Rapid usage of Internet of Things (IOT) has resulted in generating large volume of data from different heterogeneous sensor based devices that communicate with each other over the internet. Hence, biggest challenge lies in designing and adoption of efficient security mechanism in IOT based framework. Accordingly, massive volume of data is required to be analysed by using the concept of Big Data. Big data analytics comprises of different processes that is useful in analysing the data to discover some hidden patters or certain correlations that exist in the data sets. The popularity of IoT devices leads to an expensive cost resulting in loss of resources and information that are caused by security threats and attacks. Although in the literature several research proposals exist that has addressed the various concerns of Big data in IOT such as privacy involved in collecting the data, storage and analysis. However, still there is a huge gap of analyzing Big data in IOT environment. We fully investigate the security and privacy issues that are involved in Big data streaming for IOT devices.
TopI. Introduction
Internet of Things comprises of different network devices that are uniquely addressable such that communication with each other is possible. (Atzori et al. 2010) stated that IOT can be considered as combination of three main terms namely internet oriented, things-oriented, and semantic-oriented. The major objective of IOT is to enable sharing of real time autonomous network connected actors (Yang et al. 2013). As shown in Figure 1 the major terms that revolves around the IOT involves communication between sensors at any point of time, from any place. Data collection process involves locating and transferring data from large number of communicating devices within the IOT framework. With the rapid increase of Internet of Things devices, a huge quantity of data is created every year which is known as Big Data. Big data (Manyika et al. 2011) (Chowdary et al. 2020) is referred as “a novel era of knowledge that are useful in economically separating the value from enormous data obtained from multiple sources that enables discovery and analysis Big data is frequently defined by the five Vs, which are Volume: The production of petabytes or exabytes of data 2. Variety - It entails the creation of structured, semi-structured, and unstructured data received from a variety of sources, including sensors, images, videos, and more. 4. Variability - This term describes the several properties of data and 5. Veracity relates to the fineness of the data.
Figure 1. Internet of Things: Related Concepts
Application of IOT has enabled people to control and apprehend their environment that involves series of interconnected devices (Zedadra et al. 2019). The amalgamation of IoT technology with big data have been used in several areas such as smart healthcare etc. (Bibri et al., 2018). Hence, IOT enabled construction in big data environment has become an important step for developing, promoting and managing the strategic environment protected industry (Alam et al., 2017).
Even though significant work has been obtained in the area of IOT enabled smart environment applications still some challenges still prevail that includes data capturing, processing and analyzing massive amount of data for computational purposes. A real time processing system is required for handling high stream data that in turn requires rapid and effective data analysis. The integration of diverse data sources, including satellites and IoT-based sensors, as well as the availability of big data analytical tools like Hadoop and Spark with visualisation tools like Kibana, is expected to contribute to the rise of the smart environment. Figure 2 shows the major tools used in this area. However, it is challenging and promising to understand the usefulness of data this makes imperative to establish IoT based Big data applications within the smart environment.
Figure 2. Tools used in Big Data and IoT
Furthermore, there is a security and privacy risk while using Big data in IOT. Privacy of Big data involves the protection from any unauthorized users (Ardagna et al., 2014).Hence, a stability against the communal benefit of big data is utmost required. Figure 3 represent the architecture streaming of Big data in IOT environment.
Figure 3. Architecture streaming of Big Data in IoT Framework
The potential advantages that big data can provide in an IoT environment are highlighted in Table 1 for a variety of applications, including smart grid, smart inventory, smart transportation, and smart healthcare.