Fraud Prevention in Online Digital Advertising

• Κύριοι συγγραφείς: Zhu, Xingquan (Συγγραφέας), Tao, Haicheng (Συγγραφέας), Wu, Zhiang (Συγγραφέας), Cao, Jie (Συγγραφέας), Kalish, Kristopher (Συγγραφέας), Kayne, Jeremy (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2017.
• Σειρά: SpringerBriefs in Computer Science,
• Θέματα: Computer science.; Computer communication systems.; Computer security.; Computer Science.; Systems and Data Security.; Information Systems Applications (incl. Internet).; Computer Communication Networks.
• Φυσική περιγραφή: XIV, 54 p. 87 illus., 15 illus. in color. online resource.
• ISBN: 9783319567938
• ISSN: 2191-5768

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.