MeshAdv: Adversarial Meshes for Visual Recognition

Highly expressive models such as deep neural networks (DNNs) have been widely applied to various applications. However, recent studies show that DNNs are vulnerable to adversarial examples, which are carefully crafted inputs aiming to mislead the predictions. Currently, the majority of these studies have focused on perturbation added to image pixels, while such manipulation is not physically realistic. Some works have tried to overcome this limitation by attaching printable 2D patches or painting patterns onto surfaces, but can be potentially defended because 3D shape features are intact. In this paper, we propose meshAdv to generate "adversarial 3D meshes" from objects that have rich shape features but minimal textural variation. To manipulate the shape or texture of the objects, we make use of a differentiable renderer to compute accurate shading on the shape and propagate the gradient. Extensive experiments show that the generated 3D meshes are effective in attacking both classifiers and object detectors. We evaluate the attack under different viewpoints. In addition, we design a pipeline to perform black-box attack on a photorealistic renderer with unknown rendering parameters.Comment: Published in IEEE CVPR201

A Study And Analysis Of Watermarking Algorithms For Medical Images

Digital watermarking techniques hide digital data into digital images imperceptibly for different purposes and applications such as copyright protection, authentication, and data hiding. Teknik-teknik pembenaman tera air menyembunyikan data digit ke dalam imej-imej digit untuk pelbagai keperluan dan aplikasi seperti perlindungan hak cipta, pengesahan, dan penyembunyian data

Data Hiding with Deep Learning: A Survey Unifying Digital Watermarking and Steganography

Data hiding is the process of embedding information into a noise-tolerant signal such as a piece of audio, video, or image. Digital watermarking is a form of data hiding where identifying data is robustly embedded so that it can resist tampering and be used to identify the original owners of the media. Steganography, another form of data hiding, embeds data for the purpose of secure and secret communication. This survey summarises recent developments in deep learning techniques for data hiding for the purposes of watermarking and steganography, categorising them based on model architectures and noise injection methods. The objective functions, evaluation metrics, and datasets used for training these data hiding models are comprehensively summarised. Finally, we propose and discuss possible future directions for research into deep data hiding techniques

An Efficient Digital Image Watermarking Based on DCT and Advanced Image Data Embedding Method

Digital image enhancement and digital content or data image secure using DCT and advanced image data embedding method (AIDEM). AIDEM improved robustness based on particle shifting concept is reproduced secure image data and manipulated there’s a robust would like for a digital image copyright mechanism to be placed in secure image data. There’s a necessity for authentication of the content because of the owner. It’s become more accessible for malicious parties to create scalable copies of proprietary content with any compensation to the content owner. Advanced Watermarking is being viewed as a potential goal to the current downside. Astounding watermarking plans are arranged assaults on the watermarked picture are twisted and proposed to give insurance of proprietorship freedoms, information treating, and information uprightness. These methods guarantee unique information recuperation from watermarked information, while irreversible watermarking plans safeguard proprietorship freedoms. This attribute of reversible watermarking has arisen as an applicant answer for the assurance of proprietorship freedoms of information, unfortunate to alterations, for example, clinical information, genetic information, Visa, and financial balance information. These attacks are also intentional or unintentional. The attacks are classified as geometric attacks. This research presents a comprehensive and old method of these techniques that are developed and their effectiveness. Digital watermarking was developed to supply copyright protection and owners’ authentication. Digital image watermarking may be a methodology for embedding some information into digital image sequences, like text image, image data, during this research analysis on image watermarking and attacks on watermarking process time image data, classification of watermarking and applications. We aim to secure image data using advanced image data embedding method (AIDEM) improved robustness based particle shifting concept is reproduced secure image data. To develop compelling digital image watermarking methodology using mat lab tool and reliable and robust

Medical image encryption techniques: a technical survey and potential challenges

Among the most sensitive and important data in telemedicine systems are medical images. It is necessary to use a robust encryption method that is resistant to cryptographic assaults while transferring medical images over the internet. Confidentiality is the most crucial of the three security goals for protecting information systems, along with availability, integrity, and compliance. Encryption and watermarking of medical images address problems with confidentiality and integrity in telemedicine applications. The need to prioritize security issues in telemedicine applications makes the choice of a trustworthy and efficient strategy or framework all the more crucial. The paper examines various security issues and cutting-edge methods to secure medical images for use with telemedicine systems

Data Management Challenges for Internet-scale 3D Search Engines

This paper describes the most significant data-related challenges involved in building internet-scale 3D search engines. The discussion centers on the most pressing data management issues in this domain, including model acquisition, support for multiple file formats, asset versioning, data integrity errors, the data lifecycle, intellectual property, and the legality of web crawling. The paper also discusses numerous issues that fall under the rubric of trustworthy computing, including privacy, security, inappropriate content, and copying/remixing of assets. The goal of the paper is to provide an overview of these general issues, illustrated by empirical data drawn from the internet's largest operational search engine. While numerous works have been published on 3D information retrieval, this paper is the first to discuss the real-world challenges that arise in building practical search engines at scale.Comment: Second version, distributed by SIGIR Foru

Data Hiding and Its Applications

Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others