Security Issues Associated with Big Data in Cloud Computing

Abstract

In this paper, we discuss security issues for cloud computing, Big data, Map Reduce and Hadoop environment. The main focus is on security issues in cloud computing that are associated with big data. Big data applications are a great benefit to organizations, business, companies and many large scale and small scale industries.We also discuss various possible solutions for the issues in cloud computing security and Hadoop. Cloud computing security is developing at a rapid pace which includes computer security, network security, information security, and data privacy. Cloud computing plays a very vital role in protecting data, applications and the related infrastructure with the help of policies, technologies, controls, and big data tools. Moreover, cloud computing, big data and its applications, advantages are likely to represent the most promising new frontiers in science.

Empirical Analysis of Recent Advances, Characteristics and Challenges of Big Data

“…Taking the retail industry, for instance, we attempt to offer a succinct presentation in favour of the functionalities of Big Data in business aerobics. Daily in the 6000 stores of Wal-Mart's, there are approximately 267 million businesses throughout the world [41]. For searching higher competition in sell, Wal-Mart in recent times worked in partnership with HP (Hewlett Packard) to ascertain a data warehouse that has a capacity to save four (4) PB of data [24].…”

“…To make this sure, it copied data on servers to avoid the loss of data. Hadoop power is founded on 02 main subparts: Hadoop Distributed File System (HDFS) and MapReduce [41]. Additionally, modules can be added by users on top of Hadoop when required according to their application needs and goals (e.g.…”

Feature Extraction and Feature Selection : Reducing Data Complexity with Apache Spark

“…lack of any labels or any indication of a suspicious threat/attack), clustering techniques will be used to define baseline behavioural profiles and to detect outliers [1]. The latter may correspond to rare, sparse anomalies, that can be found by either first-class detection of novelties,n-gram analysis of nested attributes and pattern analysis using Indicators of Compromise (IoCs) [8] [6]. A survey on unsupervised learning outlier detection algorithms is presented in [14].…”

A Review on Big Data: Views, Categories and Aspects

“…Inukollu et al (2014) discussed security issues for cloud computing, in big data, Map Reduce approach under Hadoop environment. Authors placed various possible solutions in view of such data for problems in cloud computing security [9]. Figure 3 explains the relationships.…”