obtained. Experimental results on various datasets show that the proposed image copy-move detection approach outperforms other existing methods in the aspect of resisting geometric rotation and scaling attacks, with the adaptability of similarity threshold and low computational complexity.

GA-Based Optimized Image Watermarking Method With Histogram and Butterworth Filtering

The present paper proposes a new and significant method of optimization for digital image watermarking by using a combination of Genetic Algorithms (GA), Histogram and Butterworth filtering. In this proposed method, the histogram range selection of low frequency components is taken as a significant parameter which assists in bettering the imperceptibility and robustness against attacks. The tradeoff between the perceptual transparency and robustness is considered as an optimization puzzle which is solved with the help of Genetic Algorithm. As a result, the experimental outcomes of the present approach are obtained. These results are secure and robust to various attacks such as rotation, cropping, scaling, additive noise and filtering attacks. The peak signal to noise ratio (PSNR) and Normalized cross correlation (NC) are carefully analyzed and assessed for a set of images and MATLAB2016B software is employed as a means of accomplishing or achieving these experimental results.