STATISTICAL INFERENCE OF WEIBULL DISTRIBUTION FOR TAMPERED FAILURE RATE MODEL IN PROGRESSIVE STRESS ACCELERATED LIFE TESTING

In this note,the tampered failure rate model is generalized from the step-stress accelerated life testing setting to the progressive stress accelerated life testing for the first time.For the parametric setting where the scale parameter satisfying the equation of the inverse power law is Weibull,maximum likelihood estimation is investigated.

Research on Improved MobileViT Image Tamper Localization Model

As image manipulation technology advances rapidly,the malicious use of image tampering has alarmingly escalated,posing a significant threat to social stability.In the realm of image tampering localization,accurately localizing limited samples,multiple types,and various sizes of regions remains a multitude of challenges.These issues impede the model’s universality and generalization capability and detrimentally affect its performance.To tackle these issues,we propose FL-MobileViT-an improved MobileViT model devised for image tampering localization.Our proposed model utilizes a dual-stream architecture that independently processes the RGB and noise domain,and captures richer traces of tampering through dual-stream integration.Meanwhile,the model incorporating the Focused Linear Attention mechanism within the lightweight network(MobileViT).This substitution significantly diminishes computational complexity and resolves homogeneity problems associated with traditional Transformer attention mechanisms,enhancing feature extraction diversity and improving the model’s localization performance.To comprehensively fuse the generated results from both feature extractors,we introduce the ASPP architecture for multi-scale feature fusion.This facilitates a more precise localization of tampered regions of various sizes.Furthermore,to bolster the model’s generalization ability,we adopt a contrastive learning method and devise a joint optimization training strategy that leverages fused features and captures the disparities in feature distribution in tampered images.This strategy enables the learning of contrastive loss at various stages of the feature extractor and employs it as an additional constraint condition in conjunction with cross-entropy loss.As a result,overfitting issues are effectively alleviated,and the differentiation between tampered and untampered regions is enhanced.Experimental evaluations on five benchmark datasets(IMD-20,CASIA,NIST-16,Columbia and Coverage)validate the effectiveness of our proposed model.The meticulously calibrated FL-MobileViT model consistently outperforms numerous existing general models regarding localization accuracy across diverse datasets,demonstrating superior adaptability.

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.

An Active Image Forgery Detection Approach Based on Edge Detection

Recently, digital images have become the most used data, thanks tohigh internet speed and high resolution, cheap and easily accessible digitalcameras. We generate, transmit and store millions of images every second.Most of these images are insignificant images containing only personal information.However, in many fields such as banking, finance, public institutions,and educational institutions, the images of many valuable objects like IDcards, photographs, credit cards, and transaction receipts are stored andtransmitted to the digital environment. These images are very significantand must be secured. A valuable image can be maliciously modified by anattacker. The modification of an image is sometimes imperceptible even by theperson who stored the image. In this paper, an active image forgery detectionmethod that encodes and decodes image edge information is proposed. Theproposed method is implemented by designing an interface and applied on atest image which is frequently used in the literature. Various tampering attacksare simulated to test the fidelity of the method. The method not only notifieswhether the image is forged or not but also marks the tampered region ofthe image. Also, the proposed method successfully detected tampered regionsafter geometric attacks, even on self-copy attacks. Also, it didn’t fail on JPEGcompression.

Passive detection of copy-paste forgery between JPEG images

A blind digital image forensic method for detecting copy-paste forgery between JPEG images was proposed.Two copy-paste tampering scenarios were introduced at first:the tampered image was saved in an uncompressed format or in a JPEG compressed format.Then the proposed detection method was analyzed and simulated for all the cases of the two tampering scenarios.The tampered region is detected by computing the averaged sum of absolute difference(ASAD) images between the examined image and a resaved JPEG compressed image at different quality factors.The experimental results show the advantages of the proposed method:capability of detecting small and/or multiple tampered regions,simple computation,and hence fast speed in processing.

