Design and Implementation of an IoT-Based Smart Home Security System

Hoque, Mohammad A.; Davidson, Chad

doi:10.2991/ijndc.k.190326.004

Cited by 73 publications

(36 citation statements)

References 25 publications

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“…Smart home is an application of IoT technology. The goal of the smart home environment is the integration of home automation and security so that the homeowner can also remotely control and monitor the environment [1,3,4]. As mentioned above, IoT devices have limited resources, resulting in their low computing power and low storage space.…”

Section: Methodsmentioning

confidence: 99%

“…The consumer market offers a huge number of IoT devices monitoring the home, such as light spots, lightbulbs, smart thermostats, motion sensors, smart locks, fire alarms, security cameras, even vacuum cleaners or robot lawnmowers. The advent of low-cost smart home environments has been made possible by falling prices for IoT sensors and other hardware, as well as the advent of cloud technologies [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

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Resistance of IoT Sensors against DDoS Attack in Smart Home Environment

Huraj

Šimon

Horák

2020

Sensors

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Smart devices along with sensors are gaining in popularity with the promise of making life easier for the owner. As the number of sensors in an Internet of Things (IoT) system grows, a question arises as to whether the transmission between the sensors and the IoT devices is reliable and whether the user receives alerts correctly and in a timely manner. Increased deployment of IoT devices with sensors increases possible safety risks. It is IoT devices that are often misused to create Distributed Denial of Service (DDoS) attacks, which is due to the weak security of IoT devices against misuse. The article looks at the issue from the opposite point of view, when the target of a DDoS attack are IoT devices in a smart home environment. The article examines how IoT devices and the entire smart home will behave if they become victims of a DDoS attack aimed at the smart home from the outside. The question of security was asked in terms of whether a legitimate user can continue to control and receive information from IoT sensors, which is available during normal operation of the smart home. The case study was done both from the point of view of the attack on the central units managing the IoT sensors directly, as well as on the smart-home personal assistant systems, with which the user can control the IoT sensors. The article presents experimental results for individual attacks performed in the case study and demonstrates the resistance of real IoT sensors against DDoS attack. The main novelty of the article is that the implementation of a personal assistant into the smart home environment increases the resistance of the user’s communication with the sensors. This study is a pilot testing the selected sensor sample to show behavior of smart home under DDoS attack.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Resistance of IoT Sensors against DDoS Attack in Smart Home Environment

Huraj

Šimon

Horák

2020

Sensors

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“…Hoque and Davidson [27] presented a smart home security system framework, which uses a smart door sensor with radiofrequency transceivers for communication. e user receives an alert about the opening or closing of the door through an Android application.…”

Section: Related Literaturementioning

confidence: 99%

Internet of Things-Based Intelligent Smart Home Control System

Taiwo

Ezugwu

2021

Security and Communication Networks

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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.

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“…A blockchain-based smart home gateway network was proposed in [5] with the aid of the blockchain method provided measures for potential attacks on the gateway of smart homes. In addition to protecting transparency and ensuring security for each smart sensor activity, a novel secure wireless mechanism utilizing Blockchain technology was proposed [6].…”

Section: Related Workmentioning

confidence: 99%

Scalable and Secure Gradient Smart Dempster Shafer Reputation for Development of Smart Cities

Ayothi¹,

Duela²,

Ramesh³

et al. 2021

Preprint

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Over the last decade, blockchain has been considered an encouraging solution to secure distributed ledgers. Moreover, with the introduction of a pseudonymous payment method without a centralized database or authoritative person, blockchain has also evolved as the future generation for online payment system. However, with the eruption of a large scale database, scalability has also become a demanding issue. In addition to the obstacle mentioned above, challenges like security and scalability stop accelerated adjustments for the development of smart cities. Without directing this essential scalability and privacy issue, such an encouraging method may not help develop smart cities. This paper bestows a measure to analyze both scalability and security aspects of existing blockchain methods with applications of smart city networks. The proposed method is known as Gradient Smart Load Balancer and Blockchain Dempster Shafer Reputation (GSLB-BDSR). Gradient Smart Load Balancer is designed so that even though with the increase in the number of participating sensors, the load is said to balance by applying gradient function, therefore ensuring scalability. Next, to cover the security aspect, with the aid of scalable blocks in the blockchain network, a Blockchain Dempster Shafer Reputation model is proposed. Evaluation outcomes of proposed security solutions outperform conventional solutions.

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Design and Implementation of an IoT-Based Smart Home Security System

Cited by 73 publications

References 25 publications

Resistance of IoT Sensors against DDoS Attack in Smart Home Environment

Resistance of IoT Sensors against DDoS Attack in Smart Home Environment

Internet of Things-Based Intelligent Smart Home Control System

Scalable and Secure Gradient Smart Dempster Shafer Reputation for Development of Smart Cities

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