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Cover: 9783658404413 | Machine Learning under Malware Attack | Raphael Labaca-Castro | Buch
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Machine Learning under Malware Attack
Taschenbuch von Raphael Labaca-Castro
Sprache: Englisch

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Beschreibung
Machine learning has become key in supporting decision-making processes across a wide array of applications, ranging from autonomous vehicles to malware detection. However, while highly accurate, these algorithms have been shown to exhibit vulnerabilities, in which they could be deceived to return preferred predictions. Therefore, carefully crafted adversarial objects may impact the trust of machine learning systems compromising the reliability of their predictions, irrespective of the field in which they are deployed. The goal of this book is to improve the understanding of adversarial attacks, particularly in the malware context, and leverage the knowledge to explore defenses against adaptive adversaries. Furthermore, to study systemic weaknesses that can improve the resilience of machine learning models.
Machine learning has become key in supporting decision-making processes across a wide array of applications, ranging from autonomous vehicles to malware detection. However, while highly accurate, these algorithms have been shown to exhibit vulnerabilities, in which they could be deceived to return preferred predictions. Therefore, carefully crafted adversarial objects may impact the trust of machine learning systems compromising the reliability of their predictions, irrespective of the field in which they are deployed. The goal of this book is to improve the understanding of adversarial attacks, particularly in the malware context, and leverage the knowledge to explore defenses against adaptive adversaries. Furthermore, to study systemic weaknesses that can improve the resilience of machine learning models.
Über den Autor
Raphael Labaca-Castro is a computer scientist whose primary interests lie in the nexus between Machine Learning and Computer Security. He holds a PhD in Adversarial Machine Learning and currently leads an ML team in the quantum security field.
Inhaltsverzeichnis
The Beginnings of Adversarial ML.- Framework for Adversarial Malware Evaluation.- Problem-Space Attacks.- Feature-Space Attacks.- Closing Remarks.
Details
Erscheinungsjahr: 2023
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: xxxiv
116 S.
8 s/w Illustr.
11 farbige Illustr.
116 p. 19 illus.
11 illus. in color. Textbook for German language market.
ISBN-13: 9783658404413
ISBN-10: 3658404418
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Labaca-Castro, Raphael
Auflage: 1st ed. 2023
Hersteller: Springer Fachmedien Wiesbaden
Springer Fachmedien Wiesbaden GmbH
Maße: 210 x 148 x 9 mm
Von/Mit: Raphael Labaca-Castro
Erscheinungsdatum: 01.02.2023
Gewicht: 0,207 kg
Artikel-ID: 126044626
Über den Autor
Raphael Labaca-Castro is a computer scientist whose primary interests lie in the nexus between Machine Learning and Computer Security. He holds a PhD in Adversarial Machine Learning and currently leads an ML team in the quantum security field.
Inhaltsverzeichnis
The Beginnings of Adversarial ML.- Framework for Adversarial Malware Evaluation.- Problem-Space Attacks.- Feature-Space Attacks.- Closing Remarks.
Details
Erscheinungsjahr: 2023
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: xxxiv
116 S.
8 s/w Illustr.
11 farbige Illustr.
116 p. 19 illus.
11 illus. in color. Textbook for German language market.
ISBN-13: 9783658404413
ISBN-10: 3658404418
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Labaca-Castro, Raphael
Auflage: 1st ed. 2023
Hersteller: Springer Fachmedien Wiesbaden
Springer Fachmedien Wiesbaden GmbH
Maße: 210 x 148 x 9 mm
Von/Mit: Raphael Labaca-Castro
Erscheinungsdatum: 01.02.2023
Gewicht: 0,207 kg
Artikel-ID: 126044626
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