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About this book

This book constitutes the refereed proceedings of the Second EAI International Conference on Smart Grid and Internet of Things, SGIoT 2018, held in Niagara Falls, Canada, Ontario, in July 2018. The 14 papers presented were carefully reviewed and selected from 25 submissions and present research results on how to achieve more efficient use of resources based largely on IoT-based machine-to-machine interactions in the smart grit communication networks. The smart grid also encompasses IoT technologies, which monitor transmission lines, manage substations, integrate renewable energy generation (e.g., solar or wind), and utilize hybrid vehicle batteries. Through these technologies, the authorities can smartly identify outage problems, and intelligently schedule the power generation and delivery to the customers

Table of Contents


Smart Grid and Internet of Things


An Implementation of Harmonizing Internet of Things (IoT) in Cloud

With the evolution of Internet of Things (IoT), everything is going to be connected to the Internet and the data produced by IoT, will be used for different purposes. Since IoT generates huge amount of data, we need some scalable storage to store and compute the data sensed from the sensors. To overcome this issue, we need the integration of cloud and IoT so that the data might be stored and computed in a scalable environment. Harmonization of IoT in Cloud might be a novel solution in this regard. IoT devices will interact with each other using Constrained Application Protocol (CoAP). All the IoT devices will be assigned IP addresses for unique identification. In this paper, we have implemented harmonizing IoT in Cloud. We have used CoAP to get things connected to each other through the Internet. For the implementation we have used two sensors, fire detector and the sensor attached with the door which is responsible for opening the door. Thus the proposed implementation will be storing and retrieving the sensed data from the cloud. We have also compared our implementation with different parameters. The comparison shows that our implementation significantly improves the performance compared to the existing system.
Md. Motaharul Islam, Zaheer Khan, Yazed Alsaawy

IoT Big Data Analytics with Fog Computing for Household Energy Management in Smart Grids

Smart homes generate a vast amount of data measurements from smart meters and devices. These data have all the velocity and veracity characteristics to be called as Big Data. Meter data analytics holds tremendous potential for utilities to understand customers’ energy consumption patterns, and allows them to manage, plan, and optimize the operation of the power grid efficiently. In this paper, we propose a unified architecture that enables innovative operations for near real-time processing of large fine-grained energy consumption data. Specifically, we propose an Internet of Things (IoT) big data analytics system that makes use of fog computing to address the challenges of complexities and resource demands for near real-time data processing, storage, and classification analysis. The design architecture and requirements of the proposed framework are illustrated in this paper while the analytics components are validated using datasets acquired from real homes.
Shailendra Singh, Abdulsalam Yassine

Secured Cancer Care and Cloud Services in IoT/WSN Based Medical Systems

In recent years, the Internet of Things (IoT) has constituted a driving force of modern technological advancement, and it has become increasingly common as its impacts are seen in a variety of application domains, including healthcare. IoT is characterized by the interconnectivity of smart sensors, objects, devices, data, and applications. With the unprecedented use of IoT in industrial, commercial and domestic, it becomes very imperative to harness the benefits and functionalities associated with the IoT technology in (re)assessing the provision and positioning of healthcare to ensure efficient and improved healthcare delivery. In this research, we are focusing on two important services in healthcare systems, which are cancer care services and business analytics/cloud services. These services incorporate the implementation of an IoT that provides solution and framework for analyzing health data gathered from IoT through various sensor networks and other smart devices in order to improve healthcare delivery and to help health care providers in their decision-making process for enhanced and efficient cancer treatment. In addition, we discuss the wireless sensor network (WSN), WSN routing and data transmission in the healthcare environment. Finally, some operational challenges and security issues with IoT-based healthcare system are discussed.
Adeniyi Onasanya, Maher Elshakankiri

Privacy Preserving for Location-Based IoT Services

In recent years, the applications of location-based Internet of Things (IoT) services change the way of people’s lives and works. However, these applications may disclose some private location information of users due to lack of privacy protection mechanism, which could result in serious security issues. To protect users’ confidential data, an efficient and secure private proximity testing (ESPT) scheme is designed for location-based IoT services to improve the efficiency while maintaining the privacy of the location of the users. The proposed scheme enables a user to query a service provider whether some people are within a given search range without disclosing any private location information of the user. The security analysis and the simulation results demonstrate that the proposed scheme could not only implement a privacy-preserving proximity test, but also has less computational overheads.
Yue Qiu, Maode Ma

