C-FLAT: Control-FLow ATtestation for Embedded Systems Software
Not on the map. Why?
Abstract (arXiv)
Remote attestation is a crucial security service particularly relevant to increasingly popular IoT (and other embedded) devices. It allows a trusted party (verifier) to learn the state of a remote, and potentially malware-infected, device (prover). Most existing approaches are static in nature and only check whether benign software is initially loaded on the prover. However, they are vulnerable to run-time attacks that hijack the application's control or data flow, e.g., via return-oriented programming or data-oriented exploits. As a concrete step towards more comprehensive run-time remote attestation, we present the design and implementation of Control- FLow ATtestation (C-FLAT) that enables remote attestation of an application's control-flow path, without requiring the source code. We describe a full prototype implementation of C-FLAT on Raspberry Pi using its ARM TrustZone hardware security extensions. We evaluate C-FLAT's performance using a real-world embedded (cyber-physical) application, and demonstrate its efficacy against control-flow hijacking attacks.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 May 2016.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 2; 2025: 2; 2026: 2.
8 papers.
- 2022Proof of Unlearning: Definitions and Instantiationcited by 15
- 2024One for All and All for One: GNN-based Control-Flow Attestation for Embedded Devicescited by 1
- 2024VerifiableFL: Verifiable Claims for Federated Learning using Exclavescited by 1
- 2025Enabling Trustworthy Federated Learning via Remote Attestation for Mitigating Byzantine Threatscited by 1
- 2025AttestLLM: Efficient Attestation Framework for Billion-scale On-device LLMscited by 1
- 2021Code Integrity Attestation for PLCs using Black Box Neural Network Predictionscited by 0
- 2026Walma: Learning to See Memory Corruption in WebAssemblycited by 0
- 2026Downsides of Smartness Across Edge-Cloud Continuum in Modern Industrycited by 0
- 2026Downsides of Smartness Across Edge-Cloud Continuum in Modern Industry31 Mar 2026
- 2026Walma: Learning to See Memory Corruption in WebAssembly25 Mar 2026
- 2025AttestLLM: Efficient Attestation Framework for Billion-scale On-device LLMs8 Sep 2025
- 2025Enabling Trustworthy Federated Learning via Remote Attestation for Mitigating Byzantine Threats30 Aug 2025
- 2024VerifiableFL: Verifiable Claims for Federated Learning using Exclaves13 Dec 2024
- 2024One for All and All for One: GNN-based Control-Flow Attestation for Embedded Devices12 Mar 2024
- 2022Proof of Unlearning: Definitions and Instantiation20 Oct 2022
- 2021Code Integrity Attestation for PLCs using Black Box Neural Network Predictions15 Jun 2021