Results 41 to 50 of about 27,791 (249)

Local Node Differential Privacy

CoRR
We initiate an investigation of node differential privacy for graphs in the local model of private data analysis. In our model, dubbed LNDP*, each node sees its own edge list and releases the output of a local randomizer on this input. These outputs are aggregated by an untrusted server to obtain a final output.
Sofya Raskhodnikova, Adam D. Smith 0001, Connor Wagaman, Anatoly Zavyalov   +3 more
openaire   +2 more sources

Randori: Local Differential Privacy for All

CoRR, 2021
Polls are a common way of collecting data, including product reviews and feedback forms. However, few data collectors give upfront privacy guarantees. Additionally, when privacy guarantees are given upfront, they are often vague claims about 'anonymity'.
openaire   +2 more sources

The Role of Interactivity in Local Differential Privacy [PDF]

2019 IEEE 60th Annual Symposium on Foundations of Computer Science (FOCS), 2019
We study the power of interactivity in local differential privacy. First, we focus on the difference between fully interactive and sequentially interactive protocols. Sequentially interactive protocols may query users adaptively in sequence, but they cannot return to previously queried users.
Matthew Joseph, Jieming Mao, Seth Neel, Aaron Roth 0001   +3 more
openaire   +2 more sources

K-Means Clustering with Local Distance Privacy

Big Data Mining and Analytics, 2023
With the development of information technology, a mass of data are generated every day. Collecting and analysing these data help service providers improve their services and gain an advantage in the fierce market competition.
Mengmeng Yang, Longxia Huang, Chenghua Tang   +2 more
doaj   +1 more source

On the Lift, Related Privacy Measures, and Applications to Privacy–Utility Trade-Offs

Entropy, 2023
This paper investigates lift, the likelihood ratio between the posterior and prior belief about sensitive features in a dataset. Maximum and minimum lifts over sensitive features quantify the adversary’s knowledge gain and should be bounded to protect ...
Mohammad Amin Zarrabian, Ni Ding, Parastoo Sadeghi   +2 more
doaj   +1 more source

High-dimensional Data Publication Under Local Differential Privacy [PDF]

Jisuanji kexue
With the increasing availability of high-dimensional data collected from numerous users,preserving user privacy while utilizing high-dimensional data poses significant challenges.This paper focuses on the problem of high-dimensional data publication ...
CAI Mengnan, SHEN Guohua, HUANG Zhiqiu, YANG Yang
doaj   +1 more source

LDPORR: A localized location privacy protection method based on optimized random response

Journal of King Saud University: Computer and Information Sciences, 2023
The broad use of mobile intelligent terminals with locating functions encourages the rapid development of location-based services (LBS), which are widely used in a variety of industries such as social networking, transportation, finance, and ...
Yan Yan, Jianzhuang Chen, Adnan Mahmood, Xingying Qian, Pengbin Yan   +4 more
doaj   +1 more source

Local Differential Privacy: a tutorial

CoRR, 2019
In the past decade analysis of big data has proven to be extremely valuable in many contexts. Local Differential Privacy (LDP) is a state-of-the-art approach which allows statistical computations while protecting each individual user's privacy. Unlike Differential Privacy no trust in a central authority is necessary as noise is added to user inputs ...
openaire   +2 more sources

Sociodemographic Factors Associated With Later Stage at Diagnosis of Pediatric Germ Cell Tumors: A Report From Children's Oncology Group Registries ACCRN07 and APEC14B1

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Germ cell tumors (GCTs) often arise in the ovaries and testes (extracranial) but can also develop in the brain (intracranial). We examined the relationship of individual, family, and community‐level socioeconomic status (SES) with stage of disease at diagnosis in a cohort of pediatric patients with GCT from Children's Oncology Group
Heydon K. Kaddas, Judy Y. Ou, Todd Alonzo, Logan G. Spector, Negar Fallahazad, Emily Owens, Anne C. Kirchhoff, Adam L. Green   +7 more
wiley   +1 more source

Survey on differential privacy and its progress

Tongxin xuebao, 2017
With the arrival of the era of big data sharing,data privacy protection issues will be highlighted.Since its introduction in 2006,differential privacy technology has been widely researched in data mining and data publishing.In recent years,Google,Apple ...
Zhi-qiang GAO, Yu-tao WANG
doaj   +2 more sources