الصفحة 1
الصفحة 1
Information security practice and experience ; 4th International Conference, ISPEC 2008 Sydney, Australia, April 21-23, 2008 Proceedings
The 4 th Information Security Practice and Experience Conference (ISPEC2008) was held at Crowne Plaza, Darling Harbour, Sydney, Australia, during April 21-23, 2008. The previous three conferences were held in Singapore in 2005, Hangzhou, China in 2006 and Hong Kong, China in 2007. As with the previous three conference proceedings, the proceedings of ISPEC 2008 were published in the LNCS series by Springer. The conference received 95 submissions, out of which the Program Committee selected 29 papers for presentation at the conference. These papers are included in the proceedings. The accepted papers cover a range of topics in mathem- ics, computer science and security applications.
Information security applications ; 21st International Conference, WISA 2020, Jeju Island, South Korea, August 26–28, 2020, Revised Selected Papers
This book constitutes the thoroughly refereed proceedings of the 21st International Conference on Information Security Applications, WISA 2020, held in Jeju Island, South Korea, in August 2020. The 30 full research papers included in this book were carefully reviewed and selected from 89 submissions. They are organized in the following topical sections: AI Security and Intrusion Detection; Steganography and Malware; Application, System, and Hardware Security; Cryptography; Advances in Network Security and Attack Defense; and Cyber Security.
Frontiers in Hardware Security and Trust : Theory, design and practice
The footprint and power constraints imposed on internet-of-things end-points, smart sensors, mobile and ad hoc network devices make traditional and software based cryptographic solutions that require a general-purpose processor increasingly unfeasible. The fact that security is not the primary functionality of these devices means that only a small portion of their limited processing power and storage is available for security, driving the need for alternative security solutions. Hardware security - including hardware obfuscation, hardware security primitives, side-channel attacks and so on - is therefore becoming an increasingly active research area in both academia and industry.
Deep learning for computational problems in hardware security : Modeling attacks on strong physically unclonable function circuits
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. This book can be used as a self-learning resource for researchers and practitioners of hardware security, and will also be suitable for graduate-level courses on hardware security and application of machine learning in hardware security.
