Semi-trusted Collaborative Framework for Multi-party Computation
نویسندگان
چکیده
Data sharing is an essential process for collaborative works particularly in the banking, finance and healthcare industries. These industries require many collaborative works with their internal and external parties such as branches, clients, and service providers. When data are shared among collaborators, security and privacy concerns becoming crucial issues and cannot be avoided. Privacy is an important issue that is frequently discussed during the development of collaborative systems. It is closely related with the security issues because each of them can affect the other. The tradeoff between privacy and security is an interesting topic that we are going to address in this paper. In view of the practical problems in the existing approaches, we propose a collaborative framework which can be used to facilitate concurrent operations, single point failure problem, and overcome constraints for two-party computation. Two secure computation protocols will be discussed to demonstrate our collaborative framework.
منابع مشابه
Changing Neighbors k Secure Sum Protocol for Secure Multi Party Computation
Secure sum computation of private data inputs is an important component of Secure Multi-party Computation (SMC).In this paper we provide a protocol to compute the sum of individual data inputs with zero probability of data leakage. In our proposed protocol we break input of each party into number of segments and change the arrangement of the parties such that in each round of the computation th...
متن کاملPrivacy Aware Recommender Service using Multi-agent Middleware- an IPTV Network Scenario
IPTV service providers are starting to realize the significant value of recommender services in attracting and satisfying customers as they offer added values e.g. by delivering suitable personalized contents according to customers personal interests in a seamless way, increase content sales and gain competitive advantage over other competitors. However the current implementations of recommende...
متن کاملEfficient Secure Two-Party Computation with Untrusted Hardware Tokens (Full Version)
We consider Secure Function Evaluation (SFE) in the client-server setting where the server issues a secure token to the client. The token is not trusted by the client and is not a trusted third party. We show how to take advantage of the token to drastically reduce the communication complexity of SFE and computation load of the server. Our main contribution is the detailed consideration of desi...
متن کاملBehavioral Identification of Trusted Third Party in Secure Multiparty Computing Protocol
We present a solution for identification and reduction of malicious conduct by Trusted Third parties (TTPs) in Secure Multiparty Computing Protocol. This paper also proposes a secured protocol for computation and defines encryption to be performed before sending inputs for computation. Our protocol uses eenvelopes for sharing keys between parties and TTPs. This key sharing is done on the basis ...
متن کاملPrivate Personal Information Verification
Physical document verification is a necessary task in the process of reviewing applications for a variety of services, such as loans, insurance, and mortgages. This process consumes a large amount of time, money, and human resources, which leads to limited business throughput. Furthermore, physical document verification poses a critical risk to clients’ personal information, as they are require...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- TIIS
دوره 4 شماره
صفحات -
تاریخ انتشار 2010