April Galyardt
SEI Software Solutions Division
Publications by April Galyardt
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On Managing Vulnerabilities in AI/ML Systems
October 01, 2020 • Conference Paper
Jonathan SpringAllen D. HouseholderApril Galyardt
This paper explores how the current paradigm of vulnerability management might adapt to include machine learning systems.
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Women in Software and Cybersecurity: Dr. April Galyardt
March 10, 2020 • Podcast
April Galyardt
Dr. April Galyardt, a machine learning research scientist in the SEI's CERT Division, discusses her career journey, challenges, and lessons learned along the way.
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Comments on NISTIR 8269 (A Taxonomy and Terminology of Adversarial Machine Learning)
February 04, 2020 • White Paper
April GalyardtNathan M. VanHoudnosJonathan Spring
Feedback to the U.S. National Institute of Standards and Technology (NIST) about NIST IR 8269, a draft report detailing the proposed taxonomy and terminology of Adversarial Machine Learning (AML).
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Machine Learning in Cybersecurity: 7 Questions for Decision Makers
December 12, 2019 • Podcast
Jonathan SpringApril GalyardtAngela Horneman
April Galyardt, Angela Horneman, and Jonathan Spring discuss key questions that managers and decision makers should ask about machine learning to effectively solve cybersecurity problems.
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Component Mismatches Are a Critical Bottleneck to Fielding AI-Enabled Systems in the Public Sector
December 10, 2019 • Conference Paper
Grace LewisStephany BellomoApril Galyardt
We are investigating classes of mismatches in ML/AI systems integration, to identify the implicit assumptions made by practitioners in different fields (data scientists, software engineers, operations staff) and find ways to communicate the information.
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Machine Learning in Cybersecurity: A Guide
September 05, 2019 • Technical Report
Jonathan SpringJoshua FallonApril Galyardt
This report suggests seven key questions that managers and decision makers should ask about machine learning tools to effectively use those tools to solve cybersecurity problems.
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Assessing Cybersecurity Training
July 11, 2019 • Podcast
April Galyardt
April Galyardt, a machine learning research scientist, discusses efforts to develop a new approach to assessing the skills of the cybersecurity workforce.
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Artificial Intelligence and Machine Learning – Hype vs Reality
June 18, 2019 • Video
Rotem D. GuttmanApril Galyardt
Rotem Guttman and April Galyardt describe how machine learning (ML) fits into the bigger picture of artificial intelligence (AI) and discuss the current state of AI.
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Cyber Intelligence Tradecraft Report: The State of Cyber Intelligence Practices in the United States (Study Report and Implementation Guides)
May 21, 2019 • Collection
Jared EttingerApril GalyardtRitwik Gupta
This report details the findings of a study the SEI conducted at the request of the United States Office of the Director of National Intelligence. In the report, we present current best practices and common challenges in cyber intelligence.
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Explainable AI and Human Computer Interaction
October 24, 2018 • Presentation
April Galyardt
discussion of explainable AI
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Operational Cyber Risk Reduction
October 24, 2018 • Presentation
April GalyardtJosh Hammerstein
Approaches for cyber risk reduction
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Digital Footprints: What Can be Learned from the Traces We Leave on Social Networks
July 12, 2018 • Webinar
April GalyardtCarson Sestili
In this first webcast in a two-part series, April Galyardt and Carson Sestili described what metadata is and what information can be gleaned from it.
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Digital Footprints: What Can Be Learned From The Traces We Leave On Social Networks
May 30, 2018 • Presentation
April Galyardt
In this first webcast in a two-part series, we will describe what metadata is and what information can be gleaned from it.
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Federal Virtual Training Environment (FedVTE)
June 05, 2017 • White Paper
Marie BakerApril GalyardtDominic A. Ross
The Federal Virtual Training Environment (FedVTE) is an online, on‐demand training system containing cybersecurity and certification prep courses, at no cost to federal, state, and local government employees.
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