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Network Security Strategies in Big Data Context
Author(s) -
Imane El Alaoui,
Youssef Gahi
Publication year - 2020
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2020.07.108
Subject(s) - big data , computer science , computer security , context (archaeology) , network security , data science , process (computing) , focus (optics) , data mining , biology , physics , optics , operating system , paleontology
Big data allows organizations to process massive and complex data to extract hidden patterns, draw insights, and also to share data through the network. Data that transit in an organization network is often sensitive and requires an efficient and secure platform. For this reason, network security has been brought to the forefront in the Big data era. In this context, network security platforms have to deal with vast and complex information to predict and prevent potential attacks in real-time. However, these platforms are often based on traditional approaches, which make them unreliable to secure big data. In this paper, we mainly focus on network security and protection strategies of big data. First, we highlight factors affecting network security platforms in the Big data era. Then, we go through different big data strategies that allow ensuring security across networks while surveying recent researches.

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