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.

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.

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 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.

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.

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.

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.

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.

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.

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.

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”。

数字图像多功能水印综述

数字图像多功能水印技术通过将多种类型的水印嵌入到同一图像,以实现2种及以上的图像保护功能(版权保护、内容认证、篡改恢复等).当前,数字图像多功能水印算法仍面临着性能和应用场景等方面的挑战.为促进图像多功能水印的进一步发展,首先系统地梳理了数字图像水印技术,包括其系统特性、常见分类、关键技术与成果,以及其可实现的功能与应用场景;在此基础上,对近10年来不同类别的多功能水印嵌入模型(融合水印嵌入、零水印嵌入、水印串行嵌入、水印并行嵌入)的相关工作进行归纳与分析;最后,总结了当前数字图像多功能水印技术的不足,展望了后续研究与发展趋势.综合分析发现,多水印的嵌入难免对水印综合性能造成损失,且多功能水印在真实应用场景中的效果仍待改善.人工智能等新技术在数字图像多功能水印中的应用有望提升算法性能.

基于强化样本的伪孪生网络图像篡改定位模型

随着互联网不断发展,网络上的篡改图像越来越多,掩盖篡改痕迹的手段越来越丰富。而现在大多数检测模型没有考虑到图像后处理操作对篡改检测算法的影响,限制了其在实际生活中的应用。为了解决上述问题,提出了一种通用的基于强化样本的伪孪生网络图像篡改定位模型。所提模型利用伪孪生网络,一方面学习真实图像中的篡改特征;另一方面通过约束卷积,抑制图像内容,从而能够更加关注篡改残留的痕迹信息。网络的两分支结构可以达到充分利用图像特征信息的目的。模型利用强化样本,可以自适应地生成当前最需要学习的篡改类型图片,实现对模型有针对性地训练,使得模型在各个方向上学习收敛,最终得到全局最优模型。利用数据增强思路,自动生成丰富的篡改图像以及其对应的掩膜,这很好地解决了篡改数据集有限的问题。在4个数据集上的大量实验证明了所提模型在像素级操作检测方面的可行性和有效性。尤其是在Columbia数据集上,算法的F1值提高了33.5%,Matthews correlation coefficirnt(MCC)得分提高了23.3%,说明所提模型利用深度学习模型的优点,显著提高了篡改定位的检测效果。

基于多尺度时空特征和篡改概率改善换脸检测的跨库性能

目前大多DeepFake换脸检测算法过于依赖局部特征,尽管库内检测性能尚佳,但容易出现过拟合,导致跨库检测性能不理想,即泛化性能不够好。有鉴于此,文中提出一种基于多尺度时空特征和篡改概率的换脸视频检测算法,目的是利用假脸视频中广泛存在的帧间时域不连续性缺陷来解决现有检测算法在跨库、跨伪造方式和视频压缩时性能明显下降的问题,改善泛化检测能力。该算法包括3个模块:为检测假脸视频在时域上留下的不连续痕迹,设计了一个多尺度时空特征提取模块;为自适应计算多尺度时空特征之间的时空域关联性,设计了一个三维双注意力机制模块;为预测随机选取的像素点的篡改概率和构造监督掩膜,设计了一个辅助监督模块。将所提出的算法在FF++、DFD、DFDC、CDF等公开大型标准数据库中进行实验,并与基线算法和近期发布的同类算法进行对比。结果显示:文中算法在保持库内平均检测性能优良的同时,跨库检测和抗视频压缩时的综合性能最好,跨伪造方法检测时的综合性能中等偏上。实验结果验证了文中算法的有效性。