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Preserving Sensitive Information using Fuzzy C-Means Approach

Asha Kiran, Manimala Puri, S. Srinivasa
2018 International Journal of Computer Applications  
Providing safe access controls and privacy preservation are the primary concerns in the development of medical applications. Medical data possess sensitive information.  ...  Subsequently, the model teaches the underlying relations to perform categorization based on the input. This paper describes the experiment in view of privacy preserving data mining.  ...  ACKNOWLEDGMENTS Sincere thanks to Abacus Institute of Computer Applications, Research Center, SPPU, Pune for giving opportunity to pursue research related to data privacy.  ... 
doi:10.5120/ijca2018917656 fatcat:trygh2x54rhcxjqgdied6wz324

Survey on Privacy Preservation for Multi-Keyword Search on Data Network

2016 International Journal of Science and Research (IJSR)  
In today's emerging information networks, it is essential to find a solution for accessing the data from large number of providers while maintaining a privacy .  ...  In recent years, growth of private and semi-private information has grown rapidly on information network so, mechanisms to search such information have failed in privacy preservation.  ...  To gain a relevant information is also required while preserving a privacy. Hence there is a need to preserve privacy of data in information networks.  ... 
doi:10.21275/v5i1.nov152679 fatcat:db3fu6wthrbgjip6qef3rxed2m

Supporting privacy protection in personalized web search for knowledge mining
IJARCCE - Computer and Communication Engineering

Mr. Stibu Stephen, Mr. A. Venugopal
2015 IJARCCE  
From this method no assurance to the user privacy and also no securities were providing to their data. Hence users were afraid for their private information during search has become a major barrier.  ...  For minimizing the privacy risk here we propose the client side based technique with the combination of Greedy method to prevent the user data that we applied in Knowledge mining area.  ...  It uses TREC AP Data to create a test set for evaluating implicit feedback models.  ... 
doi:10.17148/ijarcce.2015.4115 fatcat:dz72zdafkvfvdc6bxgte5mykmy

Dare to share your information!

Trina Innes
2002 Forestry Chronicle  
Share your Model instead of your Data: Privacy Preserving Mimic Learning for Ranking Dehghani, M.; Azarbonyad, H.; Kamps, J.; de Rijke, M.  ...  Training these models requires large, representative datasets and for most IR tasks, such data contains sensitive information from users.  ...  However, in many information retrieval tasks, due to the sensitivity of the data from users and privacy issues, not all researchers have access to large-scale datasets for training their models.  ... 
doi:10.5558/tfc78090-1 fatcat:6jojcp7b45bnncbmvqs2mc5pba

Share your Model instead of your Data: Privacy Preserving Mimic Learning for Ranking [article]

Mostafa Dehghani, Hosein Azarbonyad, Jaap Kamps, Maarten de Rijke
2017 arXiv   pre-print
Training these models requires large, representative datasets and for most IR tasks, such data contains sensitive information from users.  ...  In this paper, we discuss privacy preserving mimic learning, i.e., using predictions from a privacy preserving trained model instead of labels from the original sensitive training data as a supervision  ...  However, in many information retrieval tasks, due to the sensitivity of the data from users and privacy issues, not all researchers have access to large-scale datasets for training their models.  ... 
arXiv:1707.07605v1 fatcat:s66vtqn4rrhpfglb3dj4ebtytu

Big data privacy: a technological perspective and review

Priyank Jain, Manasi Gyanchandani, Nilay Khare
2016 Journal of Big Data  
On the premise of this definition, the properties of big Abstract Big data is a term used for very large data sets that have more varied and complex structure.  ...  Big data [1, 2] specifically refers to data sets that are so large or complex that traditional data processing applications are not sufficient.  ...  towards privacy-preserving data mining of very massive data sets using MapReduce Generalization is unable to handle high dimensional data, it reduces data utility.  ... 
doi:10.1186/s40537-016-0059-y fatcat:hol5lhemzvawzc6yyxe4paa7zu

Secure Keyword Search Using TRSE Scheme over Cloud Data

A. Libana Mary, Ms. R.Asmetha Jeyarani
2014 IOSR Journal of Computer Engineering  
According to privacy it has been presented as an outsourcing of sensitive information. The searchable symmetric encryption is mainly focus on addressing the data privacy issues.  ...  The server side ranking based on order-preserving encryption and it's inevitably leaks the data privacy has to be observed and it can control in the proposed scheme.  ...  Confidentiality-Preserving Rank-Ordered Search A new framework for confidentiality preserving rank-ordered search and retrieval over large document collections.  ... 
doi:10.9790/0661-16347579 fatcat:ejlokatly5cjtpx5iwnlswnh4m

How to keep text private? A systematic review of deep learning methods for privacy-preserving natural language processing [article]

Samuel Sousa, Roman Kern
2022 arXiv   pre-print
Second, we present an extensive summary of privacy threats, datasets for applications, and metrics for privacy evaluation.  ...  To close this gap, this article systematically reviews over sixty DL methods for privacy-preserving NLP published between 2016 and 2020, covering theoretical foundations, privacy-enhancing technologies  ...  • What are the tradeoffs between privacy preservation and performance for utility tasks in NLP? • Which privacy metrics can be used for evaluating privacy-preserving NLP models?  ... 
arXiv:2205.10095v1 fatcat:rksy7oxxlbde5bol3ay44yycru