Voting System Based on Blockchain

Online ballot box system has the advantages of high efficiency and environmental protection,but the existing network voting technology still has a lot of matter.Almost all electronic voting system could be proved to be intrusion.The administrator of the system could tamper with the data for benefit,and the system may be attacked by hackers.The safety and fairness of the existing network voting system depend entirely on the safety and credibility of the website itself,but these cannot guarantee the fairness of voting.Make full use of blockchain technology,so that voting,even if there are malicious participants,but also to ensure the correctness and safety of the vote.The introduction of block chain technology,block chain has decentralized,data tampering and other characteristics.P2P network is applied in the block chain layer to construct a distributed database,digital signature algorithm and encryption technology are used to ensure that the data cannot be tampered with,consensus network algorithm is used to ensure the consistency of the data in the network,and timestamp technology is applied to save the data blocks in a chain structure connected end to end.It paper focuses on the implementation of P2P network networking mode,node block synchronization,data and block verification mechanism and consensus mechanism to ensure data consistency in the network layer of block chain layer.Using time stamp,Merkle tree,asymmetric encryption and other technologies to design data blocks and use chain structure to store data blocks.Combined with the characteristics of blockchain,a fair and transparent voting system is constructed.Model aims to apply the block chain technology to the voting scenario and design a secure block chain voting architecture.It system is designed and developed based on the block chain system.It makes full use of its decentralization,removes the dependence of electronic voting on trusted third parties,and protects the privacy of voters and candidates.Data cannot be tampered with.Once the data are stored in the block chain,it cannot be tampered with.It provides a real and credible database.

A Hybrid Intelligent Approach for Content Authentication and Tampering Detection of Arabic Text Transmitted via Internet

In this paper,a hybrid intelligent text zero-watermarking approach has been proposed by integrating text zero-watermarking and hidden Markov model as natural language processing techniques for the content authentication and tampering detection of Arabic text contents.The proposed approach known as Second order of Alphanumeric Mechanism of Markov model and Zero-Watermarking Approach(SAMMZWA).Second level order of alphanumeric mechanism based on hidden Markov model is integrated with text zero-watermarking techniques to improve the overall performance and tampering detection accuracy of the proposed approach.The SAMMZWA approach embeds and detects the watermark logically without altering the original text document.The extracted features are used as a watermark information and integrated with digital zero-watermarking techniques.To detect eventual tampering,SAMMZWA has been implemented and validated with attacked Arabic 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 for all kinds of tampering attacks with high level accuracy of tampering detection than compared methods.

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.

Entropy-Based Watermarking Approach for Sensitive Tamper Detection of Arabic Text

The digital text media is the most common media transferred via the internet for various purposes and is very sensitive to transfer online with the possibility to be tampered illegally by the tampering attacks.Therefore,improving the security and authenticity of the text when it is transferred via the internet has become one of the most difcult challenges that researchers face today.Arabic text is more sensitive than other languages due to Harakat’s existence in Arabic diacritics such as Kasra,and Damma in which making basic changes such as modifying diacritic arrangements can lead to change the text meaning.In this paper,an intelligent hybrid solution is proposed with highly sensitive detection for any tampering on Arabic text exchanged via the internet.Natural language processing,entropy,and watermarking techniques have been integrated into this method to improve the security and reliability of Arabic text without limitations in text nature or size,and type or volumes of tampering attack.The proposed scheme is implemented,simulated,and validated using four standard Arabic datasets of varying lengths under multiple random locations of insertion,reorder,and deletion attacks.The experimental and simulation results prove the accuracy of tampering detection of the proposed scheme against all kinds of tampering attacks.Comparison results show that the proposed approach outperforms all of the other baseline approaches in terms of tampering detection accuracy.

