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.

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.

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.

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.

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.

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.

Securing Arabic Contents Algorithm for Smart Detecting of Illegal Tampering Attacks

Themost common digital media exchanged via the Internet is in text form.The Arabic language is considered one of themost sensitive languages of content modification due to the presence of diacritics that can cause a change in the meaning.In this paper,an intelligent scheme is proposed for improving the reliability and security of the text exchanged via the Internet.The core mechanism of the proposed scheme depends on integrating the hidden Markov model and zero text watermarking techniques.The watermark key will be generated by utilizing the extracted features of the text analysis process using the third order and word level of the Markov model.The Embedding and detection processes of the proposed scheme will be performed logically without the effect of the original text.The proposed scheme is implemented using PHP with VS code IDE.The simulation results,using varying sizes of standard datasets,show that the proposed scheme can obtain high reliability and provide better accuracy of the common illegal tampering attacks.Comparison results with other baseline techniques show the added value of the proposed scheme.

Forward-Secure Digital Signature Scheme with Tamper Evidence

Based on the definition of tamper evidence, the authors define a new notion of tamper evidence forward secure signature scheme （TE-FSig）, and propose a general method to build a TE-FSig scheme. Based on this method, they also give out a concrete instance. A TE-FSig scheme is constructed by the standard signature scheme, forward secures signature scheme and the aggregate signature scheme. It has an additional property of tamper evidence besides the property of forward secure, which can detect the time period when the key is exposed. In the standard model, the scheme constructed in the paper is proved to satisfy the prop- erties of forward secure, strong forward tamper-evidence secure, and strongly unforgeable under the chosen-message attack.

An Optimal Text Watermarking Method for Sensitive Detecting of Illegal Tampering Attacks

Due to the rapid increase in the exchange of text information via internet networks,the security and authenticity of digital content have become a major research issue.The main challenges faced by researchers are how to hide the information within the text to use it later for authentication and attacks tampering detection without effects on the meaning and size of the given digital text.In this paper,an efficient text-based watermarking method has been proposed for detecting the illegal tampering attacks on theArabic text transmitted online via an Internet network.Towards this purpose,the accuracy of tampering detection and watermark robustness has been improved of the proposed method as compared with the existing approaches.In the proposed method,both embedding and extracting of the watermark are logically implemented,which causes no change in the digital text.This is achieved by using the third level and alphanumeric strategy of the Markov model as a text analysis technique for analyzing the Arabic contents to obtain its features which are considered as the digital watermark.This digital watermark will be used later to detecting any tampering of illegal attack on the received Arabic text.An extensive set of experiments using four data sets of varying lengths proves the effectiveness of our approach in terms of detection accuracy,robustness,and effectiveness under multiple random locations of the common tampering attacks.

Digital Evidence for Database Tamper Detection

Most secure database is the one you know the most. Tamper detection compares the past and present status of the system and produces digital evidence for forensic analysis. Our focus is on different methods or identification of different locations in an oracle database for collecting the digital evidence for database tamper detection. Starting with the basics of oracle architecture, continuing with the basic steps of forensic analysis the paper elaborates the extraction of suspicious locations in oracle. As a forensic examiner, collecting digital evidence in a database is a key factor. Planned and a modelled way of examination will lead to a valid detection. Based on the literature survey conducted on different aspects of collecting digital evidence for database tamper detection, the paper proposes a block diagram which may guide a database forensic examiner to obtain the evidences.

On the Use of Benford’s Law to Detect JPEG Biometric Data Tampering

Tampering of biometric data has attracted a great deal of attention recently. Furthermore, there could be an intentional or accidental use of a particular biometric sample instead of another for a particular application. Therefore, there exists a need to propose a method to detect data tampering, as well as differentiate biometric samples in cases of intentional or accidental use for a different application. In this paper, fingerprint image tampering is studied. Furthermore, optically acquired fingerprints, synthetically generated fingerprints and contact-less acquired fingerprints are studied for separation purposes using the Benford’s law divergence metric. Benford’s law has shown in literature to be very effective in detecting tampering of natural images. In this paper, the Benford’s law features with support vector machine are proposed for the detection of malicious tampering of JPEG fingerprint images. This method is aimed at protecting against insider attackers and hackers. This proposed method detected tampering effectively, with Equal Error Rate (EER) of 2.08%. Again, the experimental results illustrate that, optically acquired fingerprints, synthetically generated fingerprints and contact-less acquired fingerprints can be separated by the proposed method effectively.

An Overview of Image Tamper Detection

With the popularization of high-performance electronic imaging equipment and the wide application of digital image editing software,the threshold of digital image editing becomes lower and lower.Thismakes it easy to trick the human visual system with professionally altered images.These tampered images have brought serious threats to many fields,including personal privacy,news communication,judicial evidence collection,information security and so on.Therefore,the security and reliability of digital information has been increasingly concerned by the international community.In this paper,digital image tamper detection methods are classified according to the clues that they rely on,detection methods based on image content and detection methods based on double JPEG compression traces.This paper analyzes and discusses the important algorithms in several classification methods,and summarizes the problems existing in various methods.Finally,this paper predicts the future development trend of tamper detection.

Tamper技术推出无底纸标签减少包装浪费

Tamper技术推出的TamperTech无底纸标签技术，可以将每卷标签的包装浪费减少50％。这种防伪、防篡改包装标签，制造过程中省去了需要除去的底纸，它可以贴在很多材料上，包括瓦楞纸板、塑料容器和软包装。如果试图偷窃或者是撕除，就会在包装上留下清晰的警示信息“无效打开”。

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.

一种基于保守超混沌系统的脆弱水印算法

提出了一种新颖的基于混沌系统的数字图像脆弱水印算法。所提出的方案引入了一个高维保守超混沌系统与数字图像关联生成混沌序列,通过转置卷积重构后得到水印信息,将其嵌入到图像像素的最低有效位(Least Significant Bit,LSB)。相比耗散混沌,保守超混沌系统因其不具有混沌吸引子的性质和超混沌特性,可以在符合人眼视觉的掩蔽性的同时,增强安全性能。实验结果表明,该方法安全可靠,能够在各种攻击下获得较高的篡改检测和定位精度。

基于关联规则与离群点的新能源汽车动力域入侵检测

为提高新能源汽车动力域中针对篡改攻击的入侵检测系统效果,建立包括关联规则检测和离群点检测的动力域防护模型,通过实车采集固定工况下的动力域报文数据,基于关联规则算法建立规则库检测篡改攻击;在关联规则检测的基础上通过离群点检测,检测复杂类型的篡改攻击。仿真结果表明,该方法相比于传统的关联规则方法检测准确率提高5.83%,能有效检测针对新能源汽车动力域的篡改攻击。