UMBRELLA: user demand privacy preserving framework based on association rules and differential privacy in social networks

Intl J Robust & Nonlinear

Liu

2022

This article investigates resilient distributed online estimation (DOE) in unreliable directed networks with differential privacy requirements. In the network considered, some agents are subject to Byzantine attacks and thus could send arbitrary incorrect messages to their neighbors. The remaining agents aim to collaboratively estimate the value of an unknown vector parameter while protecting their private data. In this article, by adding private noises to mask the estimate, a stochastic approximation-type resilient differentially private DOE algorithm is proposed to protect the privacy of sensitive information. A time-varying step size is introduced to attenuate the divergence caused by the private noise, and furthermore, guarantees the convergence of the algorithm.When the directed graph is (2F+1)-robust, the algorithm is shown to be both mean square and almost sure convergence in the sense of 𝜖-differential privacy. A simulation example is given to verify the effectiveness and superiority of the algorithm.

Section: Introductionmentioning

confidence: 99%

Differentially private resilient distributed cooperative online estimation over digraphs

Wang

Intl J Robust & Nonlinear

Liu

2022

“…Smart city [1], [2], [3] is an agglomeration of urban society that employs intelligent technologies to improve people's life, work and communication. A key aspect of smart cities is mobile online social networks (mOSNs) [4], [5], [6], [7], [8] that are popular mainstream platforms for information and content sharing among people. Location sharing is an important component of mOSNs and also has attracted much attention recently.…”

Section: Introductionmentioning

confidence: 99%

Location-sharing Protocol for Privacy Protection in Mobile Online Social Networks

Ruan

2021

Preprint

Location-based services are becoming more and more popular in mobile online social networks(mOSNs) for smart cities, but users' privacy also has aroused wide concern, such as locations, friend sets and other private information. At present, many protocols have been proposed, but these protocols are inefficient and ignore some security risks. In the paper, we present a new location sharing protocol, which solves these two issues by using symmetric/asymmetric encryption properly. We adopt the following methods to reduce the communication and computation costs: only setting up one location server; connecting social network server and location server directly instead of through cellular towers; avoiding broadcast encryption. We introduce dummy identities to protect users' identity privacy, and prevent locationserver from inferring users' activity tracks by updating dummy identities in time. The details of security and performance analysis with the related protocols show that our protocol enjoys two advantages: (1) it's more efficient than the related protocols, which greatly reduces the computation and communication costs; (2) it satisfies all security goals, however, most previous protocols only meet some security goals.

“…Smart city [1], [2], [3] is an agglomeration of urban society that employs intelligent technologies to improve how people live, work, commute and share information. A key aspect of a smart city is mobile online social networks (mOSNs) [4], [5], [6], [7], [8] that are popular mainstream platforms for information and content sharing among people. Location sharing is an important component of mOSNs and also has attracted much attention recently.…”

Section: Introductionmentioning

confidence: 99%

“…A key aspect of a smart city is mobile online social networks (mOSNs) [4], [5], [6], [7], [8] that are popular mainstream platforms for information and content sharing among people. Location sharing is an important component of mOSNs and also has attracted much attention recently.…”

Section: Introductionmentioning

confidence: 99%

Location-Sharing Protocol for Privacy Protection in Mobile Online Social Networks

Ruan

2020

Preprint

Location-based services are becoming more and more popular in mobile online so-cial networks(mOSNs) for smart cities, but users' privacy also has aroused wide concern, such as locations, friend sets and other private information. At present, many location sharing protocols in mOSNs have been proposed, but these pro-tocols are inecient and ignore some security risks. In this paper, we propose a new location sharing protocol, which solves these two issues by using symmetric encryption and asymmetric encryption properly. We adopt the following methods to reduce the communication and computation costs: only setting up one loca-tion server; connecting social network server and location server directly instead of through celluar towers; avoiding broadcast encryption. We introduce dummy iden-tities to protect users' identity privacy, and prevent location server from inferring users' activity tracks by updating dummy identities in time. The details of security and performance analysis with the related protocols show that our protocol enjoys two advantages: (1) it's more ecient than the related protocols, which greatly re-duces the computation and communication costs; (2) it satises all security goals, however, most previous protocols only meet some security goals.