New Fragile Watermarking Technique to Identify Inserted Video Objects Using H.264 and Color Features

The transmission of video content over a network raises various issues relating to copyright authenticity,ethics,legality,and privacy.The protection of copyrighted video content is a significant issue in the video industry,and it is essential to find effective solutions to prevent tampering and modification of digital video content during its transmission through digital media.However,there are stillmany unresolved challenges.This paper aims to address those challenges by proposing a new technique for detectingmoving objects in digital videos,which can help prove the credibility of video content by detecting any fake objects inserted by hackers.The proposed technique involves using two methods,the H.264 and the extraction color features methods,to embed and extract watermarks in video frames.The study tested the performance of the system against various attacks and found it to be robust.The evaluation was done using different metrics such as Peak-Signal-to-Noise Ratio(PSNR),Mean Squared Error(MSE),Structural Similarity Index Measure(SSIM),Bit Correction Ratio(BCR),and Normalized Correlation.The accuracy of identifying moving objects was high,ranging from 96.3%to 98.7%.The system was also able to embed a fragile watermark with a success rate of over 93.65%and had an average capacity of hiding of 78.67.The reconstructed video frames had high quality with a PSNR of at least 65.45 dB and SSIMof over 0.97,making them imperceptible to the human eye.The system also had an acceptable average time difference(T=1.227/s)compared with other state-of-the-art methods.

Novel Chaotic Fragile Watermarking Algorithm for Image Authentication

Taking full advantage of the randomicity of chaotic system and its extreme sensitivity to the initial value, a new chaotic fragile watermarking algorithm is proposed. In the algorithm, the location key is looked as a logistic chaotic initial value for iteration to create a location matrix. According to this location matrix, a mapping image is generated and the embedding location of watermarking in image blocks is identified. Then, the watermarking sequence, which is related with the mapping image blocks and generated by H6non chaotic map, is embedded into the least significant bit （ LSB ） of the corresponding location in each block. Since the image content and watermarking are staggered, the algorithm has a higher security. Simulation results showed that the algorithm can detect and locate the tamper in watermarked images with an accuracy of 2 × 2 block pixels. At the same time, the watermarking images has good invisibility, and the original image is not required when extracting watermarking.

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.

New Semi-Fragile Authentication Watermarking

In this paper we propose a semi fragile watermarking scheme, which can be used for image authentication. Let the original image be performed by l level discrete wavelet transformation. An approximate wavelet coefficient matrix of the original image and real value chaotic sequences are than used to generate the content based and secure watermark. The watermark is embedded into original image by using HVS. The tamper detection can identify the tampered region of the received watermarked image. Experimental results are given.

FTG: Score-based black-box watermarking by fragile trigger generation for deep model integrity verification

Deep neural networks(DNNs)are widely used in real-world applications,thanks to their exceptional performance in image recognition.However,their vulnerability to attacks,such as Trojan and data poison,can compromise the integrity and stability of DNN applications.Therefore,it is crucial to verify the integrity of DNN models to ensure their security.Previous research on model watermarking for integrity detection has encountered the issue of overexposure of model parameters during embedding and extraction of the watermark.To address this problem,we propose a novel score-based black-box DNN fragile watermarking framework called fragile trigger generation(FTG).The FTG framework only requires the prediction probability distribution of the final output of the classifier during the watermarking process.It generates different fragile samples as the trigger,based on the classification prediction probability of the target classifier and a specified prediction probability mask to watermark it.Different prediction probability masks can promote the generation of fragile samples in corresponding distribution types.The whole watermarking process does not affect the performance of the target classifier.When verifying the watermarking information,the FTG only needs to compare the prediction results of the model on the samples with the previous label.As a result,the required model parameter information is reduced,and the FTG only needs a few samples to detect slight modifications in the model.Experimental results demonstrate the effectiveness of our proposed method and show its superiority over related work.The FTG framework provides a robust solution for verifying the integrity of DNN models,and its effectiveness in detecting slight modifications makes it a valuable tool for ensuring the security and stability of DNN applications.

Self-embedding Image Watermarking based on Combined Decision Using Pre-offset and Post-offset Blocks

To detect and recover random tampering areas,a combined-decision-based self-embedding watermarking scheme is proposed herein.In this scheme,the image is first partitioned into 2×2 size blocks.Next,the high 5 bits of a block’s average value is embedded into its offset block.The tampering type of block is detected by comparing the watermarks of its pre-offset and post-offset blocks.The theoretical analysis and experiments demonstrate that the proposed scheme not only has a lower ratio of false detection but also better performance with regard to avoiding random tampering.

Fragile Audio Watermarking with Perfect Restoration Capacity Based on an Adapted Integer Transform

We propose a novel audio watermarking scheme which can recover the original audio carrier perfectly if the watermarked audio is modified. Besides, we can adjust the maximum tampered rate allowed and the quality of watermarked audio flexibly as required. In the scheme, an efficient generalized integer transform is improved to embed watermark data which are composed of least significant bits（LSBs） of averages in each patch, reference-bits and check-bits. LSBs are needed in the inverse transform. Then, by comparing the extracted check-bits and calculated ones, the modified area can be localized. Finally, reliable reference-bits and samples data help us reconstruct the original audio without errors. The efficiency of the proposed method is theoretically and experimentally verified.