Security and Privacy Issues in IoT

Security and privacy issues are the challenging areas in the field of internet of things (IoT) and fog computing. IoT and fog has become an involving technology allowing major changes in the field of information systems and communication systems. This chapter provides the introduction of IoT and fog technology with a brief explanation of how fog is overcoming the challenges of cloud computing. Thereafter, the authors discuss the different security and privacy issues and its related solutions. Furthermore, they present six different case studies which will help the reader to understand the platform of IoT in fog.

Introduction to Fog Computing

Pushing computing, control, data storage, and processing into the cloud has been a key trend in the past decade. However, the cloud alone encounters growing limitations, such as reduced latency, high mobility, high scalability, and real-time execution in order to meet the upcoming computing and intelligent networking demands. A new paradigm called fog computing has emerged to overcome these limits. Fog extends cloud computing and services to the edge of the network. It provides data, computing, storage, and application services to end-users that can be hosted at the network edge. It reduces service latency, and improves QoS/QoE, that results in superior user experience. This chapter is about introduction and overview of fog computing, comparison between fog computing and cloud computing, fog computing and mobile edge computing, possible fog computing architecture, applications of fog computing, and possible research directions.

IOT and Data Analytics Solution for Reducing Pollution, Accidents, and Its Impact on Environment

The goal of this chapter is to inspect and consider the answer for accidents and reactions to the accidents in the urban zones. Modules have been made to manage the colossal datasets and to bring interesting bits of knowledge into the outcomes. This is done by utilizing decision tree analysis.

IOT and Data Analytics Solution for Smart Agriculture

This chapter gives the real-time solutions to the farmers by providing smart solutions for irrigation, disease monitoring, and decision supporting systems (which involves giving suggestions and solutions to the farmers by monitoring soil conditions, rain, weather, and overall quality of crop growth and the effect on the growth of the crop due to infertile soil or bad climatic conditions). These solutions are provided using the IOT and data analytics technology.

Fog Computing and Networking Architectures

The demerits of cloud computing lie in the velocity, bandwidth, and privacy of data. This chapter focuses on why fog computing presents an effective solution to cloud computing. It first explains the primary motivation behind the use of fog computing. Fog computing, in essence, extends the services of the cloud towards the edge of the network (i.e., towards the devices nearer to the customer or the end user). Doing so offers several advantages. Some of the discussed advantages are scalability, low latency, reducing network traffic, and increasing efficiency. The chapter then explains the architecture to implement a fog network, followed by its applications. Some commercial fog products are also discussed, and a use case for an airport security system is presented.

EdgeCloud

In the recent years, edge/fog computing is gaining greater importance and has led to the deployment of many smart devices and application frameworks which support real-time data processing. Edge computing is an extension to existing cloud computing environment and focuses on improving the reliability, scalability, and resource efficiency of cloud by abolishing the need for processing all the data at one time and thus increasing the bandwidth of a network. Edge computing can complement cloud computing in a way leading to a novel architecture which can benefit from both edge and cloud resources. This kind of resource architecture may require resource continuity provided that the selection of resources for executing a service in cloud is independent of physical location. Hence, this research work proposes a novel architecture called “EdgeCloud,” which is a distributed management system for resource continuity in edge to cloud computing environment. The performance of the system is evaluated by considering a traffic management service example mapped into the proposed layered framework.

Fog Computing Application Deployment and Management

Fog computing enhances cloud computing to be closer to the processes that act on IOT devices. Fogging was introduced to overcome the cloud computing paradigm which was not able to address some services, applications, and other limitations of cloud computing such as security aspects, bandwidth, and latency. Fog computing provides the direct correlation with the internet of things. IBM and CISCO are linking their concepts of internet of things with the help of fog computing. Application services are hosted on the network edge. It improves the efficiency and reduces the amount of data that is transferred to the cloud for analysis, storage, and processing. Developers write the fog application and deploy it to the access points. Several applications like smart cities, healthcare domain, pre-processing, and caching applications have to be deployed and managed properly.

Fog Computing and Its Challenges

In recent times, the number of internet of things (IoT) devices/sensors increased tremendously. To support the computational demand of real-time latency-sensitive applications of largely geo-distributed IoT devices/sensors, a new computing paradigm named fog computing has been introduced. In this chapter, the authors will introduce fog computing, its difference in comparison to cloud computing, and issues related to fog. Among the three issues (i.e. service, structural, and security issues), this chapter scrutinizes and comprehensively discusses the service and structural issues also providing the service level objectives of the fog. They next provide various algorithms for computing in fog, the challenges faced, and future research directions. Among the various uses of fog, two scenarios are put to use.

Software Engineering in Internet of Things

This chapter gives an overall role of software engineering in internet of things domain. In this chapter, the following topics are included: glimpse of complete software engineering, main motivation of IoT, how IoT evolved, usage of software engineering concepts in IoT, role of CBSE in IoT, role of aspect-oriented software engineering, heterogeneous boards in designing IoT systems, importance of integration phase in IoT systems, comparison of different IDEs of IoT, testing of IoT systems, and a case study illustrating all the concepts for online blood banking system and forest fire detection.

Confidentiality and Safekeeping Problems and Techniques in Fog Computing

Fog computing is an extension of cloud computing, and it is one of the most important architypes in the current world. Fog computing is like cloud computing as it provides data storage, computation, processing, and application services to end-users. In this chapter, the authors discuss the security and privacy issues concerned with fog computing. The issues present in cloud are also inherited by fog computing, but the same methods available for cloud computing are not applicable to fog computing due to its decentralized nature. The authors also discuss a few real-time applications like healthcare systems, intelligent food traceability, surveillance video stream processing, collection, and pre-processing of speech data. Finally, the concept of decoy technique and intrusion detection and prevention technique is covered.