Modeling IoT Smart Home Network

The purpose of the article is to present the process of modeling the IoT smart home (SH) network, which combines both user needs and efficiency requirements. The use of Alibaba cloud platform, which reduces complexity and development time, reduces costs, was justified in the project of building the IoT SH network. The structure of this platform is given, its main components are considered and an algorithm for its configuration is given. MQTT is used as an access protocol in the IoT SH network to achieve fast and reliable data transmission. Open source code, reliability, simplicity and other characteristics justify the choice of this data transfer protocol. Modeling of the network IoT SH is based on the knowledge gained in the process of practical implementation. First, the online problems of the system are tested, after the system is able to work after modification and debugging of programs, a street lamp is used as an example to create an instance of an IoT SH network on a cloud platform. The process of creating an example of an IoT SH network is described in detail in steps, in which data from a street lamp is transmitted to a cloud platform, processed there, and then displayed on a mobile device. A mobile phone was used to implement two-way interaction, simulate the sensor of the IoT SH network and display the results. The algorithms for configuring the platform, modeling the sensor and creating an object model of the device of the IoT SH network are given. For some modern control systems, this system is compatible and suitable for a larger number of cases, which contributes to the development of intelligent control in the IoT network.The purpose of the article is to present the process of modeling the IoT smart home (SH) network, which combines both user needs and efficiency requirements. The use of Alibaba cloud platform, which reduces complexity and development time, reduces costs, was justified in the project of building the IoT SH network. The structure of this platform is given, its main components are considered and an algorithm for its configuration is given. MQTT is used as an access protocol in the IoT SH network to achieve fast and reliable data transmission. Open source code, reliability, simplicity and other characteristics justify the choice of this data transfer protocol. Modeling of the network IoT SH is based on the knowledge gained in the process of practical implementation. First, the online problems of the system are tested, after the system is able to work after modification and debugging of programs, a street lamp is used as an example to create an instance of an IoT SH network on a cloud platform. The process of creating an example of an IoT SH network is described in detail in steps, in which data from a street lamp is transmitted to a cloud platform, processed there, and then displayed on a mobile device. A mobile phone was used to implement two-way interaction, simulate the sensor of the IoT SH network and display the results. The algorithms for configuring the platform, modeling the sensor and creating an object model of the device of the IoT SH network are given. For some modern control systems, this system is compatible and suitable for a larger number of cases, which contributes to the development of intelligent control in the IoT network

A Security Threat Analysis of Smart Home Network with Vulnerable Dynamic Agents

This chapter presents a security analysis of a smart home network containing vulnerable dynamic agents in the form of smart toys. As a case study, a smart toy is used as an example of an Internet of Things (IoT) device which could be potentially used as a vector into the smart home network. This chapter discusses a threat model for smart home security with a focus on the smart toy as an entry point into the network and what a threat actor could potentially achieve through this relatively new type of threat to the home

A Smart Home Network for Proactive Users

According to the European Strategy Energy Technology (SET) Plan, the resident-user engagement into thenational energy strategy is pivotal, as reported by the Challenge 1st: “Active consumer is at the centre of the energy system”. The Italian Ministry of Economic Development and ENEA have entered into a Program Agreement for the execution of the research and development lines of General Interest for the NationalElectricity System. In particular, as part of the “Development of an integrated model of the Urban Smart District” project. An experimental demonstration of a Smart Home network is being carried out in the Centocelle district of Rome and called “Smart Home Centocelle”. The project was developed in an informal settlement, which shares a common background with likewise urban settings, such as a lack of public transportation convenience or enjoyable public spaces and average quality housing, whereas people who adhered to the project have a medium-high education level and proved to be sensitive to alternative and more sustainable energy sources. Our research has examined the deployment progress made so far, gathering and analysing all the information to assess how the project applications could affect various quality-of-life dimensions: safety, health, environmental quality and personal comfort perception, social connectedness and the cost of living, above all

A Redundancy-based Security Model for Smart Home

Recent developments in smart devices, Cloud Computing and Internet of Things (IoT) are introducing network of intelligent devices. These intelligent devices can be used to develop smart home network. The home appliance in a smart home forms an ad-hoc network. A smart home network architecture can be exploited by compromising the devices it is made up of. Various malicious activities can be performed through such exploitation. This paper presents a security approach to combat this. By using a collaborative and redundant security approach, the ad-hoc network of a smart home would be able to prevent malicious exploitation. The security approach discussed in this paper is a conceptual representation on the proposed security model for smart home networks

Encrypted Network Traffic Classification and Resource Allocation with Deep Learning in Software Defined Network

