A Hybrid Intrusion Detection System for Smart Home Security

Alghayadh, Faisal; Debnath, Debatosh

doi:10.1109/eit48999.2020.9208296

Cited by 17 publications

(8 citation statements)

References 29 publications

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“…On the other hand, there are proposals where the control follows a non-reactive design, its main application is to predict solutions taking into account the inhabitants behavior to make the environment cozy and comfortable [ 20 ] and based on the user interaction with the system, so can it react when an intrusion to the home has occurred [ 21 ] or learning from the specific energy source load shifting characteristics as can be home renewable energy (wind turbines, solar panels, batteries) [ 22 , 23 ] or automatically deal with the random demand of consumers [ 24 ].…”

Section: Related Workmentioning

confidence: 99%

Design and Implementation of the E-Switch for a Smart Home

García-Vázquez

Guerrero-Osuna

Ornelas-Vargas

et al. 2021

Sensors

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As the development of systems in smart homes is increasing, it is of ever-increasing importance to have data, which artificial intelligence methods and techniques can apply to recognize activities and patterns or to detect anomalies, with the aim of reducing energy consumption in the main home domestic services, and to offer users an alternative in the management of these resources. This paper describes the design and implementation of a platform based on the internet of things and a cloud environment that allows the user to remotely control and monitor Wi-Fi wireless e-switch in a home through a mobile application. This platform is intended to represent the first step in transforming a home into a smart home, and it allows the collection and storage of the e-switch information, which can be used for further processing and analysis.

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Section: Related Workmentioning

confidence: 99%

Design and Implementation of the E-Switch for a Smart Home

García-Vázquez

Guerrero-Osuna

Ornelas-Vargas

et al. 2021

Sensors

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“…The decision layer is structured to determine the type of behavior obtained or stored in the information layer. As such, all four layers work closely together in the sense that the activities associated with one layer support the others [13]…”

Section: Smart Home Technologymentioning

confidence: 99%

“…In a smart home environment, modern wireless networks, computers, and sensors face various security threats, and machine learning is seen as an ideal solution to this problem. Using different learning algorithms train sensors, and computers without any explicit programming, machine learning technology takes advantage of artificial intelligence using various learning algorithms train sensors, and devices without any explicit programming [13] (HID) with a two-tiered intrusion detection system as shown in Figure 1. The first tier contains the machine learning technique.…”

Section: Introductionmentioning

confidence: 99%

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A Hybrid Intrusion Detection System for Smart Home Security Based on Machine Learning and User Behavior

Alghayadh¹,

Debnath²

2021

AIT

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With technology constantly becoming present in people's lives, smart homes are increasing in popularity. A smart home system controls lighting, temperature, security camera systems, and appliances. These devices and sensors are connected to the internet, and these devices can easily become the target of attacks. To mitigate the risk of using smart home devices, the security and privacy thereof must be artificially smart so they can adapt based on user behavior and environments. The security and privacy systems must accurately analyze all actions and predict future actions to protect the smart home system. We propose a Hybrid Intrusion Detection (HID) system using machine learning algorithms, including random forest, Xgboost, decision tree, K-nearest neighbors, and misuse detection technique.

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“…Blockchains have the advantage of being capable of enhancing security through verification between nodes, which makes forgery difficult. Consequently, research using blockchain techniques to develop robust security algorithms is actively underway [9][10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Design and Hardware Implementation of a Simplified DAG-Based Blockchain and New AES-CBC Algorithm for IoT Security

Lee

Sim

2021

Electronics

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Recently, to enhance the security of the Internet of Things (IoT), research on blockchain-based encryption algorithms has been actively conducted. However, because blockchains have complex structures and process large amounts of data, there are still many difficulties in using the conventional blockchain-based encryption algorithms in an IoT system that must have low power consumption and be ultra-lightweight. In this study, to address these problems (1) we simplified the conventional Directed Acyclic Graph (DAG)-based blockchain structure, and (2) we proposed a new Advanced Encryption Standard (AES)-Cipher Block Chaining (CBC) algorithm with enhanced security by periodically changing the secret key and initialization vector (IV) in the conventional AES-CBC encryption algorithm. Because the DAG, which is the conventional blockchain structure, randomly transmits data to multiple blocks, there may be overlapping blocks, and the quantity of transmitted data is not limited; thus, the time and power consumption for encryption and decryption increase. In this study, a simplified DAG was designed to address these problems so that packets can be transmitted only to three blocks, without overlapping. Finally, to verify the effectiveness of the algorithm proposed in this paper, an IoT system consisting of 10 clients and one server was implemented in hardware, and an experiment was conducted. Through the experiment, it was confirmed that when the proposed AES-CBC algorithm was used, the time taken and the amount of power consumed for encryption and decryption were reduced by about 20% compared to the conventional AES-CBC algorithm.

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A Hybrid Intrusion Detection System for Smart Home Security

Cited by 17 publications

References 29 publications

Design and Implementation of the E-Switch for a Smart Home

Design and Implementation of the E-Switch for a Smart Home

A Hybrid Intrusion Detection System for Smart Home Security Based on Machine Learning and User Behavior

Design and Hardware Implementation of a Simplified DAG-Based Blockchain and New AES-CBC Algorithm for IoT Security

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