Paper Info
Title
Attack under Disguise: An Intelligent Data Poisoning Attack Mechanism in Crowdsourcing.
Abstract
As an effective way to solicit useful information from the crowd, crowdsourcing has emerged as a popular paradigm to solve challenging tasks. However, the data provided by the participating workers are not always trustworthy. In real world, there may exist malicious workers in crowdsourcing systems who conduct the data poisoning attacks for the purpose of sabotage or financial rewards. Although data aggregation methods such as majority voting are conducted on workers» labels in order to improve data quality, they are vulnerable to such attacks as they treat all the workers equally. In order to capture the variety in the reliability of workers, the Dawid-Skene model, a sophisticated data aggregation method, has been widely adopted in practice. By conducting maximum likelihood estimation (MLE) using the expectation maximization (EM) algorithm, the Dawid-Skene model can jointly estimate each worker»s reliability and conduct weighted aggregation, and thus can tolerate the data poisoning attacks to some degree. However, the Dawid-Skene model still has weakness. In this paper, we study the data poisoning attacks against such crowdsourcing systems with the Dawid-Skene model empowered. We design an intelligent attack mechanism, based on which the attacker can not only achieve maximum attack utility but also disguise the attacking behaviors. Extensive experiments based on real-world crowdsourcing datasets are conducted to verify the desirable properties of the proposed mechanism.
Year
DOI
Venue
2018
10.1145/3178876.3186032
WWW '18: The Web Conference 2018 Lyon France April, 2018
Keywords
Field
DocType
Crowdsourcing, data poisoning, expectation maximization
Data quality,Expectation–maximization algorithm,Trustworthiness,Computer science,Crowdsourcing,Maximum likelihood,Artificial intelligence,Majority rule,Data aggregator,Machine learning
Conference
ISBN
Citations 
PageRank 
978-1-4503-5639-8
6
0.42
References 
Authors
42
6
Name
Order
Citations
PageRank
Chenglin Miao1273.17
Qi Li250720.38
lu su3111866.61
Mengdi Huai42910.02
Wenjun Jiang535624.25
Jing Gao62723131.05