International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 1991 Big Data Privacy and Security Challenges in Industries Dr. B. Chidambararajan 1 , Dr. M. Senthil Kumar 2 , Ms. S.K. Susee 3 1 Principal & professor, Dept of ECE, SRM Valliammai Engineering College, TN, India. 2 Associate professor, Dept of CSE, SRM Valliammai Engineering College, TN, India. 3 Part–time Research Scholar, Anna University, TN, India. ---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract - Extremely large data set is used for computational analysis purpose is called Big Data. This Big Data is used for many purposes like pattern checking, CA (Classifications and Associations) and most importantly activities like humanoid and interactions. Providing security to big data is essential as it can be stolen by hackers. In this regard, the security measures and challenges against big data technologies are discussed in order to provide protection. Analysis for big data to retain the possible risk and privacy issues associated with data security is an effective method for the complete performance metrics for big data. Key Words: Big data, Big data analysis, Big data framework, Data security, Data privacy. 1. INTRODUCTION This Huge volume of data is used in big data technologies. The existing methods for big data analysis is not adequate and big data storing and retrieval is a challenging task [4][11]. Data generation and storing in databases is rapidly growing in now a days. In big data setting, there is enormous issues and complications to store and retrieve data. The term big data denotes storing and analysis huge volume of data to obtain targeted output. Gathering, Storing, Searching, Sharing, Transferring, Analyzing and presenting data as per requirements are the major challenging task in big data. There are three main characteristics defined in big data [10]. They are  Volume  Velocity and  Variety The following Fig-1 shows capturing data from different sources and processing of data in big data environment. Fig-1 Architecture of Big data Data obtained from different sources and stored in data bases. The data may be structured or unstructured manner. Data analysis and data processing are done as per the users rights assigned. Users rights defined here is may be a data owners or technical analyst or business analyst [2]. 2. RELATED WORK Privacy and Security [8] in big data plays a major role by considering data privacy, data management, integrity constraints management and framework security [15]. Privacy and Security [3] differs from each other by the means where privacy focuses on the data being collected, shared and used in right manner and security focus on protecting the data from intruder’s attack, exploitation of data for other such purposes on the grounds of money mind. Categories of Big Data Privacy Data Privacy deals with preserving the privacy of data through some encryption mechanisms [7] for the data being collected from different sources during the analytic stage [9, 12]. Data Administration data being collected from wide variety of sources grows in huge number of volume on daily basis. In which the data object is attached with data about data i.e. metadata providing information about the data object under consideration becomes complex in big data applications. Integrity Security validation of input and the filtering stage embraces an important task in big data applications due to the data mass and those data should be from authorized source if not appropriate actions has to be taken. Framework Security – big data adopts distributed environment in which identification of invaders [13] or malicious users become critical. Privacy Challenges Due to the massive growth of data many privacy related concerns needs to be taken into consideration. The most substantial privacy related concerns are: big data analytics become inaccurate, data discrimination, data masking, anonymization turns impossible, security intelligence and compliance audit, making patents and copyrights irrelevant, information security itself becomes a major big data issue. Security Challenges Security in big data becomes a leading edge due to the factors velocity, volume and variety. The following are some of the security challenges of big data [1, 5, 6, 14, and 16] a. Real time security and compliance monitoring provide real time problem detection through privacy analysis.