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
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;
Conference_Titel :
IT in Business, Industry and Government (CSIBIG), 2014 Conference on
Print_ISBN :
978-1-4799-3063-0
DOI :
10.1109/CSIBIG.2014.7056985