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Fraud Prevention in Online Digital Advertising / by Xingquan Zhu, Haicheng Tao, Zhiang Wu, Jie Cao, Kristopher Kalish, Jeremy Kayne.
- Format:
- Book
- Author/Creator:
- Zhu, Xingquan, 1973- author.
- Tao, Haicheng, author.
- Wu, Zhiang, author.
- Cao, Jie (Ph. D. in computer science), author.
- Kalish, Kristopher, author.
- Kayne, Jeremy, author.
- Series:
- Computer Science (Springer-11645)
- SpringerBriefs in computer science 2191-5768
- SpringerBriefs in Computer Science, 2191-5768
- Language:
- English
- Subjects (All):
- Computer security.
- Application software.
- Computer networks.
- Systems and Data Security.
- Information Systems Applications (incl. Internet).
- Computer Communication Networks.
- Local Subjects:
- Systems and Data Security.
- Information Systems Applications (incl. Internet).
- Computer Communication Networks.
- Physical Description:
- 1 online resource (XIV, 54 pages) : 87 illustrations, 15 illustrations in color.
- Edition:
- First edition 2017.
- Contained In:
- Springer eBooks
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2017.
- System Details:
- text file PDF
- Summary:
- 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.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-319-56793-8
- 9783319567938
- Access Restriction:
- Restricted for use by site license.
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