Image Tampering Detection Using No-Reference Image Quality Metrics

In this paper,a new approach is proposed to determine whether the content of an image is authentic or modified with a focus on detecting complex image tampering.Detecting image tampering without any prior information of the original image is a challenging problem since unknown diverse manipulations may have different characteristics and so do various formats of images.Our principle is that image processing,no matter how complex,may affect image quality,so image quality metrics can be used to distinguish tampered images.In particular,based on the alteration of image quality in modified blocks,the proposed method can locate the tampered areas.Referring to four types of effective no-reference image quality metrics,we obtain 13 features to present an image.The experimental results show that the proposed method is very promising on detecting image tampering and locating the locally tampered areas especially in realistic scenarios.

Semi-Fragile Audio Watermarking Algorithm in DWT Domain

A novel semi-fragile audio watermarking algorithm in DWT domain is proposed in this paper.This method transforms the original audio into 3-layer wavelet domain and divides approximation wavelet coefficients into many groups.Through computing mean quantization of per group,this algorithm embeds the watermark signal into the average value of the wavelet coefficients.Experimental results show that our semi-fragile audio watermarking algorithm is not only inaudible and robust against various common images processing,but also fragile to malicious modification.Especially,it can detect the tampered regions effectively.

A Reliable NLP Scheme for English Text Watermarking Based on Contents Interrelationship

In this paper,a combined approach CAZWNLP(a combined approach of zero-watermarking and natural language processing)has been developed for the tampering detection of English text exchanged through the Internet.The third gram of alphanumeric of the Markov model has been used with text-watermarking technologies to improve the performance and accuracy of tampering detection issues which are limited by the existing works reviewed in the literature of this study.The third-grade level of the Markov model has been used in this method as natural language processing technology to analyze an English text and extract the textual characteristics of the given contexts.Moreover,the extracted features have been utilized as watermark information and then validated with the attacked English text to detect any suspected tampering occurred on it.The embedding mechanism of CAZWNLP method will be achieved logically without effects or modifying the original text document to embed a watermark key.CAZWNLP has been implemented using VS code IDE with PHP.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.

Image Tamper Detection and Multi-Scale Self-Recovery Using Reference Embedding with Multi-Rate Data Protection

This paper proposes a multi-scale self-recovery(MSSR)approach to protect images against content forgery.The main idea is to provide more resistance against image tampering while enabling the recovery process in a multi-scale quality manner.In the proposed approach,the reference data composed of several parts and each part is protected by a channel coding rate according to its importance.The first part,which is used to reconstruct a rough approximation of the original image,is highly protected in order to resist against higher tampering rates.Other parts are protected with lower rates according to their importance leading to lower tolerable tampering rate(TTR),but the higher quality of the recovered images.The proposed MSSR approach is an efficient solution for the main disadvantage of the current methods,which either recover a tampered image in low tampering rates or fails when tampering rate is above the TTR value.The simulation results on 10000 test images represent the efficiency of the multi-scale self-recovery feature of the proposed approach in comparison with the existing methods.

A Scheme of Fragile Watermarking Based on SVD and 2D Chaotic Mapping

This paper proposed a novel fragile watermarking scheme based on singular value decomposition (SVD) and 2D chaotic mapping. It obtains chaotic initial values from the image blocks singular value decomposition and the user’s key, then uses the chaotic mapping to get the chaotic sequence and inserts the sequence into the LSBs of the image blocks to get the watermarked image blocks. The paper reconstructed the watermarked image from all the embedded blocks. The analysis and experimental results show that the scheme is pretty fragile to tampering, and it can localize the tampering position accurately, reach 3×3 blocks.

SEMI-FRAGILE WATERMARKING ALGORITHM FOR IMAGE TAMPERS LOCALIZATION AND RECOVERY

Two watermarks are embedded into the original image. One is the authentication watermark generated by secret key, which is embedded into the sub-LSB （Least Significant Bit） of the original image for tamper localization; the other is the recovery watermark for tamper recovering. The original image is divided into 8 x 8 blocks and each block is transformed by Discrete Cosine Transform （DCT）. For each block, some lower frequency DCT coefficients are chosen to be quantized and binary encoded so as to gain the recovery watermark of each block, and the recovery watermark is embedded into the LSB of another block by chaos encryption and authentication chain technology. After the two watermarks being detected, the location of any minute changes in image can be detected, and the tampered image data can be recovered effectively. In the paper, the number of coefficients and their bit lengths are carefully chosen in order to satisfy with the payload of each block and gain the capability of self-recovering. The proposed algorithm can well resist against possible forged attacks. Experimental results show that the watermark generated by the proposed algorithm is sensitive to tiny changes in images, and it has higher accuracy of tamper localization and good capability of the tamper recovery.

