scholarly journals An ECPABE Algorithm and RPLS Protocol for Secured Transmission on IOT based Environment

2019 ◽  
Vol 8 (3) ◽  
pp. 6736-6743
Keyword(s):  
Smart Home ◽  
Security Analysis ◽  
Automation System ◽  
Security Level ◽  
The Novel ◽  
Large Area ◽  
Security Issues ◽  
Home Automation System ◽  
Main Thing ◽  
The Internet Of Things

WSN include Internet Protocol (IP) which extends the Internet of Things (IoT) related to routine life. Security is main thing in emerging technology for IOT application. Therefore, WSN has lot of issues which include: (i) To promote the sensor devices efficiently during the transmission of data for consuming low energy (ii) To resolve the security issues of data faced at the time of transmission through large area of networks. In this paper, to overcome the above issues the novel scheme is proposed. A Secure based smart home automation system in IOT application is built for this study. Furthermore, the data transmission utilizes the energy using Low power consumption protocol using RPLS and to secure the data a data security scheme ECPABE have been proposed here. The performance of proposed protocol shows the limited energy consumes and proposed ECPABE provides better security level to IoT data than the existing schemes. The results show the proposed scheme security analysis is efficient as well as secure

scholarly journals A conceptual model to support security analysis in the internet of things

2017 ◽  
Vol 14 (2) ◽  
pp. 557-578 ◽  
Author(s):  
Orestis Mavropoulos ◽  
Haralambos Mouratidis ◽  
Andrew Fish ◽  
Emmanouil Panaousis ◽  
Christos Kalloniatis
Keyword(s):  
Internet Of Things ◽  
Conceptual Model ◽  
Smart Home ◽  
Security Analysis ◽  
Decision Makers ◽  
Small Scale ◽  
Security Issues ◽  
The World ◽  
Main Driver ◽  
The Internet Of Things

This paper proposes a conceptual model to support decision makers during security analysis of Internet of Things (IoT) systems. The world is entering an era of ubiquitous computing with IoT being the main driver. Taking into account the scale of IoT, the number of security issues that are arising are unprecedented. Both academia and industry require methodologies that will enable reasoning about security in IoT system in a concise and holistic manner. The proposed conceptual model addresses a number of challenges in modeling IoT to support security analysis. The model is based on an architecture-oriented approach that incorporates sociotechnical concepts into the security analysis of an IoT system. To demonstrate the usage of the proposed conceptual model, we perform a security analysis on a small scale smart home example.

scholarly journals IoT Traffic: Modeling and Measurement Experiments

IoT ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 140-162
Author(s):  
Hung Nguyen-An ◽  
Thomas Silverston ◽  
Taku Yamazaki ◽  
Takumi Miyoshi
Keyword(s):  
Smart Home ◽  
Large Scale ◽  
Traffic Modeling ◽  
The Novel ◽  
Network Behavior ◽  
Performance Accuracy ◽  
Traffic Generator ◽  
Multiple Devices ◽  
Iot Devices ◽  
The Internet Of Things

We now use the Internet of things (IoT) in our everyday lives. The novel IoT devices collect cyber–physical data and provide information on the environment. Hence, IoT traffic will count for a major part of Internet traffic; however, its impact on the network is still widely unknown. IoT devices are prone to cyberattacks because of constrained resources or misconfigurations. It is essential to characterize IoT traffic and identify each device to monitor the IoT network and discriminate among legitimate and anomalous IoT traffic. In this study, we deployed a smart-home testbed comprising several IoT devices to study IoT traffic. We performed extensive measurement experiments using a novel IoT traffic generator tool called IoTTGen. This tool can generate traffic from multiple devices, emulating large-scale scenarios with different devices under different network conditions. We analyzed the IoT traffic properties by computing the entropy value of traffic parameters and visually observing the traffic on behavior shape graphs. We propose a new method for identifying traffic entropy-based devices, computing the entropy values of traffic features. The method relies on machine learning to classify the traffic. The proposed method succeeded in identifying devices with a performance accuracy up to 94% and is robust with unpredictable network behavior with traffic anomalies spreading in the network.

scholarly journals Internet of Things-Based Intelligent Smart Home Control System

