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Table of contents (7 chapters)
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Front Matter
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Back Matter
About this book
The authors systematically review methods of online digital advertising (ad) fraud and the techniques to prevent and defeat such fraud in this brief. The authors categorize ad fraud into three major categories, including (1) placement fraud, (2) traffic fraud, and (3) action fraud. It summarizes major features of each type of fraud, and also outlines measures and resources to detect each type of fraud. This brief provides a comprehensive guideline to help researchers understand the state-of-the-art in ad fraud detection. It also serves as a technical reference for industry to design new techniques and solutions to win the battle against fraud.
Authors and Affiliations
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Dept. of Computer & Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, USA
Xingquan Zhu, Haicheng Tao
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College of Information Engineering, Nanjing University of Finance and Economics, Nanjing, China
Zhiang Wu, Jie Cao
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Bidtellect, Inc., Delray Beach, USA
Kristopher Kalish, Jeremy Kayne
Bibliographic Information
Book Title: Fraud Prevention in Online Digital Advertising
Authors: Xingquan Zhu, Haicheng Tao, Zhiang Wu, Jie Cao, Kristopher Kalish, Jeremy Kayne
Series Title: SpringerBriefs in Computer Science
DOI: https://doi.org/10.1007/978-3-319-56793-8
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Author(s) 2017
Softcover ISBN: 978-3-319-56792-1Published: 23 June 2017
eBook ISBN: 978-3-319-56793-8Published: 08 June 2017
Series ISSN: 2191-5768
Series E-ISSN: 2191-5776
Edition Number: 1
Number of Pages: XIV, 54
Number of Illustrations: 72 b/w illustrations, 15 illustrations in colour
Topics: Systems and Data Security, Information Systems Applications (incl. Internet), Computer Communication Networks