FirmFuzz-Reference-Cited by-同舟云学术

FirmFuzz

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2nd International ACM Workshop on Security and Privacy for the Internet-of-Things - IoT S&P'19
language:
Short-container-title:

Author:

Srivastava Prashast¹,Peng Hui¹,Li Jiahao²,Okhravi Hamed³,Shrobe Howard²,Payer Mathias⁴

Affiliation:

1. Purdue University, West Lafayette, IN, USA

2. Massachusetts Institute of Technology CSAIL, Cambridge, MA, USA

3. Massachusetts Institute of Technology Lincoln Laboratory, Lexington, MA, USA

4. EPFL, Lausanne, Switzerland

Funder

National Science Foundation

Office of the Under Secretary of Defense

Office of Naval Research

Publisher

ACM Press

Reference17 articles.

1. Manos Antonakakis, Tim April, Michael Bailey, Elie Bursztein, Jaime Cochran,Zakir Durumeric, J Alex Halderman, Damian Menscher, Chad Seaman, Nick Sullivan, Kurt Thomas, Yi Zhou, Manos Antonakakis Tim April Michael Bailey Matthew Bernhard Elie Bursztein, Bullet J Jaime Cochran Zakir Durumeric Alex Halderman Luca Invernizzi, Bullet Michalis Kallitsis Deepak Kumar Chaz Lever Zane Ma, Joshua Mason Damian Menscher, Bullet Chad Seaman Nick Sullivan Kurt Thomas, and Bullet Yi Zhou. 2017. Understanding the Mirai Botnet. In Proceedings of the 26th USENIX Security Symposium. 1093--1110. https://www.usenix.org/conference/usenixsecurity17/technical-sessions/presentation/antonakakis

2. Daming Dominic Chen, Manuel Egele, Maverick Woo, and David Brumley. 2016. Towards Fully Automated Dynamic Analysis for Embedded Firmware. Network and Distributed System Security Symposium February (2016), 21--24. https://doi.org/10.14722/ndss.2016.23415

3. Andrei Costin, Apostolis Zarras, and Aurélien Francillon. 2016. Automated Dynamic Firmware Analysis at Scale: A Case Study on Embedded Web Interfaces. Proceedings of the 2016 ACM Asia Conference on Computer and Communications Security (AsiaCCS'16)(2016), 437--448. https://doi.org/10.1145/2897845.2897900arXiv:1511.03609

4. Patrice Godefroid, Hila Peleg, and Rishabh Singh. 2017. Learn &

5. Fuzz: Machine learning for input fuzzing. In ASE 2017 - Proceedings of the 32nd IEEE/ACM International Conference on Automated Software Engineering. 50--59. https://doi.org/10.1109/ASE.2017.8115618 arXiv:1701.07232

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