Multiparty Cloud Computation
  With the increasing popularity of the cloud, clients oursource their data to clouds in order to take advantage of unlimited virtualized storage space and the low management cost. Such trend prompts the privately oursourcing computation, called \emph{multiparty cloud computation} (\MCC): Given $k$ clients storing their data in the cloud, how can they perform the joint functionality by contributing their private data as inputs, and making use of cloud's powerful computation capability. Namely, the clients wish to oursource computation to the cloud together with their private data stored in the cloud, which naturally happens when the computation is involved with large datasets, e.g., to analyze malicious URLs. We note that the \MCC\ problem is different from widely considered concepts, e.g., secure multiparty computation and multiparty computation with server aid.   To address this problem, we introduce the notion of \emph{homomorphic threshold proxy re-encryption} schemes, which are encryption schemes that enjoy three promising properties: proxy re-encryption -- transforming encrypted data of one user to encrypted data of target user, threshold decryption -- decrypting encrypted data by combining secret key shares obtained by a set of users, and homomorphic computation -- evaluating functions on the encrypted data. To demonstrate the feasibility of the proposed approach, we present an encryption scheme which allows anyone to compute arbitrary many additions and at most one multiplications. 
Qingji Zheng and Xinwen Zhang
cs.CR