Smart Home Security Application Enabled by IoT:

Using Arduino, Raspberry Pi, NodeJS, and MongoDB
Recent advances in smartphones and affordable open-source hardware platforms have enabled the development of low-cost architectures for IoT-enabled home automation and security systems. These systems usually consist of a sensing and actuating layer that is made up of sensors such as PIR (Passive Infra-red) sensors, also known as motion sensors; temperature sensors; smoke sensors, and web cameras for security surveillance. These sensors, smart electrical appliances and other IoT devices connect to the Internet through a home gateway. This paper lays out architecture for a cost effective “smart” door sensor that will inform a user through an Android application, of door open events in a house or office environment. The proposed architecture uses an Arduino-compatible Elegoo Mega 2560 microcontroller (MCU) board along with the Raspberry Pi 2 board for communicating with a web server that implements a RESTful API. Several programming languages are used in the implementation and further applications of the door sensor are discussed as well as some of its shortcomings such as possible interference from other RF (Radio Frequency) devices.
Chad Davidson, Tahsin Rezwana, Mohammad A. Hoque

An MQTT-Based Scalable Architecture for Remote Monitoring and Control of Large-Scale Solar Photovoltaic Systems

This paper presents a novel IoT-based architecture that utilizes IoT communication, software, and hardware technologies to enable real-time monitoring and management of solar photovoltaic systems at a large scale. The system enables stakeholders to remotely control and monitor the photovoltaic systems and evaluate the effect of various environmental factors such as humidity, temperature, and dust. The system was implemented and evaluated in terms of network delay and resource consumption. MQTT demonstrated an average network delay of less than 1 s, proving the architecture to be ideal for solar and smart grid monitoring systems. At the hardware, the evaluation showed the hardware to consume about 3% of the panel’s capacity, while the application also utilized a very small percentage of the CPU. This lead to the conclusion that the proposed architecture is best deployed using low-cost constrained edge devices where a combination of efficient MQTT communication and low resources consumption makes the system cost-effective and scalable.
Salsabeel Shapsough, Mohannad Takrouri, Rached Dhaouadi, Imran Zualkernan

A Smart Meter Firmware Update Strategy Through Network Coding for AMI Network

With the introduction of communication infrastructure into the traditional power grids, smart power grids are emerging to meet the future electricity demands. In smart grid, advanced metering infrastructure (AMI) is one of the main components that enables bi-directional communication between home area networks and utility providers. In an AMI network, one of the crucial operations is to update the firmware of the smart meters. In this paper, we propose a new forwarding strategy for the firmware updates in AMI network. Our simulation results show that the completion time of the smart meter firmware update process can be reduced significantly by using the proposed new strategy.
Syed Qaisar Jalil, Stephan Chalup, Mubashir Husain Rehmani

Protected Bidding Against Compromised Information Injection in IoT-Based Smart Grid

The smart grid is regarded as one of the important application field of the Internet of Things (IoT) composed of embedded sensors, which sense and control the behavior of the energy world. IoT is attractive for features of grid catastrophe prevention and decrease of grid transmission line and reliable load fluctuation control. Automated Demand Response (ADR) in smart grids maintain demand-supply stability and in regulating customer side electric energy charges. An important goal of IoT-based demand-response using IoT is to enable a type of DR approach called automatic demand bidding (ADR-DB). However, compromised information board can be injected into during the DR process that influences the data privacy and security in the ADR-DB bidding process, while protecting privacy oriented consumer data is in the bidding process is must. In this work, we present a bidding approach that is secure and private for incentive-based ADR system. We use cryptography method instead of using any trusted third-party for the security and privacy. We show that proposed ADR bidding are computationally practical through simulations performed in three simulation environments.
Md Zakirul Alam Bhuiyan, Mdaliuz Zaman, Guojun Wang, Tian Wang, Md. Arafat Rahman, Hai Tao

A Chain Based Signature Scheme for Uplink and Downlink Communications in AMI Networks

