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Artificial intelligence

Fundamental AI

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Displaying 1 - 8 of 8

Robust AI Security and Alignment: A Sisyphean Endeavor?

May 14, 2026
Author(s)
Apostol Vassilev
This article establishes information-theoretic limitations for robustness of artificial intelligence (AI) security and alignment. Knowing these limitations and preparing for their challenges is essential for responsible adoption of AI. Broader implications

Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations

March 24, 2025
Author(s)
Apostol Vassilev, Alina Oprea, Alie Fordyce, Hyrum Anderson, Xander Davies, Maia Hamin
This NIST Trustworthy and Responsible AI report provides a taxonomy of concepts and defines terminology in the field of adversarial machine learning (AML). The taxonomy is arranged in a conceptual hierarchy that includes key types of ML methods, life cycle

Interactive Simulations of Backdoors in Neural Networks

May 21, 2024
Author(s)
Peter Bajcsy, Maxime Bros, Matthew Coudron
This work addresses the problem of planting and defending cryptographic-based backdoors in artificial intelligence models. The motivation comes from our lack of understanding and the implications of using cryptographic techniques for planting undetectable

Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations

January 4, 2024
Author(s)
Apostol Vassilev, Alina Oprea, Alie Fordyce, Hyrum Andersen
This NIST AI report develops a taxonomy of concepts and defines terminology in the field of adversarial machine learning (AML). The taxonomy is built on survey of the AML literature and is arranged in a conceptual hierarchy that includes key types of ML

Survey of Graph Neural Networks and Applications

July 28, 2022
Author(s)
Fan Liang, Cheng Qian, Wei Yu, David W. Griffith, Nada T. Golmie
The advance of deep learning has shown great potential in applications (speech, image and video classification). In these applications, deep learning models are trained by datasets in Euclidean space with fixed dimensions and sequences. Nonetheless, the

Towards a Standard for Identifying and Managing Bias in Artificial Intelligence

March 15, 2022
Author(s)
Reva Schwartz, Apostol Vassilev, Kristen K. Greene, Lori Perine, Andrew Burt, Patrick Hall
As individuals and communities interact in and with an environment that is increasingly virtual they are often vulnerable to the commodification of their digital exhaust. Concepts and behavior that are ambiguous in nature are captured in this environment
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