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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

On managing vulnerabilities in AI/ML systems
Jonathan Spring, April Galyardt, Allen D. Householder, et al.
New Security Paradigms Workshop (2020), pp. 111-126
Open Access | Times Cited: 14

Showing 14 citing articles:

Machine learning security attacks and defense approaches for emerging cyber physical applications: A comprehensive survey
Jaskaran Singh, Mohammad Wazid, Ashok Kumar Das, et al.
Computer Communications (2022) Vol. 192, pp. 316-331
Closed Access | Times Cited: 24
Three Challenges to Secure AI Systems in the Context of AI Regulations
Ronan Hamon, H. Junklewitz, Josep Soler Garrido, et al.
IEEE Access (2024) Vol. 12, pp. 61022-61035
Open Access | Times Cited: 5
Robust Testing of AI Language Models Resilience with Novel Adversarial Prompts
Brendan Hannon, Yulia Kumar, Dejaun Gayle, et al.
(2024)
Open Access | Times Cited: 4
Evaluating the Cybersecurity Risk of Real-world, Machine Learning Production Systems
Ron Bitton, Nadav Maman, Inderjeet Singh, et al.
ACM Computing Surveys (2022) Vol. 55, Iss. 9, pp. 1-36
Open Access | Times Cited: 11
Robust Testing of AI Language Model Resiliency with Novel Adversarial Prompts
Brendan Hannon, Yulia Kumar, Dejaun Gayle, et al.
Electronics (2024) Vol. 13, Iss. 5, pp. 842-842
Open Access | Times Cited: 2
Adversarial Machine Learning and Cybersecurity
Micah Musser
(2023)
Open Access | Times Cited: 5
Why We Need to Know More: Exploring the State of AI Incident Documentation Practices
Violet Turri, Rachel Dzombak
(2023), pp. 576-583
Open Access | Times Cited: 4
Identifying Patterns in Common Vulnerabilities and Exposures Databases with Exploratory Data Analysis
Atul Kumar, Ishu Sharma
2022 International Conference on Automation, Computing and Renewable Systems (ICACRS) (2022), pp. 919-924
Closed Access | Times Cited: 7
Supporting Artificial Intelligence/Machine Learning Security Workers Through an Adversarial Techniques, Tools, and Common Knowledge Framework
Mohamad Fazelnia, Ahmet Okutan, Mehdi Mirakhorli
IEEE Security & Privacy (2022) Vol. 21, Iss. 1, pp. 37-48
Closed Access | Times Cited: 6
Standards for LLM Security
Subhabrata Majumdar
(2024), pp. 225-231
Closed Access
Artificial Intelligence and Machine Learning for Network Security: Quo Vadis?
Michael J. De Lucia, Avinash Srinivasan
Advances in information security (2024), pp. 79-97
Closed Access
A Framework for Evaluating the Cybersecurity Risk of Real World, Machine Learning Production Systems.
Ron Bitton, Nadav Maman, Inderjeet Singh, et al.
arXiv (Cornell University) (2021)
Closed Access | Times Cited: 3
Design of an Academic CSIRT – A Proposal Based on Strategic Planning Principles
Daniel Nuñez-Agurto, Mario Ron, Enrique V. Carrera, et al.
Lecture notes in networks and systems (2022), pp. 295-308
Closed Access | Times Cited: 1
Navigating the Landscape of Robust and Secure Artificial Intelligence: A Comprehensive Literature Review
Et al. Saurabh Suman Choudhuri
International Journal on Recent and Innovation Trends in Computing and Communication (2023) Vol. 11, Iss. 11, pp. 617-623
Open Access
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