ICASSP 2017accepted0 citations
A novel iterative online rating attack based on market self-exciting property
Abstract
The prosperity of online rating system makes it an important place for malicious vendors to mislead public's online decisions, whereas the security related studies are lagging behind. In this work, we adopt a quantile regression model to investigate influential factors on online user choices and reveal the “self-exciting” property of online market. Inspired by these findings, we propose a novel iterative rating attack and validate its advantage through experiments.
BibTeX
@inproceedings{icassp2017_anoveliterativeo,
title = {A novel iterative online rating attack based on market self-exciting property},
author = {Yuhong Liu and Wenqi Zhou},
booktitle = {ICASSP 2017},
year = {2017}
}