@conference{p4t2016,
  title = {Privacy-Preserving Abuse Detection in Future Decentralised Online Social
        Networks}, 
  author = {{\'A}lvaro Garc{\'\i}a-Recuero and Jeffrey Burdges and Christian Grothoff}, 
  booktitle = {Data Privacy Management (DPM)}, 
  organization = {Springer}, 
  year = {2016}, 
  month = {September}, 
  address = {Heraklion, Greece}, 
  publisher = {Springer}, 
  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}, 
  www_section = {abuse, GNUnet, Privacy preserving, reputation, Social networking}, 
  www_pdf_url = {https://git.gnunet.org/bibliography.git/plain/docs/p4t.pdf}, 
  www_tags = {selected}, 
  url = {https://bibliography.gnunet.org}, 
}