DocumentCode
3575297
Title
Real time BIG data analytic: Security concern and challenges with Machine Learning algorithm
Author
Singh, Jainendra
Author_Institution
Dept. of Comput. Sci., Maharaja Surajmal Inst., New Delhi, India
fYear
2014
Firstpage
1
Lastpage
4
Abstract
With great power of data comes great responsibility! A big data initiative should not only focus on the volume, velocity or variety of the data, but also on the best way to protect it. Security is usually an afterthought, but Elemental provides the right technology framework to get you the deep visibility and multilayer security any big data project requires. Multilevel protection of your data processing nodes means implementing security controls at the application, operating system and network level while keeping a bird´s eye on the entire system using actionable intelligence to deter any malicious activity, emerging threats and vulnerabilities. Advances in Machine Learning (ML) provide new challenges and solutions to the security problems encountered in applications, technologies and theories. Machine Learning (ML) techniques have found widespread applications and implementations in security issues. Many ML techniques, approaches, algorithms, methods and tools are extensively used by security experts and researchers to achieve better results and to design robust systems.
Keywords
Big Data; learning (artificial intelligence); security of data; data security; machine learning algorithm; multilayer security; multilevel protection; real time big data analytic; Analytical models; Big data; Blogs; Cryptography; Data models; Filtering; High definition video; Big Data Analytic; Hadoop; Machine Learning Algorithm; Mahout; Security Challenges;
fLanguage
English
Publisher
ieee
Conference_Titel
IT in Business, Industry and Government (CSIBIG), 2014 Conference on
Print_ISBN
978-1-4799-3063-0
Type
conf
DOI
10.1109/CSIBIG.2014.7056985
Filename
7056985
Link To Document