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"Efficient maliciously secure two-party mixed-protocol framework for da" by Yulin Wu, Xuan Wang et al.

In the artificial intelligence era, data-driven computation tasks, such as machine learning, have been playing an essential role as the decision-maker to unlock the value of big data in many fields. Moreover, the ultimate goal of pursuing accuracy and efficiency improvement to better promote the application of data-driven computation has never changed. Since the main method to improve the accuracy of these tasks (e.g., the model training of machine learning) is to increase the diversity of datasets, this requires multiple data providers to share their data. However, data providers, e.g., private companies, are reluctant to share their datasets directly, considering the privacy protection of user information and the leakage prevention of their business secrets. Therefore, how to securely and efficiently perform joint datasets based data-driven computation tasks has become the main problem. In this work, without getting the aid of any trusted-third party (e.g., the cloud server), we cons ....

Committed Oblivious Linear Evaluation , Homomorphic Commitments , Ixed Protocol , Ecure Two Party Computation ,

"Efficient Server-Aided Secure Two-Party Computation in Heterogeneous M" by Yulin Wu, Xuan Wang et al.

With the ubiquity of mobile devices and rapid development of cloud computing, mobile cloud computing (MCC) has been considered as an essential computation setting to support complicated, scalable and flexible mobile applications by overcoming the physical limitations of mobile devices with the aid of cloud. In the MCC setting, since many mobile applications (e.g., map apps) interacting with cloud server and application server need to perform computation with the private data of users, it is important to realize secure computation for MCC. In this article, we propose an efficient server-aided secure two-party computation (2PC) protocol for MCC. This is the first work that considers collusion between a malicious garbled circuit evaluator and a semi-honest server while ensuring privacy and correctness. Also, it can guarantee fairness when collusion does not exist. The security analysis shows that our protocol can securely compute any function f(x, y) against different types of adversaries ....

Garbled Circuit , Mobile Cloud Computing , Ecure Two Party Computation , Erver Aided Computation ,