Librería: Bookmans, Tucson, AZ, Estados Unidos de America
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Librería: Corner of a Foreign Field, Tokyo, TOKYO, Japon
Original o primera edición
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Añadir al carritoSoft cover. Condición: Good. No Jacket. 1st Edition. 2018.Softcover.Good condition.Some highlighting to the text.91 pages.Ships from Japan.Usually ships in 1-2 working days.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: Books Puddle, New York, NY, Estados Unidos de America
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Añadir al carritoCondición: New. pp. 91.
Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Idioma: Inglés
Publicado por Springer-Verlag New York Inc, 2018
ISBN 10: 3319737872 ISBN 13: 9783319737874
Librería: Revaluation Books, Exeter, Reino Unido
EUR 75,38
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Añadir al carritoPaperback. Condición: Brand New. pap/psc edition. 100 pages. 9.25x6.10x0.28 inches. In Stock.
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de America
EUR 84,69
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Idioma: Inglés
Publicado por Springer International Publishing, 2018
ISBN 10: 3319737872 ISBN 13: 9783319737874
Librería: moluna, Greven, Alemania
EUR 48,74
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Idioma: Inglés
Publicado por Springer, Berlin, Springer, 2018
ISBN 10: 3319737872 ISBN 13: 9783319737874
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 55,59
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This SpringerBrief discusses how to develop intelligent systems for cyber attribution regarding cyber-attacks. Specifically, the authors review the multiple facets of the cyber attribution problem that make it difficult for 'out-of-the-box' artificial intelligence and machine learning techniques to handle. Attributing a cyber-operation through the use of multiple pieces of technical evidence (i.e., malware reverse-engineering and source tracking) and conventional intelligence sources (i.e., human or signals intelligence) is a difficult problem not only due to the effort required to obtain evidence, but the ease with which an adversary can plant false evidence. This SpringerBrief not only lays out the theoretical foundations for how to handle the unique aspects of cyber attribution - and how to update models used for this purpose - but it also describes a series of empirical results, as well as compares results of specially-designed frameworks for cyber attribution to standard machine learning approaches. Cyber attribution is not only a challenging problem, but there are also problems in performing such research, particularly in obtaining relevant data. This SpringerBrief describes how to use capture-the-flag for such research, and describes issues from organizing such data to running your own capture-the-flag specifically designed for cyber attribution. Datasets and software are also available on the companion website.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 46,22
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Añadir al carritoCondición: new. Questo è un articolo print on demand.
Idioma: Inglés
Publicado por Berlin Springer International Publishing Springer Feb 2018, 2018
ISBN 10: 3319737872 ISBN 13: 9783319737874
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 51,40
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This SpringerBrief discusses how to develop intelligent systems for cyber attribution regarding cyber-attacks. Specifically, the authors review the multiple facets of the cyber attribution problem that make it difficult for 'out-of-the-box' artificial intelligence and machine learning techniques to handle. Attributing a cyber-operation through the use of multiple pieces of technical evidence (i.e., malware reverse-engineering and source tracking) and conventional intelligence sources (i.e., human or signals intelligence) is a difficult problem not only due to the effort required to obtain evidence, but the ease with which an adversary can plant false evidence. This SpringerBrief not only lays out the theoretical foundations for how to handle the unique aspects of cyber attribution - and how to update models used for this purpose - but it also describes a series of empirical results, as well as compares results of specially-designed frameworks for cyber attribution to standard machine learning approaches. Cyber attribution is not only a challenging problem, but there are also problems in performing such research, particularly in obtaining relevant data. This SpringerBrief describes how to use capture-the-flag for such research, and describes issues from organizing such data to running your own capture-the-flag specifically designed for cyber attribution. Datasets and software are also available on the companion website. 91 pp. Englisch.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 75,12
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Añadir al carritoCondición: New. Print on Demand pp. 91.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 76,23
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Añadir al carritoCondición: New. PRINT ON DEMAND pp. 91.