A Novel Block-based Watermarking Scheme Using the SVD Transform

In this paper, a block-based watermarking scheme based on the Singular Value Decomposition (SVD) is proposed. Our watermark, a pseudo-random Gaussian sequence, is embedded by modifying the angles formed by the right singular vectors of each block of the original image. The orthogonality property of the right singular vector matrix is preserved during the embedding process. Several experiments have been carried out to test the performance of the proposed scheme against different attack scenarios. We conclude that the proposed scheme is resistant against common signal processing operations and attacks, while it preserves the quality of the original image

Digital Watermarking Security

As creative works (e.g. books, films, music, photographs) become increasingly available in digital formats in a highly connected world, it also becomes increasingly difficult to secure intellectual property rights. Digital watermarking is one potential technology to aid intellectual property owners in controlling and tracking the use of their works. Surveys the state of digital watermarking research and examines the attacks that the technology faces and how it fares against them. Digital watermarking is an inherently difficult design problem subject to many constraints. The technology currently faces an uphill battle to be secure against relatively simple attacks

A survey on security analysis of machine learning-oriented hardware and software intellectual property

Intellectual Property (IP) includes ideas, innovations, methodologies, works of authorship (viz., literary and artistic works), emblems, brands, images, etc. This property is intangible since it is pertinent to the human intellect. Therefore, IP entities are indisputably vulnerable to infringements and modifications without the owner’s consent. IP protection regulations have been deployed and are still in practice, including patents, copyrights, contracts, trademarks, trade secrets, etc., to address these challenges. Unfortunately, these protections are insufficient to keep IP entities from being changed or stolen without permission. As for this, some IPs require hardware IP protection mechanisms, and others require software IP protection techniques. To secure these IPs, researchers have explored the domain of Intellectual Property Protection (IPP) using different approaches. In this paper, we discuss the existing IP rights and concurrent breakthroughs in the field of IPP research; provide discussions on hardware IP and software IP attacks and defense techniques; summarize different applications of IP protection; and lastly, identify the challenges and future research prospects in hardware and software IP security

Protecting Ownership Rights of Videos Against Digital Piracy: An Efficient Digital Watermarking Scheme

Violation of one’s intellectual ownership rights by the others is a common problem which entertainment industry frequently faces now-a-days. Sharing of information over social media platforms such as Instagram, WhatsApp and twitter without giving credit the owner causes huge financial losses to the owner and hence needs an immediate attention. Digital watermarking is a promising technique to protect owners’ right against digital piracy. Most of the state-of-the-art techniques does not provides adequate level of resilience against majority of video specific attacks and other commonly applied attacks. Therefore, this paper proposes a highly transparent and robust video watermarking solution to protect the owners rights by first convert each video frame into YCbCr color components and then select twenty five strongest speeded-up robust features (SURF) points of the normalized luminance component as points for both watermark embedding and extraction. After applying variety of geometric, simple signal processing and video specific attacks on the watermarked video meticulous analysis is performed using popular metrics which reveals that the proposed scheme possesses high correlation value which makes it superior for practical applications against these attacks. The scheme also proposes a novel three-level impairment scale for subjective analysis which gives stable results to derive correct conclusions

Deep Intellectual Property: A Survey

With the widespread application in industrial manufacturing and commercial services, well-trained deep neural networks (DNNs) are becoming increasingly valuable and crucial assets due to the tremendous training cost and excellent generalization performance. These trained models can be utilized by users without much expert knowledge benefiting from the emerging ''Machine Learning as a Service'' (MLaaS) paradigm. However, this paradigm also exposes the expensive models to various potential threats like model stealing and abuse. As an urgent requirement to defend against these threats, Deep Intellectual Property (DeepIP), to protect private training data, painstakingly-tuned hyperparameters, or costly learned model weights, has been the consensus of both industry and academia. To this end, numerous approaches have been proposed to achieve this goal in recent years, especially to prevent or discover model stealing and unauthorized redistribution. Given this period of rapid evolution, the goal of this paper is to provide a comprehensive survey of the recent achievements in this field. More than 190 research contributions are included in this survey, covering many aspects of Deep IP Protection: challenges/threats, invasive solutions (watermarking), non-invasive solutions (fingerprinting), evaluation metrics, and performance. We finish the survey by identifying promising directions for future research.Comment: 38 pages, 12 figure

Watermarking security: theory and practice

This article proposes a theory of watermarking security based on a cryptanalysis point of view. The main idea is that information about the secret key leaks from the observations, for instance watermarked pieces of content, available to the opponent. Tools from information theory (Shannon's mutual information and Fisher's information matrix) can measure this leakage of information. The security level is then defined as the number of observations the attacker needs to successfully estimate the secret key. This theory is applied to two common watermarking methods: the substitutive scheme and the spread spectrum based techniques. Their security levels are calculated against three kinds of attack. The experimental work illustrates how Blind Source Separation (especially Independent Component Analysis) algorithms help the opponent exploiting this information leakage to disclose the secret carriers in the spread spectrum case. Simulations assess the security levels derived in the theoretical part of the article

Integration and optimization of collusion secure fingerprinting in image watermarking

Estágio realizado na Fraunhofer SIT - e orientado pelo Dr. Huajian Liu e pelo Dr. Marcel SchäferTese de mestrado integrado. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 201