Data-Driven Optimization Based Primary Users’ Operational Privacy Preservation
نویسندگان
چکیده
منابع مشابه
A novel method for detecting structural damage based on data-driven and similarity-based techniques under environmental and operational changes
The applications of time series modeling and statistical similarity methods to structural health monitoring (SHM) provide promising and capable approaches to structural damage detection. The main aim of this article is to propose an efficient univariate similarity method named as Kullback similarity (KS) for identifying the location of damage and estimating the level of damage severity. An impr...
متن کاملPrivacy Preservation through Data Generation
Many databases will or can not be disclosed without strong guarantees that no sensitive information can be extracted. To address this concern several data perturbation techniques have been proposed. However, it has been shown that either sensitive information can still be extracted from the perturbed data with little prior knowledge, or that many patterns are lost. In this paper we show that ge...
متن کاملPrivacy Preservation in Distributed Subgradient Optimization Algorithms
In this paper, some privacy-preserving features for distributed subgradient optimization algorithms are considered. Most of the existing distributed algorithms focus mainly on the algorithm design and convergence analysis, but not the protection of agents' privacy. Privacy is becoming an increasingly important issue in applications involving sensitive information. In this paper, we first show t...
متن کاملPrivacy Preservation Decision Tree Based On Data Set Complementation
Privacy preservation in data mining has been a popular and an important research area for more than a decade due to its vast spectrum of applications. A new class of data mining method called privacy preserving data mining algorithm has been developed. The aim of this algorithm is to protect the sensitive information in data from the large amount of data set. The privacy preservation of data se...
متن کاملData-Driven Privacy Indicators
Third party applications work on top of existing platforms that host users’ data. Although these apps access this data to provide users with specific services, they can also use it for monetization or profiling purposes. In practice, there is a significant gap between users’ privacy expectations and the actual access levels of 3rd party apps, which are often over-privileged. Due to weaknesses i...
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: IEEE Transactions on Cognitive Communications and Networking
سال: 2018
ISSN: 2332-7731
DOI: 10.1109/tccn.2018.2837876