COBRA: Context-Aware Bernoulli Neural Networks for Reputation Assessment

AAAI 2020 pp. 7317-7324

doi:10.1609/AAAI.V34I05.6225 /aaai/2020/zeynalvand2020aaai-cobra/

Abstract

Trust and reputation management (TRM) plays an increasingly important role in large-scale online environments such as multi-agent systems (MAS) and the Internet of Things (IoT). One main objective of TRM is to achieve accurate trust assessment of entities such as agents or IoT service providers. However, this encounters an accuracy-privacy dilemma as we identify in this paper, and we propose a framework called Context-aware Bernoulli Neural Network based

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Text

Zeynalvand et al. "COBRA: Context-Aware Bernoulli Neural Networks for Reputation Assessment." AAAI Conference on Artificial Intelligence, 2020. doi:10.1609/AAAI.V34I05.6225

Markdown

[Zeynalvand et al. "COBRA: Context-Aware Bernoulli Neural Networks for Reputation Assessment." AAAI Conference on Artificial Intelligence, 2020.](https://mlanthology.org/aaai/2020/zeynalvand2020aaai-cobra/) doi:10.1609/AAAI.V34I05.6225

BibTeX

@inproceedings{zeynalvand2020aaai-cobra,
  title     = {{COBRA: Context-Aware Bernoulli Neural Networks for Reputation Assessment}},
  author    = {Zeynalvand, Leonid and Luo, Tie and Zhang, Jie},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2020},
  pages     = {7317-7324},
  doi       = {10.1609/AAAI.V34I05.6225},
  url       = {https://mlanthology.org/aaai/2020/zeynalvand2020aaai-cobra/}
}