Security and Communication Networks / 2019 / Article / Fig 4

Research Article

Detecting Shilling Attacks with Automatic Features from Multiple Views

Figure 4

Precision of eight methods with six types of attacks at various filler sizes across various attack sizes on the Netflix dataset.

(a) 3% filler size
(b) 5% filler size

We are committed to sharing findings related to COVID-19 as quickly and safely as possible. Any author submitting a COVID-19 paper should notify us at to ensure their research is fast-tracked and made available on a preprint server as soon as possible. We will be providing unlimited waivers of publication charges for accepted articles related to COVID-19. Sign up here as a reviewer to help fast-track new submissions.