ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1906.08149
  4. Cited By
Efficient privacy preservation of big data for accurate data mining

Efficient privacy preservation of big data for accurate data mining

Information Sciences (Inf. Sci.), 2019
19 June 2019
Pathum Chamikara Mahawaga Arachchige
P. Bertók
D. Liu
S. Çamtepe
I. Khalil
ArXiv (abs)PDFHTML

Papers citing "Efficient privacy preservation of big data for accurate data mining"

11 / 11 papers shown
ALPINE: Closed-Loop Adaptive Privacy Budget Allocation for Mobile Edge Crowdsensing
ALPINE: Closed-Loop Adaptive Privacy Budget Allocation for Mobile Edge Crowdsensing
Guanjie Cheng
Siyang Liu
Junqin Huang
Xinkui Zhao
Yin Wang
Mengying Zhu
Linghe Kong
166
1
0
10 Apr 2026
Gradients Stand-in for Defending Deep Leakage in Federated Learning
Gradients Stand-in for Defending Deep Leakage in Federated Learning
H. Yi
H. Ren
C. Hu
Y. Li
J. Deng
Xin Xie
FedML
250
1
0
11 Oct 2024
A Survey on Vulnerability of Federated Learning: A Learning Algorithm
  Perspective
A Survey on Vulnerability of Federated Learning: A Learning Algorithm Perspective
Xianghua Xie
Chen Hu
Hanchi Ren
Jingjing Deng
FedMLAAML
312
40
0
27 Nov 2023
OptimShare: A Unified Framework for Privacy Preserving Data Sharing --
  Towards the Practical Utility of Data with Privacy
OptimShare: A Unified Framework for Privacy Preserving Data Sharing -- Towards the Practical Utility of Data with Privacy
Pathum Chamikara Mahawaga Arachchige
Seung Ick Jang
I. Oppermann
Dongxi Liu
Musotto Roberto
...
Meisam Mohammady
S. Çamtepe
Sylvia Young
Chris Dorrian
Nasir David
299
2
0
06 Jun 2023
Gradient Leakage Defense with Key-Lock Module for Federated Learning
Gradient Leakage Defense with Key-Lock Module for Federated Learning
Hanchi Ren
Jingjing Deng
Xianghua Xie
FedML
526
3
0
06 May 2023
Digital Privacy Under Attack: Challenges and Enablers
Digital Privacy Under Attack: Challenges and EnablersACM Computing Surveys (ACM Comput. Surv.), 2023
Baobao Song
Mengyue Deng
Mengyue Deng
Qiujun Lan
R. Doss
Gang Li
AAML
455
5
0
18 Feb 2023
An In-depth Review of Privacy Concerns Raised by the COVID-19 Pandemic
An In-depth Review of Privacy Concerns Raised by the COVID-19 Pandemic
Jiaqi Wang
96
2
0
23 Jan 2021
PPaaS: Privacy Preservation as a Service
PPaaS: Privacy Preservation as a Service
Pathum Chamikara Mahawaga Arachchige
P. Bertók
I. Khalil
Dongxi Liu
S. Çamtepe
318
12
0
04 Jul 2020
Privacy Preserving Face Recognition Utilizing Differential Privacy
Privacy Preserving Face Recognition Utilizing Differential Privacy
Pathum Chamikara Mahawaga Arachchige
P. Bertók
I. Khalil
D. Liu
S. Çamtepe
PICV
243
150
0
21 May 2020
Local Differential Privacy for Deep Learning
Local Differential Privacy for Deep LearningIEEE Internet of Things Journal (IEEE IoT Journal), 2019
Pathum Chamikara Mahawaga Arachchige
P. Bertók
I. Khalil
Dongxi Liu
S. Çamtepe
Mohammed Atiquzzaman
464
265
0
08 Aug 2019
An Efficient and Scalable Privacy Preserving Algorithm for Big Data and
  Data Streams
An Efficient and Scalable Privacy Preserving Algorithm for Big Data and Data StreamsComputers & security (Comput. Secur.), 2019
Pathum Chamikara Mahawaga Arachchige
P. Bertók
D. Liu
S. Çamtepe
I. Khalil
225
59
0
31 Jul 2019
1
Page 1 of 1