Advantages And Disadvantages Of Big Data

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INTRODUCTION - The term “Big Data” refers to the massive amounts of digital information companies and governments collect about human beings and environment. The amount of data produced or gathered is increasing at a faster rate and is like to double after every two years i.e., from 2500 exabytes in 2012 to 40,000 exabytes in 2020 . Security and privacy issues are describes by the 3 V’s of big data- volume, variety, and velocity.
The security and privacy issues can be grouped into four categories according to the nature of big data :
 Infrastructure security
 Data privacy
Data management
 Integrity and reactive security.
Solving data security and privacy challenges requires addressing three distinct issues:
 Modeling: formalizing a threat model that covers most of the cyber-attack or data-leakage scenarios
 Analysis: finding tractable
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Real-Time Security Monitoring- One of the most challenging Big Data analytics problems is real-time security monitoring, which consists of two main angles: (a) monitoring the Big Data infrastructure itself and (b) using the same infrastructure for data analytics.
Real-time security monitoring is a challenge because of the number of alerts generated by security devices. These alerts (correlated or not) lead to a massive number of false positives, which are often ignored due to limited human capacity for analysis. This problem might even increase with Big Data, given the volume and velocity of data streams. The implementation of the security best practices depends on the situation at hand. At the moment of writing, there are no built-in security monitoring and analysis tools in Hadoop. However, monitoring and analysis tools are being developed and announced by different Hadoop providers and vendors. An alternative solution is the implementation of front-end systems to monitor Hadoop requests (e.g., Database Activity Monitoring proxy of firewall).
7. Cryptographically Enforced Data-Centric
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