An H.264/AVC Video Watermarking Scheme in VLC Domain for Content Authentication

A semi-fragile content authentication algorithm is proposed for low bit-rate H.264/AVC video in VLC domain. Utilizing the intra prediction mode and coded block pattern in VLC domain, the proposed algorithm chooses those macro-blocks from which the signature is extracted and constructs content signature at macro-block level according to the relationship among the energies of quantized low-frequency coefficients of sub-macroblocks. The signature is embedded by modifying the trailing coefficients. The experimental results show that the proposed algorithm performs well in visual quality impact and keep the bit-rate basically unchanged. In addition, the algorithm can embed signatures into I, P, B slices simultaneously and remarkably enhances the watermark capacity. By verifying the extracted signature, the algorithm can detect and locate video tampering efficiently.

Content Authentication Based on JPEG-to-JPEG Watermarking

A content authentication technique based on JPEG-to-JPEG watermarking is proposed in this paper. In this technique, each 8x8 block in a JPEG compressed image is first processed by entropy decoding, and then the quantized discrete cosine transform （DCT） is applied to generate DCT coefficients： one DC coefficient and 63 AC coefficients in frequency coefficients. The DCT AC coefficients are used to form zero planes in which the watermark is embedded by a chaotic map. In this way, the watermark information is embedded into JPEG compressed domain, and the output watermarked image is still a JPEG format. The proposed method is especially applicable to content authentication of JPEG image since the quantized coefficients are modified for embedding the watermark and the chaotic system possesses an important property with the high sensitivity on initial values. Experimental results show that the tamper regions are localized accurately when the watermarked JPEG image is maliciously tampered.

Digital Text Document Watermarking Based Tampering Attack Detection via Internet

Owing to the rapid increase in the interchange of text information through internet networks,the reliability and security of digital content are becoming a major research problem.Tampering detection,Content authentication,and integrity verification of digital content interchanged through the Internet were utilized to solve a major concern in information and communication technologies.The authors’difficulties were tampering detection,authentication,and integrity verification of the digital contents.This study develops an Automated Data Mining based Digital Text Document Watermarking for Tampering Attack Detection(ADMDTW-TAD)via the Internet.The DM concept is exploited in the presented ADMDTW-TAD technique to identify the document’s appropriate characteristics to embed larger watermark information.The presented secure watermarking scheme intends to transmit digital text documents over the Internet securely.Once the watermark is embedded with no damage to the original document,it is then shared with the destination.The watermark extraction process is performed to get the original document securely.The experimental validation of the ADMDTW-TAD technique is carried out under varying levels of attack volumes,and the outcomes were inspected in terms of different measures.The simulation values indicated that the ADMDTW-TAD technique improved performance over other models.

FMHADP:Design of an Efficient Pre-Forensic Layer for Mitigating Hybrid Attacks via Deep Learning Pattern Analysis

Network attack detection and mitigation require packet collection,pre-processing,feature analysis,classification,and post-processing.Models for these tasks sometimes become complex or inefficient when applied to real-time data samples.To mitigate hybrid assaults,this study designs an efficient forensic layer employing deep learning pattern analysis and multidomain feature extraction.In this paper,we provide a novel multidomain feature extraction method using Fourier,Z,Laplace,Discrete Cosine Transform(DCT),1D Haar Wavelet,Gabor,and Convolutional Operations.Evolutionary method dragon fly optimisation reduces feature dimensionality and improves feature selection accuracy.The selected features are fed into VGGNet and GoogLeNet models using binary cascaded neural networks to analyse network traffic patterns,detect anomalies,and warn network administrators.The suggested model tackles the inadequacies of existing approaches to hybrid threats,which are growing more common and challenge conventional security measures.Our model integrates multidomain feature extraction,deep learning pattern analysis,and the forensic layer to improve intrusion detection and prevention systems.In diverse attack scenarios,our technique has 3.5% higher accuracy,4.3% higher precision,8.5% higher recall,and 2.9% lower delay than previous models.

