Big Data Analytics with Hadoop to analyze Targeted Attacks on Enterprise Data

نویسنده

  • Bhawna Gupta
چکیده

Big Data describes data sets that are too large, to unstructured or too fast changing for analysis. Big Data analytics is the process of analyzing and mining Big Data. Due to increase in number of sophisticated targeted threats and rapid growth in data, the analysis of data becomes too difficult. Today's Big Data security analytics systems rely, on untrustworthy data. As organizations open and extend their data networksallowing partners, suppliers and customers to access corporate information in new and dynamic ways and this becomes more vulnerable to data misuse and theft. Attackers have become more adapt at highly targeted, complex attacks that overtake static threat detection measures. Today's attacks are prepared by advanced technologies are not detected until the damage has been occurred. Now the challenge is collecting and analyzing the Big Data fast enough to contain threats and perform last remediation. In this review paper, we are discussing about technique how Big Data is analyzed by using the technique of Hadoop and why the Big Data Security Analytics is important to mitigate the security threats to secure the enterprise data more efficiently.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Fuzzy TOPSIS Approach for Big Data Analytics Platform Selection

Big data sizes are constantly increasing. Big data analytics is where advanced analytic techniques are applied on big data sets. Analytics based on large data samples reveals and leverages business change. The popularity of big data analytics platforms, which are often available as open-source, has not remained unnoticed by big companies. Google uses MapReduce for PageRank and inverted indexes....

متن کامل

2016 Olympic Games on Twitter: Sentiment Analysis of Sports Fans Tweets using Big Data Framework

Big data analytics is one of the most important subjects in computer science. Today, due to the increasing expansion of Web technology, a large amount of data is available to researchers. Extracting information from these data is one of the requirements for many organizations and business centers. In recent years, the massive amount of Twitter's social networking data has become a platform for ...

متن کامل

Big Data in Distributed Analytics, Cybersecurity, Cyber Warfare and Digital Forensics

Big Data can reduce the processing time of large volumes of data in the distributed computing environment using Hadoop. It also can predict potential cybersecurity breaches, help stop cyber attacks, and facilitate post-breach digital forensic analysis. This paper introduces Big Data applications in distributed analytics, general cybersecurity (general cyber threats, cyber attacks, and cyber sec...

متن کامل

Cloud Computing Technology Algorithms Capabilities in Managing and Processing Big Data in Business Organizations: MapReduce, Hadoop, Parallel Programming

The objective of this study is to verify the importance of the capabilities of cloud computing services in managing and analyzing big data in business organizations because the rapid development in the use of information technology in general and network technology in particular, has led to the trend of many organizations to make their applications available for use via electronic platforms hos...

متن کامل

Joins for Hybrid Warehouses: Exploiting Massive Parallelism in Hadoop and Enterprise Data Warehouses

HDFS has become an important data repository in the enterprise as the center for all business analytics, from SQL queries, machine learning to reporting. At the same time, enterprise data warehouses (EDWs) continue to support critical business analytics. This has created the need for a new generation of special federation between Hadoop-like big data platforms and EDWs, which we call the hybrid...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014