Control-Flow Integrity

By Nathan Burow, Scott A. Carr, Joseph Nash, Per Larsen, Michael Franz, Stefan Brunthaler, Mathias Payer. ACM Computing Surveys, 2017

604 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Materials Chemistry, Signal Processing

View Paper: https://www.semanticscholar.org/paper/6828960c7447d878df8f278e285b269cdf8fb93d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Nicholas Carlini
2. David A. Wagner
3. Zhenkai Liang
4. Sanjit A. Seshia
5. Rohit Sinha
6. Dawn Song
7. Sriram K. Rajamani
8. Ahmad-Reza Sadeghi

In Materials Chemistry

1. David A. Wagner
2. Nicholas Carlini

In Signal Processing

1. Nicholas Carlini
2. Sanjit A. Seshia
3. Rohit Sinha
4. David A. Wagner
5. Sriram K. Rajamani
6. Lucas Davi
7. Ahmad-Reza Sadeghi
8. Sang Kil Cha

Citations in the corpus

• The Art, Science, and Engineering of Fuzzing: A Survey (2018, background): “Integrity [13], [14] (CFI), which detects control flow transitions at runtime that are not possible in the original program.”
• Counterfeit Object-oriented Programming: On the Difficulty of Preventing Code Reuse Attacks in C++ Applications (2015, methodology): “Before presenting the ideas and concepts behind COOP in detail, we review the background necessary for understanding our approach and its relation to existing work.”
• A design and verification methodology for secure isolated regions (2016, methodology): “Our method to check for WCFI-RW draws inspiration from prior work to perform instrumentation in order to satisfy control-flow integrity (CFI [2, 33]) and software fault isolation (SFI [27, 39, 44]).”
• Data-Oriented Programming: On the Expressiveness of Non-control Data Attacks (2016, methodology): “For example, the CFI proposed by Abadi et al. relies on read-only tags inside code region to enforce the security check [6].”
• HardFails: Insights into Software-Exploitable Hardware Bugs (2019, background): “Thus, we assume all platform software is protected by defenses such as control-flow integrity [1] and data-flow integrity [13], or is formally verified.”
• Control-Flow Bending: On the Effectiveness of Control-Flow Integrity (2015, methodology): “Control-Flow Integrity (CFI) [1, 15] adds a stateless check before each indirect control-flow transfer (indirect jump/call, or function return) to ensure that the target location is in a static set defined by the control-flow graph.”