The climate has changed absolutely in every area in just a few years as digitized, making high-speed internet service a significant need in the future. Future Internet is supposed to face exponential growth in traffic, and highly complicated infrastructure, threatening to make conventional NTC approaches unreliable and even counterproductive. In recent days, AI Stimulated state-of-the-art breakthroughs with the ability to tackle extensive and multifarious challenges, and the network community is initiated by considering the NTC prototype from legacy rule-based towards a novel AI-based. Design and execution are applied to interdisciplinary become more essential. A smart home network supports various applications and smart devices within the proposed work, including e-health devices, regular computing devices, and home automation devices. Many devices accessible through the Internet by Home GateWay for Congestion (HGC) in a smart home. Throughout this paper, a Software-Defined Network Home GateWay for Congestion (SDNHGC) architecture for improved management of remote smart home networks and protection of the significant networks SDN controller. It enables effective network capacity regulation, focused on real-time traffic analysis and core network resource allocation. It cannot control the Network in dispersed smart homes. Our innovative SDNHGC expands power across the connectivity network, a smart home network enabling improved end-to-end monitoring of networks. The planned SDNHGC directly will gain centralized device identification by classifying traffic through a smart home network. Several of the current traffic classifications approach, checking deep packets, cannot have this real-time device knowledge for encrypted data to solve this issue

Datanet: Deep Learning Based Encrypted Network Traffic Classification in SDN Home Gateway

A smart home network will support various smart devices and applications, e.g., home automation devices, E-health devices, regular computing devices, and so on. Most devices in a smart home access the Internet through a home gateway (HGW). In this paper, we propose a software-defined network (SDN)-HGW framework to better manage distributed smart home networks and support the SDN controller of the core network. The SDN controller enables efficient network quality-of-service management based on real-time traffic monitoring and resource allocation of the core network. However, it cannot provide network management in distributed smart homes. Our proposed SDN-HGW extends the control to the access network, i.e., a smart home network, for better end-to-end network management. Specifically, the proposed SDN-HGW can achieve distributed application awareness by classifying data traffic in a smart home network. Most existing traffic classification solutions, e.g., deep packet inspection, cannot provide real-time application awareness for encrypted data traffic. To tackle those issues, we develop encrypted data classifiers (denoted as DataNets) based on three deep learning schemes, i.e., multilayer perceptron, stacked autoencoder, and convolutional neural networks, using an open data set that has over 200 000 encrypted data samples from 15 applications. A data preprocessing scheme is proposed to process raw data packets and the tested data set so that DataNet can be created. The experimental results show that the developed DataNets can be applied to enable distributed application-aware SDN-HGW in future smart home networks

Modeling IoT Smart Home Network

The purpose of the article is to present the process of modeling the IoT smart home (SH) network, which combines both user needs and efficiency requirements. The use of Alibaba cloud platform, which reduces complexity and development time, reduces costs, was justified in the project of building the IoT SH network. The structure of this platform is given, its main components are considered and an algorithm for its configuration is given. MQTT is used as an access protocol in the IoT SH network to achieve fast and reliable data transmission. Open source code, reliability, simplicity and other characteristics justify the choice of this data transfer protocol. Modeling of the network IoT SH is based on the knowledge gained in the process of practical implementation. First, the online problems of the system are tested, after the system is able to work after modification and debugging of programs, a street lamp is used as an example to create an instance of an IoT SH network on a cloud platform. The process of creating an example of an IoT SH network is described in detail in steps, in which data from a street lamp is transmitted to a cloud platform, processed there, and then displayed on a mobile device. A mobile phone was used to implement two-way interaction, simulate the sensor of the IoT SH network and display the results. The algorithms for configuring the platform, modeling the sensor and creating an object model of the device of the IoT SH network are given. For some modern control systems, this system is compatible and suitable for a larger number of cases, which contributes to the development of intelligent control in the IoT network

Аналіз технологій бездротового доступу мережі управління розумним будинком

Мета роботи – обґрунтування побудови мережі розумного будинку, аналіз її характеристик та порівняння технологій для управління розумним будинком. Розглянуті основні технології бездротового доступу для розгортання мережі розумного будинку, проведено їх аналіз.The purpose of the work is to substantiate the construction of a smart home network, analyze its characteristics and compare technologies for smart home management. The main technologies of wireless access for the deployment of a smart home network are considered, their analysis is carried out

GHOST - safe-guarding home IoT environments with personalised real-time risk control

We present the European research project GHOST, (Safe-guarding home IoT environments with personalised real-time risk control), which challenges the traditional cyber security solutions for the IoT by proposing a novel reference architecture that is embedded in an adequately adapted smart home network gateway, and designed to be vendor-independent. GHOST proposes to lead a paradigm shift in consumer cyber security by coupling usable security with transparency and behavioural engineering