Case Study: Neural Network Malware Detection Verification for Feature and Image Datasets-Reference-Cited by-同舟云学术

Case Study: Neural Network Malware Detection Verification for Feature and Image Datasets

Published:2024-04-14 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2024 IEEE/ACM 12th International Conference on Formal Methods in Software Engineering (FormaliSE)
language:
Short-container-title:

Author:

Robinette Preston K.¹^ORCID,Manzanas Lopez Diego¹^ORCID,Serbinowska Serena²^ORCID,Leach Kevin¹^ORCID,Johnson Taylor T¹^ORCID

Affiliation:

1. Vanderbilt University, Nashville, TN, United States of America

2. Vanderbilt University, Nashville, TN, USA

Funder

National Defense Science and Engineering Graduate

NSF (National Science Foundation)

Defense Advanced Research Projects Agency

Air Force Office of Scientific Research

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3644033.3644372

Reference39 articles.

1. [n. d.]. 2022 Incident Response Report. https://www.paloaltonetworks.com/unit42/2022-incident-response-report

2. Stanley Bak. 2021. nnenum: Verification of ReLU Neural Networks with Optimized Abstraction Refinement. In NASA Formal Methods Symposium. Springer.

3. Branch and Bound for Piecewise Linear Neural Network Verification;Bunel Rudy;J. Mach. Learn. Res.,2020

4. Nicholas Carlini, Florian Tramer, Krishnamurthy Dj Dvijotham, Leslie Rice, Mingjie Sun, and J Zico Kolter. 2023. (Certified!!) Adversarial Robustness for Free!. In The Eleventh International Conference on Learning Representations. https://openreview.net/forum?id=JLg5aHHv7j

5. Nicholas Carlini and David Wagner. 2017. Magnet and" efficient defenses against adversarial attacks" are not robust to adversarial examples. arXiv preprint arXiv:1711.08478 (2017).

Cited by 1 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. Tutorial: Safe, Secure, and Trustworthy Artificial Intelligence (AI) via Formal Verification of Neural Networks and Autonomous Cyber-Physical Systems (CPS) with NNV;2024 54th Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume (DSN-S);2024-06-24