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001437966 001__ 1437966
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001437966 0247_ $$a10.1007/978-981-33-6726-5$$2doi
001437966 035__ $$aSP(OCoLC)1259623724
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001437966 049__ $$aISEA
001437966 050_4 $$aQ325.5
001437966 08204 $$a006.3/1$$223
001437966 24500 $$aCyber security meets machine learning /$$cXiaofeng Chen, Willy Susilo, Elisa Bertino, editors.
001437966 260__ $$aSingapore :$$bSpringer,$$c2021.
001437966 300__ $$a1 online resource
001437966 336__ $$atext$$btxt$$2rdacontent
001437966 337__ $$acomputer$$bc$$2rdamedia
001437966 338__ $$aonline resource$$bcr$$2rdacarrier
001437966 347__ $$atext file
001437966 347__ $$bPDF
001437966 5050_ $$aChapter 1. IoT Attacks and Malware -- Chapter 2. Machine Learning-based Online Source Identification for Image Forensics -- Chapter 3. Reinforcement Learning Based Communication Security for Unmanned Aerial Vehicles -- Chapter 4. Visual Analysis of Adversarial Examples in Machine Learning -- Chapter 5. Adversarial Attacks against Deep Learning-based Speech Recognition Systems -- Chapter 6. Secure Outsourced Machine Learning -- Chapter 7. A Survey on Secure Outsourced Deep Learning.
001437966 506__ $$aAccess limited to authorized users.
001437966 520__ $$aMachine learning boosts the capabilities of security solutions in the modern cyber environment. However, there are also security concerns associated with machine learning models and approaches: the vulnerability of machine learning models to adversarial attacks is a fatal flaw in the artificial intelligence technologies, and the privacy of the data used in the training and testing periods is also causing increasing concern among users. This book reviews the latest research in the area, including effective applications of machine learning methods in cybersecurity solutions and the urgent security risks related to the machine learning models. The book is divided into three parts: Cyber Security Based on Machine Learning; Security in Machine Learning Methods and Systems; and Security and Privacy in Outsourced Machine Learning. Addressing hot topics in cybersecurity and written by leading researchers in the field, the book features self-contained chapters to allow readers to select topics that are relevant to their needs. It is a valuable resource for all those interested in cybersecurity and robust machine learning, including graduate students and academic and industrial researchers, wanting to gain insights into cutting-edge research topics, as well as related tools and inspiring innovations.
001437966 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed July 14, 2021).
001437966 650_0 $$aMachine learning$$xSecurity measures.
001437966 650_0 $$aComputer security.
001437966 650_6 $$aApprentissage automatique$$xSécurité$$xMesures.
001437966 650_6 $$aSécurité informatique.
001437966 655_0 $$aElectronic books.
001437966 7001_ $$aChen, Xiaofeng,$$d1976-$$eeditor.
001437966 7001_ $$aSusilo, Willy,$$eeditor.
001437966 7001_ $$aBertino, Elisa,$$eeditor.
001437966 77608 $$iPrint version:$$z9813367253$$z9789813367258$$w(OCoLC)1227382659
001437966 852__ $$bebk
001437966 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-33-6726-5$$zOnline Access$$91397441.1
001437966 909CO $$ooai:library.usi.edu:1437966$$pGLOBAL_SET
001437966 980__ $$aBIB
001437966 980__ $$aEBOOK
001437966 982__ $$aEbook
001437966 983__ $$aOnline
001437966 994__ $$a92$$bISE