Best Practices: Adopting Security Into the Cloud-Based Internet of Things

Best Practices: Adopting Security Into the Cloud-Based Internet of Things

Anchitaalagammai J. V., Kavitha S., Murali S., Padmadevi S., Shanthalakshmi Revathy J.
DOI: 10.4018/978-1-7998-3111-2.ch006
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Abstract

The internet of things (IoT) is rapidly changing our society to a world where every “thing” is connected to the internet, making computing pervasive like never before. It is increasingly becoming a ubiquitous computing service, requiring huge volumes of data storage and processing. Unfortunately, due to the lack of resource constraints, it tends to adopt a cloud-based architecture to store the voluminous data generated from IoT application. From a security perspective, the technological revolution introduced by IoT and cloud computing can represent a disaster, as each object might become inherently remotely hackable and, as a consequence, controllable by malicious actors. This chapter focus on security considerations for IoT from the perspectives of cloud tenants, end-users, and cloud providers in the context of wide-scale IoT proliferation, working across the range of IoT technologies. Also, this chapter includes how the organization can store the IoT data on the cloud securely by applying different Access control policies and the cryptography techniques.
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Introduction

IoT is an interconnection of everyday objects in a network, which are usually equipped with tremendous intelligence level. IoT has increased the usage of Internet gigantically by integrating every object for interaction through embedded systems, which leads to a highly dispersed network of devices communicating with human beings as well as electronic devices which support internet. IoT is a promising phenomenon which will improve the quality of our lives. In the recent past, IoT has been the center of attraction of researchers and practitioners from all over the world. IoT is a device which is capable of capturing data, storing and processing it. It can also visualize services, monitor and manage various devices.

There is a need of an advanced prototype for security, which considers the security issues from a holistic perspective comprising the advanced users and their intercommunication with this technology. Internet is primary of IoT hence there can be security loophole. Intercommunication paradigms are developed based on sensing programming for IoT applications, evolving an intercommunication stack to develop the required efficiency and reliability. Securing intercommunication is a crucial issue for all the paradigms that are developing based on sensing programming for IoT applications(Choudhury et al., 2017). If we provide good software which insures about security of the cloud storage system and communication between IoT device and cloud, then there is a no problem to accept cloud storage to store IoT data.

Figure 1.

Illustration of Cloud based IoT

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Data generated by the IoT devices is massive and therefore, traditional data collection, storage, and processing techniques may not work at this scale. Furthermore, the sheer amount of data can also be used for patterns, behaviors, predictions, and assessment. Additionally, the heterogeneity of the data generated by IoT creates another front for the current data processing mechanisms. Therefore, to harness the value of the IoT-generated data, new mechanisms are needed. In this context, Machine Learning (ML) is considered to be one of the most suitable computational paradigms to provide embedded intelligence in the IoT devices (Hussain et al., 2019). ML can help machines and smart devices to infer useful knowledge from the device or human-generated data. It can also be defined as the ability of a smart device to vary or automate the situation or behavior based on knowledge which is considered as an essential part for an IoT solution. ML techniques have been used in tasks such as classification, regression and density estimation. Variety of applications such as computer vision, fraud detection, bio-informatics, malware detection, authentication, and speech recognition use ML algorithms and techniques.

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Potential Attacks In Iot

A handful of IoT-related attacks seem to receive the most attention in the popular press which few of them are as follows.

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