2026-09-19T00:46:47Zhttps://ecommons.cornell.edu/server/oai/requestoai:ecommons.cornell.edu:1813/442992026-05-14T13:54:31Zcom_1813_35col_1813_47
Deng, Danny
Suh,Gookwon Edward
Manohar,Rajit
Martinez,Jose F.
2016-07-05T15:30:02Z
2016-07-05T15:30:02Z
2016-05-29
https://hdl.handle.net/1813/44299
https://doi.org/10.7298/X40K26H3
9597066
Secure and reliable computing remains an open problem. Just in the past year, security vulnerabilities continued to be discovered in widely-used applications, and remote attacks that take advantage of these vulnerabilities can cause an enormous amount of damage. Runtime monitoring is a promising approach for addressing a wide range of security and reliability problems in a general and transparent fashion. However, software-only approaches have high performance overheads on applications, and using custom hardware to mitigate these overheads can result in rigid schemes that are unable to adapt to new threats. In this thesis, we will describe steps to build an architectural framework for runtime monitoring that can address the drawbacks of previously proposed runtime monitoring schemes by utilizing reconfigurable hardware and optimizing for performance.
en_US
Computer Security
Co-Processing
Cache Compression
Flexible And Efficient Accelerator Architecture For Runtime Monitoring
dissertation or thesis
application/pdf
Electrical Engineering
Cornell University
Doctor of Philosophy
Ph. D., Electrical Engineering
Publication
Cornell Theses and Dissertations
Deng, Danny
5893a6ea-7af3-41d7-abc6-04bcd26ab5df
open.access
open.access
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<Abstract>Secure and reliable computing remains an open problem. Just in the past year, security vulnerabilities continued to be discovered in widely-used applications, and remote attacks that take advantage of these vulnerabilities can cause an enormous amount of damage. Runtime monitoring is a promising approach for addressing a wide range of security and reliability problems in a general and transparent fashion. However, software-only approaches have high performance overheads on applications, and using custom hardware to mitigate these overheads can result in rigid schemes that are unable to adapt to new threats. In this thesis, we will describe steps to build an architectural framework for runtime monitoring that can address the drawbacks of previously proposed runtime monitoring schemes by utilizing reconfigurable hardware and optimizing for performance.</Abstract>
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