Smart grid is an electric infrastructure that makes extensive use of communication and information technology making it a surface for numerous cyber-security threats. In this research, we propose an authentication scheme for downlink and uplink communications in the advanced metering infrastructure network. The proposal is based on chain based signature with some modifications to tackle its computation and storage overhead. Besides, the proposal integrates symmetric encryption with the signature scheme to ensure data privacy and confidentiality. Our analysis proves that the proposed scheme is resilient against numerous known attacks and is efficient in terms of computation cost and ciphertext size.
Samer Khasawneh, Michel Kadoch

Robustness Situations in Cases of Node Failure and Packet Collision Enabled by TCNet: Trellis Coded Network - A New Algorithm and Routing Protocol

This research exploits the new concept of route discovery using TCNet - Trellis Coded Networks an algorithm and routing protocol based on convolutional codes to be used in WSNs an important infrastructure of the Internet of Things (IoT) architecture. This work shows the robustness of the TCNet algorithm in making decisions in cases of nodes failure and packages collisions, taking advantage of the regeneration capacity of the trellis. This proposal innovates in making decisions on the node itself, without the need of signaling messages such as “Route Request”, “Route Reply” or the RTS and CTS. TCNet uses low complexity Finite State Machine (FSM) network nodes (“XOR” gates and shift registers), eliminating the use of any routing tables by means of Trellis decoding, where the sequence of states of the FSM, corresponds to a network route, and can be chosen based on different optimization criteria.
Diogo F. Lima Filho, José R. Amazonas

Applications and Technologies


Effectiveness of Hard Clustering Algorithms for Securing Cyber Space

In the era of big data, it is more challenging than before to accurately identify cyber attacks. The characteristics of big data create constraints for the existing network anomaly detection techniques. Among these techniques, unsupervised algorithms are superior than the supervised algorithms for not requiring training data. Among the unsupervised techniques, hard clustering is widely accepted for deployment. Therefore, in this paper, we investigated the effectiveness of different hard clustering techniques for identification of a range of state-of-the-art cyber attacks such as backdoor, fuzzers, worms, reconnaissance etc. from the popular UNSW-NB15 dataset. The existing literature only provides the accuracy of identification of the all types of attacks in generic fashion, however, our investigation ensures the effectiveness of hard clustering for individual attacks. The experimental results reveal the performance of a number of hard clustering techniques. The insights from this paper will help both the cyber security and data science community to design robust techniques for securing cyber space.
Sakib Mahtab Khandaker, Afzal Hussain, Mohiuddin Ahmed

On Data Driven Organizations and the Necessity of Interpretable Models

It this paper we investigate data driven organizations in the context of predictive models, we also reflect on the need for interpretability of the predictive models in such a context. By investigating a specific use-case, the maintenance offer from a heavy truck manufacturer, we explore their current situation trying to identify areas that needs change in order to go from the current situation towards a more data driven and agile maintenance offer. The suggestions for improvements are captured in a proposed data driven framework for this type of business. The aim of the paper is that the suggested framework can inspire and start further discussions and investigations into the best practices for creating a data driven organization, in businesses facing similar challenges as in the presented use-case.
Tony Lindgren

A Multi-factor Authentication Method for Security of Online Examinations

Security of online examinations is the key to success of remote online learning. However, it faces many conventional and non-conventional security threats. Impersonation and abetting are rising non-conventional security threats, when a student invites a third party to impersonate or abet in a remote exam. This work proposed dynamic profile questions authentication to identify that the person taking an online test is the same who completed the course work. This is combined with remote proctoring to prevent students from taking help from a third party during exam. This research simulated impersonation and abetting attacks in remote online course and laboratory based control simulation to analyse the impact of dynamic profile questions and proctoring. The study also evaluated effectiveness of the proposed method. The findings indicate that dynamic profile questions are highly effective. The security analysis shows that impersonation attack was not successful.
Abrar Ullah, Hannan Xiao, Trevor Barker

Evaluation Metrics for Big Data Project Management

In this paper, we investigated the current scenario of big data project management followed by success criteria. Our research found that, the evaluation metrics are generic and no universal metric available for the big data projects. Therefore, we have proposed few evaluation metrics suitable for big data projects.
Munir Ahmad Saeed, Mohiuddin Ahmed


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