Oblivious transfer is a fundamental building block for multiparty computation protocols. In
this paper, we present a generally realizable framework for fully-simulatable $ t $-out-of-$ n …

Privacy is crucial in many applications of machine learning. Legal, ethical and societal
issues restrict the sharing of sensitive data making it difficult to learn from datasets that are …

In today's era, with the rapid development of big data technology and the continuous
increase in data volume, large amounts of data are constantly collected by different …

Mobility data is the cornerstone of crucial applications, including traffic monitoring,
crowdsourcing, and social networks. However, research shows that publishing accurate …

Context: Data Mining (DM) method has been evolving year by year and as of today there is
also the enhancement of DM technique that can be run several times faster than the …

Given the sheer size of the consumer credit market and the huge number of consumer credit
users, credit risk modeling, or predicting delinquent (or default) probabilities of borrowers to …

With the development of cloud computing technology, data can be outsourced to the cloud
and conveniently shared among users. However, in many circumstances, users may have …

随着云计算技术的发展, 数据可外包给云, 方便用户共享. 然而, 用户常常担心其数据在云端的
可靠性和完整性. 因此, 在云端提供安全的数据共享服务至关重要. 本文将门限秘密共享技术和 …

Oblivious transfer (OT) is a fundamental primitive in cryptography. Halevi-Kalai OT (Halevi,
S. and Y. Kalai (2012), Journal of Cryptology 25 (1)), which is based on smooth projective …

Considering the untrusted server, differential privacy and local differential privacy has been
used for privacypreserving in data aggregation. Through our analysis, differential privacy …