Privacy Preservation in Data Mining Using Elliptical Curve Cryptography
نویسندگان
چکیده
There are many distributed and centralized data mining techniques often used for various applications. Privacy and security issues of these techniques are recently investigated with a conclusion that they reveal information or data to each other clients involved to find global valid results. But because of privacy issues, involving clients do not want to share such type of data. Recently many cryptography algorithms have been found to address privacy problems in distributed and centralized data mining. In this thesis, we propose an elliptic curve cryptography based algorithm to mine privacy-preserving association rules on horizontally partitioned data. Elliptic Curve Integration Encryption Scheme is used for security of data and Elliptic Curve Digital Signature Algorithm for authentication. Moreover, we have also considered unsecured communication channels in distributed environment. Proposed algorithm provides privacy and security against involving clients and other clients (adversaries) who can reveal information by reading unsecured channel between involving clients. Finally, we analyse the privacy and security provided by proposed algorithm.
منابع مشابه
A Novel Framework using Elliptic Curve Cryptography for Extremely Secure Transmission in Distributed Privacy Preserving Data Mining
Privacy Preserving Data Mining is a method which ensures privacy of individual information during mining. Most important task involves retrieving information from multiple data bases which is distributed. The data once in the data warehouse can be used by mining algorithms to retrieve confidential information. The proposed framework has two major tasks, secure transmission and privacy of confid...
متن کاملA Survey of Cryptographic and Non-cryptographic Techniques for Privacy Preservation
Cryptography is to become familiar with the requirement of large, complex, information rich data sets for it’s privacy preservation. The privacy preserving data mining has been generated; to go through the concept of privacy in data mining is hard. Several algorithms and approaches are being generated theoretically, but practically it is hard. Privacy in data mining can be achieved through seve...
متن کاملPrivacy-Preserving Distributed Data Mining Techniques: A Survey
In various distributed data mining settings, leakage of the real data is not adequate because of privacy issues. To overcome this problem, numerous privacy-preserving distributed data mining practices have been suggested such as protect privacy of their data by perturbing it with a randomization algorithm and using cryptographic techniques. In this paper, we review and provide extensive survey ...
متن کاملA review on Privacy Preservation and Collaborative Data Mining
Privacy preservation is major issue in current data transmission over internet and cloud network. For the integrity and security of data various methods are used such as cryptography, data transformation, Steganography, watermarking and many more method. In consequence of all these method some data mining technique is used. The data mining technique provide Varity of algorithm for privacy prese...
متن کاملPrivacy-preserving data mining in homogeneous collaborative clustering
Privacy concern has become an important issue in data mining. In this paper, a novel algorithm for privacy preserving in distributed environment using data clustering algorithm has been proposed. As demonstrated, the data is locally clustered and the encrypted aggregated information is transferred to the master site. This aggregated information consists of centroids of clusters along with their...
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:
دوره شماره
صفحات -
تاریخ انتشار 2014