Personalized Privacy-Preserving Granular Computing Model
نویسندگان
چکیده
As a new computing model, Granular computing provides a new efficient way for solving complicated problems, massive data mining, and fuzzy information processing. Privacy is becoming an increasingly important issue in many data mining applications. In this paper, we combined the existing model of granular computing with personalized privacy-preserving demand, and proposed a new granular computing model, which is called personalized privacy-preserving granular computing model. We also proofed that the new model can make individual privacy preserving more rational, improve the accuracy of the individual privacy preserving.
منابع مشابه
A centralized privacy-preserving framework for online social networks
There are some critical privacy concerns in the current online social networks (OSNs). Users' information is disclosed to different entities that they were not supposed to access. Furthermore, the notion of friendship is inadequate in OSNs since the degree of social relationships between users dynamically changes over the time. Additionally, users may define similar privacy settings for their f...
متن کاملZero-knowledge Test of Vector Equivalence and Granulation of User Data with Privacy
This paper introduces a new framework for privacy preserving computation to the granular computing community. The framework is called P4P (Peers for Privacy) and features a unique architecture and practical protocols for user data validation and vector addition-based computation. It turned out that many non-trivial and non-linear computations can be done using an iterative algorithm with vector...
متن کاملPrivacy Preserving Collaborative Filtering using Biclustering in Ubiquitous Computing Environments
Privacy concerns are a major hurdle in the success of personalized services in ubiquitous computing environments. Personalized recommendations are usually served using Collaborative Filtering techniques. In this paper, we propose a framework for privacy preserving collaborative filtering in ubiquitous computing environments. The proposed framework is based on a biclustering algorithm which empl...
متن کاملPrivacy Preserving in Personalized Mobile Marketing
With the popularity of smart portable devices and advances in wireless technologies, mobile marketing increases quickly. Among various methods, short message is regarded as the most efficient mode. While mobile advertising enhances communication with consumers, the messages without a required permission cause privacy violations. So, how to simultaneously supporting personalization and privacy p...
متن کاملPersonalized Privacy-Preserving Social Recommendation
Privacy leakage is an important issue for social recommendation. Existing privacy preserving social recommendation approaches usually allow the recommender to fully control users’ information. This may be problematic since the recommender itself may be untrusted, leading to serious privacy leakage. Besides, building social relationships requires sharing interests as well as other private inform...
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 2009