首页    期刊浏览 2024年12月12日 星期四
登录注册

文章基本信息

  • 标题:Big Data Analytics with Hadoop to analyze Targeted Attacks on Enterprise Data
  • 本地全文:下载
  • 作者:Bhawna Gupta ; Dr. Kiran Jyoti
  • 期刊名称:International Journal of Computer Science and Information Technologies
  • 电子版ISSN:0975-9646
  • 出版年度:2014
  • 卷号:5
  • 期号:3
  • 页码:3867-3870
  • 出版社:TechScience Publications
  • 摘要: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 networks- allowing 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.
  • 关键词:Big Data Analytics; Hadoop; MapReduce; Big Data;Security Analytics; Targeted Attacks
国家哲学社会科学文献中心版权所有