1737416522     

Methods and data analysis for cross-cultural research / Fons J.R. van de Vijver (Tilburg University, the Netherlands; North-West University, South Africa; University of Queensland, Australia), Kwok Leung (Chinese University of Hong Kong) ; Editors: Velichko H. Fetvadjiev(University of Amsterdam), Jia He (Tilburg University), Johnny R.J. Fontaine,

Vijver, Fons J. R. van de, 1952-2019 [Verfasserin/Verfasser]

Leung, Kwok, 1958-2015 [Verfasserin/Verfasser] ; Fetvadjiev, Velichko H. [Herausgeberin/-geber] ; He, Jia [Herausgeberin/-geber] ; Fontaine, Johnny R. J. [Herausgeberin/-geber]

Second edition

Cambride ; New York ; Melbourne ; New Delhi ; Singapore : Cambridge University Press, 2021

xvii, 189 Seiten : Illustrationen, Diagramme

Englisch

Includes bibliographical references and index

Erscheint auch als: Methods and data analysis for cross-cultural research / Vijver, Fons J. R. van de (Online-Ausgabe)

978-1-107-69467-5 (paperback); 978-1-107-05779-1 (hardback)

978-1-107-41518-8 (ISBN der parallelen Ausgabe im Fernzugriff)

2020046846

OCoLC: 1260300089     

GN502

155.8/2     Ähnliche Literatur

LOC-SH: Ethnopsychology

"Malicious hackers utilize the World Wide Web to share knowledge. Analyzing the online communication and behavior of these threat actors can help reduce the risk of attacks. This book shifts attention from the defender environment to the attacker environment, offering a new security paradigm of 'proactive cyber threat intelligence' that allows defenders of computer networks to gain a better understanding of their adversaries by analyzing assets, capabilities, and interest of malicious hackers. The authors propose models, techniques, and frameworks based on threat intelligence mined from the heart of the underground cyber world: the malicious hacker communities. They provide insights into the hackers themselves and the groups they form dynamically in the act of exchanging ideas and techniques, buying or selling malware, and exploits. The book covers both methodology-a hybridization of machine learning, artificial intelligence, and social network analysis methods-and the resulting conclusions, detailing how a deep understanding of malicious hacker communities can be the key to designing better attack prediction systems"--