Software that covertly monitors user actions, also known as spyware, has become a first-level security threat due to its ubiquity and the difficulty of detecting and removing it. This is especially so for video conferencing, thin-client computing and Internet cafes.
CryptoGraphics: Exploiting Graphics Cards for Security explores the potential for implementing ciphers within GPUs, and describes the relevance of GPU-based encryption to the security of applications involving remote displays. As the processing power of GPUs increases, research involving the use of GPUs for general purpose computing has arisen. This work extends such research by considering the use of a GPU as a parallel processor for encrypting data. The authors evaluate the operations found in symmetric and asymmetric key ciphers to determine if encryption can be programmed in existing GPUs. A detailed description for a GPU based implementation of AES is provided. The feasibility of GPU-based encryption allows the authors to explore the use of a GPU as a trusted system component. Unencrypted display data can be confined to the GPU to avoid exposing it to any malware running on the operating system.
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An invited speaker at the 2005 RSA Conference, Cryptographers Track, Debra Cook is a Ph.D. student in computer science at Columbia University in New York. Her research interests are focused in applied cryptography. She has a B.S. and M.S.E. in mathematical sciences from the Johns Hopkins University and an M.S. in computer science from Columbia. After graduating from Johns Hopkins, she was a senior technical staff member at Bell Labs and AT&T Labs before pursuing her Ph.D.
Angelos Keromytis is an Assistant Professor of Computer Science at Columbia University. His research interests include design and analysis of network and cryptographic protocols, software security and reliability, and operating system design. He received his Ph.D. in Computer Science from the University of Pennsylvania, and his B.S. in Computer Science from the University of Crete in Greece.
CryptoGraphics: Exploiting Graphics Cards for Security explores the potential for implementing ciphers within graphics processing units (GPUs), and describes the relevance of GPU-based encryption and decryption to the security of applications involving remote displays.
As a result of the increasing processing power of GPUs, research involving the use of GPUs for general purpose computing has arisen. While GPUs do not support the range of operations found in CPUs, their processing power has grown to exceed that of CPUs and their designs are evolving to increase their programmability. GPUs are especially attractive for applications requiring a large quantity of parallel processing. This work extends such research by considering the use of GPUs as a parallel processor for encrypting data.
The authors evaluate the operations found in symmetric and asymmetric key ciphers to determine if encryption can be programmed in existing GPUs. While certain operations make it impossible to implement some ciphers in a GPU, the operations used in most block ciphers, including AES, can be performed in GPUs. A detailed description and code for a GPU based implementation of AES is provided.
The feasibility of GPU-based encryption allows the authors to explore the use of a GPU as a trusted system component. The motivation for using a GPU as a trusted component, including the applicability to thin-client and remote conferencing applications, is discussed. By enabling encryption and decryption in a GPU, unencrypted display data can be confined to the GPU to avoid exposing it to any malware running on the operating system. A prototype implementation of GPU-based decryption for protecting displays exported to untrusted clients is described. Issues and solutions related to fully securing data on untrusted clients, including the protection of user input, are also discussed.
CryptoGraphics: Exploiting Graphics Cards for Security is designed for a professional audience of researchers and practitioners in industry. This book is also suitable as a secondary text for advanced-level students in computer science.
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