Combining Control-Flow Integrity and Static Analysis for Efficient and Validated Data Sandboxing

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Combining Control-Flow Integrity and Static Analysis for Efficient and Validated Data Sandboxing

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Title: Combining Control-Flow Integrity and Static Analysis for Efficient and Validated Data Sandboxing
Author: Zeng, Bin; Tan, Gang; Morrisett, John Gregory

Note: Order does not necessarily reflect citation order of authors.

Citation: Zeng, Bin, Gang Tan, and J. Greg Morrisett. 2011. Combining control-flow integrity and static analysis for efficient and validated data sandboxing. In CCS '11 Proceedings of the 18th ACM conference on Computer and communications security: Chicago, Illinois, October 17-21, 2011, ed. Yan Chen, George Danezis, and Vitaly Shmatikov, 29-40. New York, NY: Association for Computing Machinery.
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Abstract: In many software attacks, inducing an illegal control-flow transfer in the target system is one common step. Control-Flow Integrity (CFI) protects a software system by enforcing a pre-determined control-flow graph. In addition to providing strong security, CFI enables static analysis on low-level code. This paper evaluates whether CFI-enabled static analysis can help build efficient and validated data sandboxing. Previous systems generally sandbox memory writes for integrity, but avoid protecting confidentiality due to the high overhead of sandboxing memory reads. To reduce overhead, we have implemented a series of optimizations that remove sandboxing instructions if they are proven unnecessary by static analysis. On top of CFI, our system adds only 2.7% runtime overhead on SPECint2000 for sandboxing memory writes and adds modest 19% for sandboxing both reads and writes. We have also built a principled data-sandboxing verifier based on range analysis. The verifier checks the safety of the results of the optimizer, which removes the need to trust the rewriter and optimizer. Our results show that the combination of CFI and static analysis has the potential of bringing down the cost of general inlined reference monitors, while maintaining strong security.
Published Version: doi:10.1145/2046707.2046713
Other Sources: http://www.cse.lehigh.edu/~gtan/paper/cfiDataSandboxing.pdf
Terms of Use: This article is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#OAP
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:9943234

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  • FAS Scholarly Articles [7176]
    Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University
 
 

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