A Framework for Big Data Security Using MapReduce in IoT Enabled Computing
Kartikay Kala, Kartik Makhloga, Anayat Khan, Aishwarya Pandey, Saksham Mittal · 2024
With the increase in number of IoT devices day by day, a large amount of unstructured, structured and semi-structured data is being generated, collectively termed as big data. The amount of data stored and processed in the cloud is increasing at a rapid pace. The traditional storage devices cannot meet the requirement of the cloud at both hardware and software levels. There is a need for a mechanism which can handle this issue. Hadoop is a platform which can overcome this big data issue. Hadoop uses HDFS and Map Reduce to process large quantity of data in the cloud system. It is also essential to ensure big data security generated by IoT devices and only the authorized users can access the data. Therefore, this research aims to secure big data using RSA. MapReduce is used to process and encrypt big data as it helps in parallel processing of the data in few seconds. This research paper presents a comparative study focused on the encryption time performance in Hadoop, specifically examining the impact of increasing mappers on the overall encryption process.