Privacy-Preserving Multi-Party Directory Services
نویسندگان
چکیده
منابع مشابه
Towards Privacy-Preserving Multi-party Bartering
Both B2B bartering as well as bartering between individuals is increasingly facilitated through online platforms. However, typically these platforms lack automation and tend to neglect the privacy of their users by leaking crucial information about trades. It is in this context that we devise the first privacypreserving protocol for automatically determining an actual trade between multiple par...
متن کاملThird Party Privacy Preserving Protocol for Secure Web Services
Web services is become major issue in distributed data mining. In the literature we can found a number of proposals of privacy preserving which can be divided into two major categories that is trusted third party and multiparty based privacy protocols. In case of the trusted third party privacy protocol models the conventional asymmetric cryptographic based techniques or algorithms will be used...
متن کاملCloudMine: Multi-Party Privacy-Preserving Data Analytics Service
An increasing number of businesses are replacing their data storage and computation infrastructure with cloud services. Likewise, there is an increased emphasis on performing analytics based on multiple datasets obtained from different data sources. While ensuring security of data and computation outsourced to a third party cloud is in itself challenging, supporting analytics using data distrib...
متن کاملPrivacy Preserving k-Means Clustering in Multi-Party Environment
Extracting meaningful and valuable knowledge from databases is often done by various data mining algorithms. Nowadays, databases are distributed among two or more parties because of different reasons such as physical and geographical restrictions and the most important issue is privacy. Related data is normally maintained by more than one organization, each of which wants to keep its individual...
متن کاملPrivacy Preserving PageRank Algorithm By Using Secure Multi-Party Computation
In this work, we study the problem of privacy preserving computation on PageRank algorithm. The idea is to enforce the secure multi party computation of the algorithm iteratively using homomorphic encryption based on Paillier scheme. In the proposed PageRank computation, a user encrypt its own graph data using asymmetric encryption method, sends the data set into different parties in a privacy-...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: ICST Transactions on Security and Safety
سال: 2019
ISSN: 2032-9393
DOI: 10.4108/eai.29-7-2019.159627