Results 61 to 70 of about 2,055 (161)
Experimenting sensitivity-based anonymization framework in apache spark
Journal of Big Data, 2018 One of the biggest concerns of big data and analytics is privacy. We believe the forthcoming frameworks and theories will establish several solutions for the privacy protection.
Mohammed Al-Zobbi +2 more
doaj +1 more source
Procedia Computer Science, 2013 AbstractRecent innovations in Big Data have enabled major strides forward in our ability to glean important insights from massive amounts of data, and to use these insights to make better decisions. Underlying many of these innovations is a computational paradigm known as MapReduce, which enables computational processes to be scaled up to very large ...
openaire +1 more source
Mining Characteristics of Vulnerable Smart Contracts across Lifecycle Stages
IET Blockchain, Volume 5, Issue 1, January/December 2025.This paper conducts the first empirical study on smart contract security across three lifecycle stages: deployment and execution, upgrade, and destruction. It identifies seven vulnerability‐related features and applies them to machine learning models, revealing stage‐specific vulnerability patterns and improving detection accuracy.
Hongli Peng, Wenkai Li, Xiaoqi Li
wiley +1 more source
IEEE Access, 2018 In this paper, we discuss some challenges regarding the Hadoop framework. One of the main ones is the computing performance of Hadoop MapReduce jobs in terms of CPU, memory, and hard disk I/O. The networking side of a Hadoop cluster is another challenge,
Ali Khaleel, Hamed Al-Raweshidy
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Big data: modern approaches to storage and analysis
Труды Института системного программирования РАН, 2018 Big data challenged traditional storage and analysis systems in several new ways. In this paper we try to figure out how to overcome this challenges, why it's not possible to make it efficiently and describe three modern approaches to big data handling ...
Pavel Klemenkov, Sergey Kuznetsov
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Finding Top- $k$ Dominance on Incomplete Big Data Using MapReduce Framework
IEEE Access, 2018 Incomplete data is one major kind of multi-dimensional dataset that has random-distributed missing nodes in its dimensions. It is very difficult to retrieve information from this type of dataset when it becomes large.
Payam Ezatpoor +3 more
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Proceedings of the 7th International Conference on Security of Information and Networks, 2014 MapReduce is a new parallel programming paradigm proposedto process large amount of data in a distributed setting.Since its introduction, there have been efforts to improvethe architecture of this model making it more efficient,secure and scalable. In parallel with these developments,there are also efforts to implement and deploy MapReduce,and one of ...
Zhang, Ning, Lahmer, Ibrahim
openaire +2 more sources
mRNAs of plants and green algae lack the m7G cap‐1 structure
New Phytologist, Volume 246, Issue 2, Page 396-401, April 2025.
Chen Xiao +7 more
wiley +1 more source
Hadoop Çatısının Bulut Ortamında Gerçeklenmesi Ve Terabyte Sort Deneyleri
MANAS: Journal of Engineering, 2015 Hadoop framework employs MapReduce programming paradigm to process big data by distributing data across a cluster and aggregating. MapReduce is one of the methods used to process big data hosted on large clusters.
G. Ozen, R. Sultanov
doaj
A privacy-preserving parallel and homomorphic encryption scheme
Open Physics, 2017 In order to protect data privacy whilst allowing efficient access to data in multi-nodes cloud environments, a parallel homomorphic encryption (PHE) scheme is proposed based on the additive homomorphism of the Paillier encryption algorithm. In this paper
Min Zhaoe, Yang Geng, Shi Jingqi
doaj +1 more source