DeepMarks: A Digital Fingerprinting Framework for Deep Neural Networks

This paper proposes DeepMarks, a novel end-to-end framework for systematic fingerprinting in the context of Deep Learning (DL). Remarkable progress has been made in the area of deep learning. Sharing the trained DL models has become a trend that is ubiquitous in various fields ranging from biomedical diagnosis to stock prediction. As the availability and popularity of pre-trained models are increasing, it is critical to protect the Intellectual Property (IP) of the model owner. DeepMarks introduces the first fingerprinting methodology that enables the model owner to embed unique fingerprints within the parameters (weights) of her model and later identify undesired usages of her distributed models. The proposed framework embeds the fingerprints in the Probability Density Function (pdf) of trainable weights by leveraging the extra capacity available in contemporary DL models. DeepMarks is robust against fingerprints collusion as well as network transformation attacks, including model compression and model fine-tuning. Extensive proof-of-concept evaluations on MNIST and CIFAR10 datasets, as well as a wide variety of deep neural networks architectures such as Wide Residual Networks (WRNs) and Convolutional Neural Networks (CNNs), corroborate the effectiveness and robustness of DeepMarks framework

Digital Right Management (DRM) Dan Audio Watermarking Untuk Perlindungan Hak Cipta Pada Konten Musik Digital

Pembajakan hak cipta terhadap konten musik digital masih menjadi masalah besar dalam industri musik. Hal tersebut dikarenakan mudahnya proses pembajakan dan kemudahan distribusi konten digital melalui internet. Isu perlindungan hak cipta menjadi hal sangat penting untuk diterapkan dalam industri musik. Digital right management (DRM) dan audio watermarking adalah cara yang bisa diterapkan untuk melindungi properti intelektual hak cipta pada konten musik digital melawan pembajakan

Comparative Analysis Spread Spectrum and Parity Coding Steganography in E-commerce

The transaction data online has increased compared to the previous communications that mostly in the form of voice and text messaging. To improve the security, data must be protected such a way that it cannot be attacked by unauthorized parties. In this case, a good security system must be able to transmit the original information to the second party without having to know the existence and validity by a third party. One of the security systems that can be used is steganography. In this paper, we will compare the performance of Spread Spectrum and Parity Coding in e-commerce based on Android in case of processing time between insertion and retrieval information, and the changing image size during the insertion process. Our experimental results show that parity coding has better performance on client side that use low performance smart phone based on Android operating system and spread spectrum has better performance on blackberry store server that use laptop PC

A Review of Copyright Protection Approaches in Electronic Commerce (Watermarking Method)

Digital watermarking is the best way to protect intellectual property from illicit copying. Digital watermarks hide the identity of an image or audio file in its noise signal. A pattern of bits inserted into a digital image, audio or video file that identifies the files copyright information. The purpose of this paper is to provide copyright protection for intellectual property that\u27s in digital format. In this career we review digital watermarks an application of steganography

Digital Right Management (DRM) dan Audio Watermarking untuk Perlindungan Hak Cipta pada Konten Musik Digital

Pembajakan hak cipta terhadap konten musik digital masih menjadi masalah besar dalam industri musik. Hal tersebut dikarenakan mudahnya proses pembajakan dan kemudahan distribusi konten digital melalui internet. Isu perlindungan hak cipta menjadi hal sangat penting untuk diterapkan dalam industri musik. Digital right management (DRM) dan audio watermarking adalah cara yang bisa diterapkan untuk melindungi properti  intelektual hak cipta pada  konten musik digital melawan pembajakan.  Kata kunci: pembajakan musik, musik digital, digital audio, hak cipta, digital right management (DRM),  audio watermarking