A New Fragile Watermarking Scheme for Text Documents Authentication

Because there are different modification types of deleting characters and inserting characters in text documents, the algorithms for image authentication can not be used for text documents authentication directly. A text watermarking scheme for text document authentication is proposed in this paper. By extracting the features of character cascade together with the user secret key, the scheme combines the features of the text with the user information as a watermark which is embedded into the transformed text itself. The receivers can verify the integrity and the authentication of the text through the blind detection technique. A further research demonstrates that it can also localize the tamper, classify the type of modification, and recover part of modified text documents. The aforementioned conclusion has been proved by both our experiment results and analysis.

Tamper Detection and Localization for Quranic Text Watermarking Scheme Based on Hybrid Technique

The text of the Quran is principally dependent on the Arabic language.Therefore,improving the security and reliability of the Quran’s text when it is exchanged via internet networks has become one of the most difcult challenges that researchers face today.Consequently,the diacritical marks in the Holy Quran which represent Arabic vowels(i,j.s)known as the kashida(or“extended letters”)must be protected from changes.The cover text of the Quran and its watermarked text are different due to the low values of the Peak Signal to Noise Ratio(PSNR),and Normalized Cross-Correlation(NCC);thus,the location for tamper detection accuracy is low.The gap addressed in this paper to improve the security of Arabic text in the Holy Quran by using vowels with kashida.To enhance the watermarking scheme of the text of the Quran based on hybrid techniques(XOR and queuing techniques)of the purposed scheme.The methodology propose scheme consists of four phases:The rst phase is pre-processing.This is followed by the second phase where an embedding process takes place to hide the data after the vowel letters wherein if the secret bit is“1”,it inserts the kashida but does not insert the kashida if the bit is“0”.The third phase is an extraction process and the last phase is to evaluate the performance of the proposed scheme by using PSNR(for the imperceptibility),and NCC(for the security of the watermarking).Experiments were performed on three datasets of varying lengths under multiple random locations of insertion,reorder and deletion attacks.The experimental results were revealed the improvement of the NCC by 1.76%,PSNR by 9.6%compared to available current schemes.

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.

A Survey of Blind Forensics Techniques for JPEG Image Tampering

Blind forensics of JPEG image tampering as a kind of digital image blind forensics technology is gradually becoming a new research hotspot in the field of image security. Firstly, the main achievements of domestic and foreign scholars in the blind forensic technology of JPEG image tampering were briefly described. Then, according to the different methods of tampering and detection, the current detection was divided into two types: double JPEG compression detection and block effect inconsistency detection. This paper summarized the existing methods of JPEG image blind forensics detection, and analyzed the two methods. Finally, the existing problems and future research trends were analyzed and prospected to provide further theoretical support for the research of JPEG image blind forensics technology.

Comparative Evaluation of Semi Fragile Watermarking Algorithms for Image Authentication

Technology has no limits today;we have lots of software available in the market by which we can alter any image. People usually copies image from the internet and after some changes they claim that these are their own properties. Insuring digital image integrity has therefore become a major issue. Over the past few years, watermarking has emerged as the leading candidate to solve problems of ownership and content authentications for digital multimedia documents. To protect authenticity of images semi fragile watermarking is very concerned by researchers because of its important function in multimedia content authentication. The aim of this paper is to present a survey and a comparison of emerging techniques for image authentication using semifragile watermarking. In present paper comprehensive overview of insertion and extraction methods used in different semi fragile water marking algorithm are studied using image parameters, potential application, different algorithms are described and focus is on their comparison according to the properties cited above and future directions for developing a better image authentication algorithm are suggested.