Smart-Fragile Authentication Scheme for Robust Detecting of Tampering Attacks on English Text

Content authentication,integrity verification,and tampering detection of digital content exchanged via the internet have been used to address a major concern in information and communication technology.In this paper,a text zero-watermarking approach known as Smart-Fragile Approach based on Soft Computing and Digital Watermarking(SFASCDW)is proposed for content authentication and tampering detection of English text.A first-level order of alphanumeric mechanism,based on hidden Markov model,is integrated with digital zero-watermarking techniques to improve the watermark robustness of the proposed approach.The researcher uses the first-level order and alphanumeric mechanism of Markov model as a soft computing technique to analyze English text.Moreover,he extracts the features of the interrelationship among the contexts of the text,utilizes the extracted features as watermark information,and validates it later with the studied English text to detect any tampering.SFASCDW has been implemented using PHP with VS code IDE.The robustness,effectiveness,and applicability of SFASCDW are proved with experiments involving four datasets of various lengths in random locations using the three common attacks,namely insertion,reorder,and deletion.The SFASCDW was found to be effective and could be applicable in detecting any possible tampering.

Novel Scheme for Compressed Image Authentication Using LSB Watermarking and EMRC6 Encryption

In the current era, transmission and storing of medical data in the digital form is of great concern and thus the requirement for content authentication has aroused. As a solution to these, digital watermarking techniques and encryption schemes have been used to secure medical data like medical images. In this paper a combination of two algorithms to provide image authentication for medical images in the compressed format is proposed. In the proposed method, the watermark image is encrypted using the Enhanced modified RC6 block cipher (EMRC6) algorithm and the encrypted watermark image is watermarked using the simple Least significant Bit (LSB) watermarking technique. The watermarked output image shows no visual imparity and the watermark which has been extracted has no visual difference. The test results show that the watermarked image has high quality and the watermark is very secure. Also the PSNR value of proposed method is 44.966 on an average and 43.0633 for the existing system where LSB technique is integrated with MRC6 for security of watermark. Hence the work is aimed to increase the embedding volume and make the watermark more secure which is the basic requirement of medical image security.

A Smart English Text Zero-Watermarking Approach Based on Third-Level Order and Word Mechanism of Markov Model

Text information is principally dependent on the natural languages.Therefore,improving security and reliability of text information exchanged via internet network has become the most difficult challenge that researchers encounter.Content authentication and tampering detection of digital contents have become a major concern in the area of communication and information exchange via the Internet.In this paper,an intelligent text Zero-Watermarking approach SETZWMWMM(Smart English Text Zero-Watermarking Approach Based on Mid-Level Order and Word Mechanism of Markov Model)has been proposed for the content authentication and tampering detection of English text contents.The SETZWMWMM approach embeds and detects the watermark logically without altering the original English text document.Based on Hidden Markov Model(HMM),Third level order of word mechanism is used to analyze the interrelationship between contexts of given English texts.The extracted features are used as a watermark information and integrated with digital zero-watermarking techniques.To detect eventual tampering,SETZWMWMM has been implemented and validated with attacked English text.Experiments were performed on four datasets of varying lengths under multiple random locations of insertion,reorder and deletion attacks.The experimental results show that our method is more sensitive and efficient for all kinds of tampering attacks with high level accuracy of tampering detection than compared methods.

Multipurpose audio watermarking algorithm

To make audio watermarking accomplish both copyright protection and content authentication with localization, a novel multipurpose audio watermarking scheme is proposed in this paper. The zero-watermarking idea is introduced into the design of robust watermarking algorithm to ensure the transparency and to avoid the interference between the robust watermark and the semi-fragile watermark. The property of natural audio that the VQ indices of DWT-DCT coefficients among neighboring frames tend to be very similar is utilized to extract essential feature from the host audio, which is then used for watermark ex-traction. And, the chaotic mapping based semi-fragile watermark is embedded in the detail wavelet coefficients based on the instantaneous mixing model of the independent component analysis (ICA) system. Both the robust and semi-fragile watermarks can be extracted blindly and the semi-fragile watermarking algorithm can localize the tampering accurately. Simulation results demonstrate the effectiveness of our algorithm in terms of transparency, security, robustness and tampering localization ability.

