Confidentiality-Preserving Collaborative Bayesian Networks

Effective large-scale process optimization in manufacturing industries requires close cooperation between different parties of human experts who encode their knowledge of related domains as Bayesian network models. For example, parties in the steel industry must collaboratively use their Bayesian networks on process parameters at the maker,...

Secure multi-party computation for supply chain collaboration

Despite evidence that collaborating in the supply chain can reduce inefficiency and result in mutual gain, parties do not wish to collaborate if they have to share their private proprietary information. The main reason for their privacy concern is that the party does not want to lose their competitive advantage by giving away company secrets....

Mitigating Inference Attacks in Collaborative Credit Card Fraud Detection using Secure Multi-Party Selection

The convenient service offered by credit cards and the technological advances in e-commerce have caused the number of online payment transactions to increase daily. With this rising number, the opportunity for fraudsters to obtain cardholder details via online credit card fraud has also increased. As a result, according to the European Central...