A Utility-optimized Framework for Personalized Private Histogram Estimation

  • Diploma
  • BCA
  • B.Sc
  • B.Tech/B.E.
  • M.Sc
  • MCA
  • M.Tech/M.E.
Technologies
  • .netMVC
  • PHP
  • Python
  • Django

Abstract—Recently, local differential privacy (LDP), as a strong and practical notion, has been applied to deal with privacy issues in data collection. However, existing LDP-based strategies mainly focus on utility optimization at a single privacy level while ignoring various privacy preferences of data providers and multilevel privacy demands for statistics. In this paper, we for the ?rst time propose a framework to optimize the utility of histogram estimation with these two privacy requirements. To clarify the goal of privacy protection, we personalize the traditional de?nition of LDP. We design two independent approaches to minimize the utility loss: Advanced Combination, which composes multilevel results for utility optimization, and Data Recycle with Personalized Privacy, which enlarges sample size for an estimation. We demonstrate their effectiveness on privacy and utility, respectively. Moreover, we embed these approaches within a Recycle and Combination Framework and prove that the framework stably achieves the optimal utility by quantifying its error bounds. On real-world datasets, our approaches are experimentally validated and remarkably outperform baseline methods

2 years ago


DOWNLOAD


Related Topics

Image Security using Image Encryption and Image Stitching

Abstract—With increase in digital communication, multimedia data such as digital images, videos etc. we require fast and robust security systems. To achieve high security, encryption is one of the way to protect our data from unauthorized users. In this paper, the proposed model aims to provide s...

  • Diploma
  • BCA
  • B.Sc
  • B.Tech/B.E.
  • M.Sc
  • MCA
  • M.Tech/M.E.


Technologies
  • .netMVC
  • PHP
  • Python
  • Java
  • Django
Depression Detection via Harvesting Social Media: A Multi modal Dictionary Learning Solution

Depression is a major contributor to the overall global burden of diseases. Traditionally, doctors diagnose depressed people face to face via referring to clinical depression criteria. However, more than 70% of the patients would not consult doctors at early stages of depression, which leads to f...

  • Diploma
  • BCA
  • B.Sc
  • B.Tech/B.E.
  • M.Sc
  • MCA
  • M.Tech/M.E.


Technologies
  • .netMVC
  • PHP
  • Python
  • Java
  • Django
  • Android
Detecting Stress Based on Social Interactions in Social Networks

Abstract— Psychological stress is threatening people’s health. It is non-trivial to detect stress timely for proactive care. With the popularity of social media, people are used to sharing their daily activities and interacting with friends on social media platforms, making it feasible to leverag...

  • Diploma
  • BCA
  • B.Sc
  • B.Tech/B.E.
  • M.Sc
  • MCA
  • M.Tech/M.E.


Technologies
  • .netMVC
  • PHP
  • Python
  • Java
  • Django
  • Android
DETERMINING SOIL PROPERTIES

ABSTRACT Different machine learning algorithms were as-sessed for estimating five functional soil parameters (SOC content, Calcium content, Phosphorous content, sand content, and pH value). The algorithms planned to use will include variants of linear regression and support vector regression. A...

  • Diploma
  • BCA
  • B.Sc
  • B.Tech/B.E.
  • M.Sc
  • MCA
  • M.Tech/M.E.


Technologies
  • .netMVC
  • PHP
  • Python
  • Java
  • Django
  • Android
  • BigData
VOPRec: Vector Representation Learning of Papers with Text Information and Structural Identity for Recommendation

Abstract—Finding relevant papers is a non-trivial problem for scholars due to the tremendous amount of academic information in the era of scholarly big data. Scienti?c paper recommendation systems have been developed to solve such problem by recommending relevant papers to scholars. However, prev...

  • Diploma
  • BCA
  • B.Sc
  • B.Tech/B.E.
  • M.Sc
  • MCA
  • M.Tech/M.E.


Technologies
  • .netMVC
  • PHP
  • Python
  • Java
  • Django
  • Android
  • BigData