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This book constitutes the refereed proceedings of the 4th International Conference on Security, Privacy, and Applied Cryptography Engineering held in Pune, India, in October 2014. The 19 papers presented together with two invited papers were carefully reviewed and selected from 66 submissions. The papers are organized in topical sections on cryptographic building blocks; mini tutorial; attacks and countermeasures; tools and methods; and secure systems and applications.

The book discusses a broad overview of traditional machine learning methods and state-of-the-art deep learning practices for hardware security applications, in particular the techniques of launching potent "modeling attacks" on Physically Unclonable Function (PUF) circuits, which are promising hardware security primitives. The volume is self-contained and includes a comprehensive background on PUF circuits, and the necessary mathematical foundation of traditional and advanced machine learning techniques such as support vector machines, logistic regression, neural networks, and deep learning....

Digital Watermarking is the art and science of embedding information in existing digital content for Digital Rights Management (DRM) and authentication. Reversible watermarking is a class of (fragile) digital watermarking that not only authenticates multimedia data content, but also helps to maintain perfect integrity of the original multimedia "cover data." In non-reversible watermarking schemes, after embedding and extraction of the watermark, the cover data undergoes some distortions, although perceptually negligible in most cases. In contrast, in reversible watermarking, zero-distortion...