Robust machine learning algorithms and systems for detection and mitigation of adversarial attacks and anomalies : proceedings of a workshop /
Casola, Linda Clare, 1982-
Robust machine learning algorithms and systems for detection and mitigation of adversarial attacks and anomalies : proceedings of a workshop / Linda Casola and Dionna Ali, rapporteurs ; Intelligence Community Studies Board ; Computer Science and Telecommunications Board, Division on Engineering and Physical Sciences, the National Academies of Sciences, Engineering, Medicine. - Washington, DC : the National Academies Press, (c)2019.. - 1 online resource (xii, 69 pages) : color illustrations
Includes bibliographies and index.
Introduction -- Plenary session -- Adversarial attacks -- Detection and mitigation of adversarial attacks and anomalies -- Enablers of machine learning algorithms and systems -- Recent trends i machine learning, parts 1 and 2 -- Plenary session -- Recent trends in machine learning, part 3 -- Machine learning systems --References -- Appendixes
"The Intelligence Community Studies Board (ICSB) of the National Academies of Sciences, Engineering, and Medicine convened a workshop on December 11-12, 2018, in Berkeley, California, to discuss robust machine learning algorithms and systems for the detection and mitigation of adversarial attacks and anomalies. This publication summarizes the presentations and discussions from the workshop"--Publisher's description
9780309496124
Machine learning--Congresses.
Computer algorithms--Congresses.
Cyberterrorism--Prevention--Congresses.
Machine learning.
Computer security.
Computer networks--Security measures.
Electronic Books.
HV6773 / .R638 2019 Q325
Robust machine learning algorithms and systems for detection and mitigation of adversarial attacks and anomalies : proceedings of a workshop / Linda Casola and Dionna Ali, rapporteurs ; Intelligence Community Studies Board ; Computer Science and Telecommunications Board, Division on Engineering and Physical Sciences, the National Academies of Sciences, Engineering, Medicine. - Washington, DC : the National Academies Press, (c)2019.. - 1 online resource (xii, 69 pages) : color illustrations
Includes bibliographies and index.
Introduction -- Plenary session -- Adversarial attacks -- Detection and mitigation of adversarial attacks and anomalies -- Enablers of machine learning algorithms and systems -- Recent trends i machine learning, parts 1 and 2 -- Plenary session -- Recent trends in machine learning, part 3 -- Machine learning systems --References -- Appendixes
"The Intelligence Community Studies Board (ICSB) of the National Academies of Sciences, Engineering, and Medicine convened a workshop on December 11-12, 2018, in Berkeley, California, to discuss robust machine learning algorithms and systems for the detection and mitigation of adversarial attacks and anomalies. This publication summarizes the presentations and discussions from the workshop"--Publisher's description
9780309496124
Machine learning--Congresses.
Computer algorithms--Congresses.
Cyberterrorism--Prevention--Congresses.
Machine learning.
Computer security.
Computer networks--Security measures.
Electronic Books.
HV6773 / .R638 2019 Q325