Výsledky vyhledávání - "Charles Smutz"

Explainable AI in Cybersecurity Operations: Lessons Learned from xAI Tool Deployment

Autor: Megan Nyre-Yu, Elizabeth Morris, Michael Smith, Blake Moss, Charles Smutz

Publikováno v: Proceedings 2022 Symposium on Usable Security.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::a7e013e56bb1c6166f2ebc2ca68cccf4
https://doi.org/10.14722/usec.2022.23014

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SAGE Intrusion Detection System: Sensitivity Analysis Guided Explainability for Machine Learning

Autor: Michael Smith, Erin Acquesta, Arlo Ames, Alycia Carey, Christopher Cuellar, Richard Field, Trevor Maxfield, Scott Mitchell, Blake Moss, Elizabeth Morris, Megan Nyre-Yu, Ahmad Rushdi, Mallory Stites, Charles Smutz, Xin Zhou

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e38e84fe0a7033c9a91b286ab4ff7bf2
https://doi.org/10.2172/1820253

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Considerations for Deploying xAI Tools in the Wild: Lessons Learned from xAI Deployment in a Cybersecurity Operations Setting

Autor: Megan Nyre-Yu, Elizabeth Morris, Blake Moss, Charles Smutz, Michael Smith

Publikováno v: Proposed for presentation at the ACM SIG Knowledge Discovery and Data Mining Workshop on Responsible AI held August 14-18, 2021 in Singapore, Singapore..

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6511a2d4529602f468fc18f6955ff6f8
https://doi.org/10.2172/1869535

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Sage Advice? The Impacts of Explanations for Machine Learning Models on Human Decision-Making in Spam Detection

Autor: Charles Smutz, Mallory C. Stites, Michael R. Smith, Megan Nyre-Yu, Blake Moss

Publikováno v: Artificial Intelligence in HCI ISBN: 9783030777715
HCI (36)

The impact of machine learning (ML) explanations and different attributes of explanations on human performance was investigated in a simulated spam detection task. Participants decided whether the metadata presented about an email indicated that it w

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f89a2790f13ecc1d42656f6aa3906ea3
https://doi.org/10.1007/978-3-030-77772-2_18

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When a Tree Falls: Using Diversity in Ensemble Classifiers to Identify Evasion in Malware Detectors

Autor: Charles Smutz, Angelos Stavrou

Publikováno v: NDSS

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f137272d56abee9acf4be1c17f223c8b
https://doi.org/10.14722/ndss.2016.23078

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Malicious PDF detection using metadata and structural features

Autor: Charles Smutz, Angelos Stavrou

Publikováno v: ACSAC

Owed to their versatile functionality and widespread adoption, PDF documents have become a popular avenue for user exploitation ranging from large-scale phishing attacks to targeted attacks. In this paper, we present a framework for robust detection

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::abf29fa80f4cf9a0532a5f1f6bacefe8
https://doi.org/10.1145/2420950.2420987

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