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Secure program execution via dynamic information flow tracking

Suh, G. Edward, Lee, Jae W., Zhang, David, Devadas, Srinivas·2004·Proceedings of the 11th international conference on Architectural support for programming languages and operating systems

Abstract

We present a simple architectural mechanism called dynamic information flow tracking that can significantly improve the security of computing systems with negligible performance overhead. Dynamic information flow tracking protects programs against malicious software attacks by identifying spurious information flows from untrusted I/O and restricting the usage of the spurious information.Every security attack to take control of a program needs to transfer the program's control to malevolent code. In our approach, the operating system identifies a set of input channels as spurious, and the processor tracks all information flows from those inputs. A broad range of attacks are effectively defeated by checking the use of the spurious values as instructions and pointers.Our protection is transparent to users or application programmers; the executables can be used without any modification. Also, our scheme only incurs, on average, a memory overhead of 1.4% and a performance overhead of 1.1%.

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Metadata

Authors
Suh, G. E., Lee, J. W., Zhang, D., & Devadas, S.
Venue
Proceedings of the 11th international conference on Architectural support for programming languages and operating systems
Publisher
ACM
Published
2004-10-07
Pages
85-96
OpenAlex
W2100666033
Cited by
740
References
0
FWCI
27.54
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Secure program execution via dynamic information flow tracking. https://app.cochat.ai/papers/10.1145/1024393.1024404
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Suh, G. E., Lee, J. W., Zhang, D., & Devadas, S. (2004). Secure program execution via dynamic information flow tracking. Proceedings of the 11th international conference on Architectural support for programming languages and operating systems. https://doi.org/10.1145/1024393.1024404

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.