Text Analysis-Based Watermarking Approach for Tampering Detection of English Text

Due to the rapid increase in the exchange of text information via internet networks,the security and the reliability of digital content have become a major research issue.The main challenges faced by researchers are authentication,integrity verication,and tampering detection of the digital contents.In this paper,text zero-watermarking and text feature-based approach is proposed to improve the tampering detection accuracy of English text contents.The proposed approach embeds and detects the watermark logically without altering the original English text document.Based on hidden Markov model(HMM),the fourth level order of the word mechanism is used to analyze the contents of the given English text to nd the interrelationship between the contexts.The extracted features are used as watermark information and integrated with digital zero-watermarking techniques.To detect eventual tampering,the proposed approach has been implemented and validated with attacked English text.Experiments were performed using four standard datasets of varying lengths under multiple random locations of insertion,reorder,and deletion attacks.The experimental and simulation results prove the tampering detection accuracy of our method against all kinds of tampering attacks.Comparison results show that our proposed approach outperforms all the other baseline approaches in terms of tampering detection accuracy.

Arabic Feature-Based Text Watermarking Technique for Sensitive Detecting Tampering Attack

In this article,a high-sensitive approach for detecting tampering attacks on transmitted Arabic-text over the Internet(HFDATAI)is proposed by integrating digital watermarking and hidden Markov model as a strategy for soft computing.The HFDATAI solution technically integrates and senses the watermark without modifying the original text.The alphanumeric mechanism order in the first stage focused on the Markov model key secret is incorporated into an automated,null-watermarking approach to enhance the proposed approach’s efficiency,accuracy,and intensity.The first-level order and alphanumeric Markov model technique have been used as a strategy for soft computing to analyze the text of the Arabic language.In addition,the features of the interrelationship among text contexts and characteristics of watermark information extraction that is used later validated for detecting any tampering of the Arabic-text attacked.The HFDATAI strategy was introduced based on PHP with included IDE of VS code.Experiments of four separate duration datasets in random sites illustrate the fragility,efficacy,and applicability of HFDATAI by using the three common tampering attacks i.e.,insertion,reorder,and deletion.The HFDATAI was found to be effective,applicable,and very sensitive for detecting any possible tampering on Arabic text.

An Optimized English Text Watermarking Method Based on Natural Language Processing Techniques

In this paper,the text analysis-based approach RTADZWA(Reliable Text Analysis and Digital Zero-Watermarking Approach)has been proposed for transferring and receiving authentic English text via the internet.Second level order of alphanumeric mechanism of hidden Markov model has been used in RTADZWA approach as a natural language processing to analyze the English text and extracts the features of the interrelationship between contexts of the text and utilizes the extracted features as watermark information and then validates it later with attacked English text to detect any tampering occurred on it.Text analysis and text zero-watermarking techniques have been integrated by RTADZWA approach to improving the performance,accuracy,capacity,and robustness issues of the previous literature proposed by the researchers.The RTADZWA approach embeds and detects the watermark logically without altering the original text document to embed a watermark.RTADZWA has been implemented using PHP with VS code IDE.The experimental and simulation results using standard datasets of varying lengths show that the proposed approach can obtain high robustness and better detection accuracy of tampering common random insertion,reorder,and deletion attacks,e.g.,Comparison results with baseline approaches also show the advantages of the proposed approach.

A multipurpose audio watermarking algorithm with synchronization and encryption

We propose a new multipurpose audio watermarking scheme in which two complementary watermarks are used. For audio copyright protection, the watermark data with copyright information or signature are first encrypted by Arnold transforma- tion. Then the watermark data are inserted in the low frequency largest significant discrete cosine transform （DCT） coefficients to obtain robustness performance. For audio authentication, a chaotic signal is inserted in the high frequency insignificant DCT coefficients to detect tampered regions. Furthermore, the synchronization code is embedded in the audio statistical characteristics to resist desynchronization attacks. Experimental results show that our proposed method can not only obtain satisfactory detection and tampered location, but also achieve imperceptibility and robustness to common signal processing attacks, such as cropping, shifting, and time scale modification （TSM）. Comparison results show that our method outperforms some existing methods.