File Inclusion Vulnerability Analysis using Hadoop and Navie Bayes Classifier | Abstract

ISSN ONLINE(2320-9801) PRINT (2320-9798)

Research Article Open Access

File Inclusion Vulnerability Analysis using Hadoop and Navie Bayes Classifier

Abstract

Big data is an evolving data set that describes any voluminous amount of structured, semi-structured and unstructured data and is beyond the ability of a traditional database tool .Big data can be analysed for extracting valuable information. Hadoop rides the big data where the massive quantity of information is processed using clusters of commodity hardware. A web server log is automatically created by a server which maintains a history of vulnerability attacks. SQL Injection and Remote File Inclusion are the two most frequently used vulnerability attacks and hackers preferring easier rather than complicated attack techniques .RFI uses the weakness of PHP language which in today’s world is the most widely used. Hadoop Technologies like Oozie, Hive,Pig and Sqoop can be used to analyze web log data to detect File inclusion vulnerabilities . Naïve Bayes algorithm is implemented in Hive user defined function to classify attack keywords in log file. Oozie is a job coordinator and work flow manager that supports several types of Hadoop jobs such as Java map-reduce, Streaming map- reduce, Pig, Hive, and Sqoop

Vidya Muraleedharan, Dr.KSatheesh Kumar, Ashok Babu

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