| HAL-Inria | Publications, software ... of Inria's scientists |
Conference papers
Privacy-Preserving Abuse Detection in Future Decentralised Online Social Networks
Abstract : Future online social networks need to not only protect sensitive data of their users, but also protect them from abusive behavior coming from malicious participants in the network. We investigate the use of supervised learning techniques to detect abusive behavior and describe privacy-preserving protocols to compute the feature set required by abuse classification algorithms in a secure and privacy-preserving way. While our method is not yet fully resilient against a strong adaptive adversary, our evaluation suggests that it will be useful to detect abusive behavior with a minimal impact on privacy.
Cited literature [16 references]
https://hal.inria.fr/hal-01355951
Contributor : Álvaro García-Recuero <>
Submitted on : Thursday, September 22, 2016 - 9:08:16 PM
Last modification on : Friday, July 10, 2020 - 4:21:33 PM
Contributor : Álvaro García-Recuero <>
Submitted on : Thursday, September 22, 2016 - 9:08:16 PM
Last modification on : Friday, July 10, 2020 - 4:21:33 PM
File
p4t.pdf
Publisher files allowed on an open archive