2020 Index IEEE Transactions on Information Forensics and Security Vol. 15

2020 IEEE Transactions on Information Forensics and Security  
., +, TIFS 2020 1248-1260 On the Information Leakage in Private Information Retrieval Systems. Guo, T., +, TIFS 2020 2999-3012 Private Information Retrieval Over Random Linear Networks.  ...  ., +, TIFS 2020 435-446 An Adaptive Authenticated Data Structure With Privacy-Preserving for Big Data Stream in Cloud.  ... 
doi:10.1109/tifs.2021.3053735 fatcat:eforexmnczeqzdj3sc2j4yoige

Report on the 2017 ACM SIGIR International Conference Theory of Information Retrieval (ICTIR?17)

Hui Fang, Jaap Kamps, Evangelos Kanoulas, Maarten de Rijke, Emine Yilmaz
2018 SIGIR Forum  
or industrial settings.  ...  Abstract This is a report on ICTIR'17, which continued its tradition of being the premier forum for presentation of research on theoretical aspects of Information Retrieval (IR).  ...  for discussion on fundamental issues in information access and information processing.  ... 
doi:10.1145/3190580.3190591 fatcat:s7imfuw3s5g7zm7cb3fjugv3me

D2.7 Key performance indicators selection and definition - final version

Susanna Bonura, Davide Dalle Carbonare
2020 Zenodo  
The Evaluation Framework employed for validating the MUSKETEER platform, is based on the Goal Question Metric (GQM) method.  ...  This task deals with the definition of KPIs related to the processing and analysis of data coming from the two industrial scenarios, which shall be improved through the application of MUSKETEER data platform  ...  MUSKETEER allows ML over datasets allocated in different locations (thus removing the data localization barrier) where the privacy preserving analytics remove any chance of information leakage and with  ... 
doi:10.5281/zenodo.5845684 fatcat:zedfi6jdibgptbherd6rp2abte

Perspective Challenges & Proposed Solution for Ppdm Using Data Mining Techniques

Charu Sharma
2017 International Journal for Research in Applied Science and Engineering Technology  
The task of mining data by preserving its privacy is called Privacy Preserving Data Mining (PPDM).  ...  Data mining is usually used to retrieve unseen information, sensitive insensitive data, and knowledge from the high volume of databases.  ...  In most of the cases, the constraints for privacy preserving are accurate data, generated models and performance of mining and maintaining privacy. The several approaches used with PPDM are A.  ... 
doi:10.22214/ijraset.2017.8298 fatcat:x6bmks5qxfd4jnbxmmi2hxepbe

A systematic review on privacy-preserving distributed data mining

Chang Sun, Lianne Ippel, Andre Dekker, Michel Dumontier, Johan van Soest, Karin Verspoor
2021 Data Science  
Privacy-preserving distributed data mining techniques (PPDDM) aim to overcome these challenges by extracting knowledge from partitioned data while minimizing the release of sensitive information.  ...  Combining and analysing sensitive data from multiple sources offers considerable potential for knowledge discovery.  ...  Dayana Spagnuelo for their valuable comments. We would like to thank Dr. Leto Peel for his generous feedback and suggestions to help us improve the quality of the manuscript.  ... 
doi:10.3233/ds-210036 fatcat:tzdj4mggv5f6xld3tvpghgltd4

D3.4 Final Prototype of the MUSKETEER Platform

Mark Purcell, Ambrish Rawat
2021 Zenodo  
It also supports the assessments to be carried out in WP6 and provides interfaces which allow for the development of client connectors and end-to-end demonstrations of the industrial use cases in WP7.  ...  The following information is added to the model lineage: Machine Learning to Augment Shared Knowledge in Federated Privacy-Preserving Scenarios (MUSKETEER) • Contribution -an aggregator defined/assigned  ...  ", "params": ["<TaskName>", <{Model}>, "<metadata>"] } } } • <Model> -a trained model (JSON, optional) • <Metadata> -participant specific information (string) Retrieving Lineage A new API is required  ... 
doi:10.5281/zenodo.5841512 fatcat:ftcptbh2sbcf5dwpto2xm4w5py

Survey of Interoperability in Electronic Health Records Management and Proposed Blockchain Based Framework: MyBlockEHR

Rahul G. Sonkamble, Shraddha P. Phansalkar, Vidyasagar M. Potdar, Anupkumar M. Bongale
2021 IEEE Access  
2) What are the different privacy-preservation techniques and security standards for EHR data storage?  ...  The proposed framework employs partitioning of EHR to onchain and off-chain storages for performance guarantees with the retrieval of valid off-chain data.  ...  TABLE VII EVALUATION VII OF PERFORMANCE OF DATA MODELS IN EHR MANAGEMENT Works Data Model Document Types Data Store Examples Retrieval Performance Object Complexity Features Consistency Isolation Scalability  ... 
doi:10.1109/access.2021.3129284 fatcat:o4shlvvcmvfahkstrxvq3piq64
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