We propose an efficient framework for enabling secure multi-party numerical computations in a Peer-to-Peer network. This problem arises in a range of applications such as collabo...
Danny Bickson, Danny Dolev, Genia Bezman, Benny Pi...
We present a new construction of non-committing encryption schemes. Unlike the previous constructions of Canetti et al. (STOC ’96) and of Damg˚ard and Nielsen (Crypto ’00), ou...
Seung Geol Choi, Dana Dachman-Soled, Tal Malkin, H...
Abstract. Secure multi-party computation has been considered by the cryptographic community for a number of years. Until recently it has been a purely theoretical area, with few im...
Benny Pinkas, Thomas Schneider, Nigel P. Smart, St...
Many advancements in the area of Secure Multi-Party Computation (SMC) protocols use improvements in communication complexity as a justification. We conducted an experimental stud...
Florian Kerschbaum, Daniel Dahlmeier, Axel Schr&ou...
Privacy preserving data mining has been investigated extensively. The previous works mainly fall into two categories, perturbation and randomization based approaches and secure mu...
Li Liu, Murat Kantarcioglu, Bhavani M. Thuraisingh...
We propose a modification to the framework of Universally Composable (UC) security [3]. Our new notion, involves comparing the protocol executions with an ideal execution involvin...
We show how to securely realize any multi-party functionality in a way that preserves security under an a-priori bounded number of concurrent executions, regardless of the number ...
Privacy is of growing concern in today's day and age. Protecting the privacy of health data is of paramount importance. With the rapid advancement in imaging technology, anal...