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Olutosin Taiwo ◽  
Absalom E. Ezugwu
Keyword(s):  
Machine Learning ◽  
Mobile Application ◽  
Smart Home ◽  
Human Life ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Automation System ◽  
Home Automation ◽  
Area Of Interest ◽  
Home Automation System

The smart home is now an established area of interest and research that contributes to comfort in modern homes. With the Internet being an essential part of broad communication in modern life, IoT has allowed homes to go beyond building to interactive abodes. In many spheres of human life, the IoT has grown exponentially, including monitoring ecological factors, controlling the home and its appliances, and storing data generated by devices in the house in the cloud. Smart home includes multiple components, technologies, and devices that generate valuable data for predicting home and environment activities. This work presents the design and development of a ubiquitous, cloud-based intelligent home automation system. The system controls, monitors, and oversees the security of a home and its environment via an Android mobile application. One module controls and monitors electrical appliances and environmental factors, while another module oversees the home’s security by detecting motion and capturing images. Our work uses a camera to capture images of objects triggered by their motion being detected. To avoid false alarms, we used the concept of machine learning to differentiate between images of regular home occupants and those of an intruder. The support vector machine algorithm is proposed in this study to classify the features of the image captured and determine if it is that of a regular home occupant or an intruder before sending an alarm to the user. The design of the mobile application allows a graphical display of the activities in the house. Our work proves that machine learning algorithms can improve home automation system functionality and enhance home security. The work’s prototype was implemented using an ESP8266 board, an ESP32-CAM board, a 5 V four-channel relay module, and sensors.

scholarly journals Home Automation with Intruder Detection and Energy Control

2021 ◽  
Vol 9 (VI) ◽  
pp. 3473-3480
Author(s):  
M. Niharika
Keyword(s):  
Light Intensity ◽  
Smart Home ◽  
Security System ◽  
Automation System ◽  
Home Automation ◽  
Energy Control ◽  
Intruder Detection ◽  
Alert Message ◽  
Home Automation System

In previous project we made a home automation system, where we can control our appliances through Blynk app and Google assistant with the help of IFTTT. As an extension we will provide feedback to user whether the appliance is on or off. We will also use sensors like LDR for measuring light intensity in this project to make it smart. We will also include security system where in we have sensors to doors and windows and give buzzer along with an alert message to the user. On a whole we will provide a smart home automation system.

scholarly journals Smart Home Environment Future Challenges and Issues - A Survey

2021 ◽  
Vol 3 (1) ◽  
pp. 1-8
Author(s):  
Sathesh ◽  
Yasir Babiker Hamdan
Keyword(s):  
Energy Management ◽  
Home Environment ◽  
Smart Home ◽  
Automation System ◽  
Home Automation ◽  
Negative Effects ◽  
Research Article ◽  
Home Energy Management ◽  
Smart Home Environment ◽  
Home Automation System

The smart home automation is that the exploitation internet enabled devices remotely and mechanically management appliances such as lighting, heating system and security measures in and around your home. This papers talks about relative emission effects in Home Energy Management. Also the result outcome is that consumption of the electricity will be reduced towards green environment. Moreover, the research paper is considering the analysis of calculate the negative effects in environment due to full home automation system. While calculating these negative effects, the Life Cycle Assessment (LCA) should be in sum total. This study uses to analysis the electricity consumption for environment impact of Home Energy Management system (HEMs). The research article discusses home automation system consumes the energy for different devices connected for smart home. The maximum energy consumption in smart home network is smart plugs due to an uninterrupted supply. Therefore this research article comprises about home automation energy management that shows the balance energy consumption between the devices in a regular interval. Also this research article provides a future challenge tasks in security issues in smart home environment. Also the perception for smart home environment focuses the Interoperability, Reliability, Integration of smart homes and term privacy in context, term security and privacy vulnerabilities to smart home.

Smart Home automation system using IR, bluetooth, GSM and android

2017 ◽  
Author(s):  
Anuja Shinde ◽  
Shobha Kanade ◽  
Namrata Jugale ◽  
Abhijeet Gurav ◽  
Rambabu A. Vatti ◽  
...  
Keyword(s):  
Smart Home ◽  
Automation System ◽  
Home Automation ◽  
Home Automation System
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