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Big Data Analytics: Security and Privacy Challenges
تجزیه و تحلیل داده های بزرگ: چالش های امنیتی و حفظ حریم خصوصی-2016 The digitalization of our day-to-day activities has
resulted in a huge volume of data. This data, called Big Data, is
used by many organizations to extract valuable information
either to take marketing decisions, track specific behaviors or
detect threat attacks. The processing of such data is made
possible by using multiple techniques, called Big Data Analytics,
which allow getting enormous benefits by dealing with any
massive volume of unstructured, structured and semi-structured
content that is fast changing and impossible to process using
conventional database techniques. However, while Big Data
represents an immense opportunity for many industries and
decisions makers, it also represents a big risk for many users.
This risk arises from the fact that these analytics tools consist of
storing, managing and efficiently analyzing varied data gathered
from all possible and available sources. The consequence is that
people become widely vulnerable to exposure because of
combining and exploring specific behavioral data. That is, it is
possible to collect more data than it should have which leads to
many security and privacy violations. Therefore, research
community has to consider these issues by proposing strong
protection techniques that enable getting benefits from big data
without risking privacy. In this paper, we highlight the benefits
of Big Data Analytics and then we review challenges of security
and privacy in big data environments. Furthermore, we present
some available protection techniques and propose some possible
tracks that enable security and privacy in a malicious big data
context.
Keywords: Big Data Analytics | Security | Privacy | Homomorphic Encryption | Blind Processing. |
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