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Title: Position paper: GPT conjecture: understanding the trade-offs between granularity, performance and timeliness in control-flow integrity
Abstract

Performance/security trade-off is widely noticed in CFI research, however, we observe that not every CFI scheme is subject to the trade-off. Motivated by the key observation, we ask three questions: ➊ does trade-off really exist in different CFI schemes? ➋ if trade-off do exist, how do previous works comply with it? ➌ how can it inspire future research? Although the three questions probably cannot be directly answered, they are inspiring. We find that a deeper understanding of the nature of the trade-off will help answer the three questions. Accordingly, we proposed theGPTconjecture to pinpoint the trade-off in designing CFI schemes, which says that at most two out of three properties (fine granularity, acceptable performance, and preventive protection) could be achieved.

 
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Award ID(s):
2019340 1814679
NSF-PAR ID:
10307270
Author(s) / Creator(s):
;
Publisher / Repository:
Springer Science + Business Media
Date Published:
Journal Name:
Cybersecurity
Volume:
4
Issue:
1
ISSN:
2523-3246
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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