Quantum Machine Learning for Software Supply Chain Attacks: How Far Can We Go?-Reference-Cited by-同舟云学术

Quantum Machine Learning for Software Supply Chain Attacks: How Far Can We Go?

Published:2022-06 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)
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Short-container-title:

Author:

Masum Mohammad¹,Nazim Mohammad²,Faruk Md Jobair Hossain³,Shahriar Hossain¹,Valero Maria²,Khan Md Abdullah Hafiz²,Uddin Gias⁴,Barzanjeh Shabir⁴,Saglamyurek Erhan⁴,Rahman Akond⁵,Ahamed Sheikh Iqbal⁶

Affiliation:

1. Analytics and Data Science Institute, Kennesaw State University,USA

2. Kennesaw State University,Department of Computer Science,USA

3. Kennesaw State University,Department of Software Engineering and Game Development,USA

4. Institute for Quantum Science and Technology, University of Calgary,Electrical and Software Engineering,Canada

5. Tennessee Tech University,Department of Computer Science,USA

6. Marquette University,Department of Computer Science,USA

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9842455/9842394/09842669.pdf?arnumber=9842669

Reference37 articles.

1. Quantum Support Vector Machine for Big Data Classification

2. Quantum Neural Networks: Concepts, Applications, and Challenges

3. Quantum Neural Networks

4. A Review of Quantum Cybersecurity: Threats, Risks and Opportunities;jobair;1st International Conference on AI in Cybersecurity (ICAIC),2022

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