LO-FAT

Author:

Dessouky Ghada1,Zeitouni Shaza1,Nyman Thomas2,Paverd Andrew3,Davi Lucas4,Koeberl Patrick5,Asokan N.3,Sadeghi Ahmad-Reza1

Affiliation:

1. Technische Universität Darmstadt, Germany

2. Aalto University, Finland and Trustonic, Finland

3. Aalto University, Finland

4. University of Duisburg-Essen, Germany

5. Intel Labs, Germany

Publisher

ACM

Cited by 59 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Using Page Offsets for Detecting Control-Flow Anomalies;Innovative Security Solutions for Information Technology and Communications;2024

2. Whole-Program Control-Flow Path Attestation;Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security;2023-11-15

3. Caveat (IoT) Emptor: Towards Transparency of IoT Device Presence;Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security;2023-11-15

4. $\mathcal{P}\text{ARseL}$: Towards a Verified Root-of-Trust Over seL4;2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD);2023-10-28

5. Blockchain-Assisted Integrity Attestation of Distributed Dependency IoT Services;IEEE SYST J;2023

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