scholarly journals Block Data Record-Based Dynamic Encryption Key Generation Method for Security between Devices in Low Power Wireless Communication Environment of IoT

2020 ◽  
Vol 10 (21) ◽  
pp. 7940
Author(s):  
Soohwan Cho ◽  
Deokyoon Ko ◽  
Sooyoung Park
Keyword(s):  
Internet Of Things ◽  
Wireless Communication ◽  
Low Power ◽  
Packet Loss ◽  
Asynchronous Communication ◽  
Sensor Data ◽  
The Internet ◽  
Efficient Energy ◽  
Dynamic Encryption ◽  
The Internet Of Things

The Internet of Things uses low-power wireless communication for wireless connectivity and efficient energy. Low-power wireless communication is applied to IoT for wireless connection and efficient energy consumption in various areas such as wearable devices, smart homes, and power plants in order to send and receive data and control the environment. Security is becoming more important because the Internet of Things controls real physical systems. For the security of the Internet of Things, the encryption key is important to identify and authenticate devices that are trusted. The static encryption key method used for devices is likely to be calculated in reverse through the value of the key and is vulnerable to exploitation attacks. This requires the application of dynamic encryption keys that generate keys periodically. However, in the case of low-power wireless communication, the asynchronous communication method and the packet loss make it difficult to apply existing dynamic encryption key technologies. In this paper, we proposed dynamic encryption key method that applies the mechanism of the block chain to solve these problems. Based on the history of sensor data between devices, encryption keys are dynamically generated. The proposed method is to generate the same encryption key between devices with only one step of asynchronous communication considering packet loss. The proposed method is also validated in terms of availability and security in the Internet of Things low-power wireless communication.

scholarly journals Energy Efficiency in Short and Wide-Area IoT Technologies—A Survey

Technologies ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 22
Author(s):  
Eljona Zanaj ◽  
Giuseppe Caso ◽  
Luca De Nardis ◽  
Alireza Mohammadpour ◽  
Özgü Alay ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Internet Of Things ◽  
Low Power ◽  
Energy Efficient ◽  
Wide Area ◽  
Wide Area Networks ◽  
The Internet ◽  
Extensive Review ◽  
Research Directions ◽  
The Internet Of Things

In the last years, the Internet of Things (IoT) has emerged as a key application context in the design and evolution of technologies in the transition toward a 5G ecosystem. More and more IoT technologies have entered the market and represent important enablers in the deployment of networks of interconnected devices. As network and spatial device densities grow, energy efficiency and consumption are becoming an important aspect in analyzing the performance and suitability of different technologies. In this framework, this survey presents an extensive review of IoT technologies, including both Low-Power Short-Area Networks (LPSANs) and Low-Power Wide-Area Networks (LPWANs), from the perspective of energy efficiency and power consumption. Existing consumption models and energy efficiency mechanisms are categorized, analyzed and discussed, in order to highlight the main trends proposed in literature and standards toward achieving energy-efficient IoT networks. Current limitations and open challenges are also discussed, aiming at highlighting new possible research directions.

scholarly journals Internet of Vehicles: Commencing Intellectual Hoarse Towards Self-Regulating Cars and Vehicular Clouds for Smart Transportation Structure [Vehicular Ad-Hoc Network: A Review and Application in the Internet of Vehicles]

2018 ◽  
Vol 7 (3.12) ◽  
pp. 545
Author(s):  
Risabh Mishra ◽  
M Safa ◽  
Aditya Anand
Keyword(s):  
Internet Of Things ◽  
Wireless Communication ◽  
Automobile Industry ◽  
Information Exchange ◽  
Large Scale ◽  
Intelligent Transportation System ◽  
Information Service ◽  
The Internet ◽  
Internet Of Vehicles ◽  
The Internet Of Things

Recent advances in wireless communication technologies and automobile industry have triggered a significant research interest in the field of Internet of Vehicles over the past few years.The advanced period of the Internet of Things is guiding the development of conventional Vehicular Networks to the Internet of Vehicles.In the days of Internet connectivity there is need to be in safe and problem-free environment.The Internet of Vehicles (IoV) is normally a mixing of three networks: an inter-vehicleNetwork, an intra-vehicle network, and a vehicle to vehicle network.Based on  idea of three networks combining into one, we define  Internet of Vehicles as a large-scale distributed system to wireless communication and information exchange between vehicle2X (X: vehicle, road, human and internet).It is a combined   network for supporting intelligent traffic management, intelligent dynamic information service, and intelligent vehicle control, representation of an application of the Internet of Things (IoT) technology for intelligent transportation system (ITS).  

scholarly journals Worldwide Connectivity for the Internet of Things Through LoRaWAN

2019 ◽  
Vol 11 (3) ◽  
pp. 57 ◽  
Author(s):  
Lorenzo Vangelista ◽  
Marco Centenaro
Keyword(s):  
Internet Of Things ◽  
Low Power ◽  
Cellular Network ◽  
Wide Area ◽  
The Internet ◽  
Area Network ◽  
Wide Area Network ◽  
Frequency Bands ◽  
The Moment ◽  
The Internet Of Things

The low-power wide-area network (LPWAN) paradigm is gradually gaining market acceptance. In particular, three prominent LPWAN technologies are emerging at the moment: LoRaWAN™ and SigFox™, which operate on unlicensed frequency bands, and NB-IoT, operating on licensed frequency bands. This paper deals with LoRaWAN™, and has the aim of describing a particularly interesting feature provided by the latest LoRaWAN™ specification—often neglected in the literature—i.e., the roaming capability between different operators of LoRaWAN™ networks, across the same country or even different countries. Recalling that LoRaWAN™ devices do not have a subscriber identification module (SIM) like cellular network terminals, at a first glance the implementation of roaming in LoRaWAN™ networks could seem intricate. The contribution of this paper consists in explaining the principles behind the implementation of a global LoRaWAN network, with particular focus on how to cope with the lack of the SIM in the architecture and how to realize roaming.

scholarly journals An Improved Unsupervised Single-Channel Speech Separation Algorithm for Processing Speech Sensor Signals

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Dazhi Jiang ◽  
Zhihui He ◽  
Yingqing Lin ◽  
Yifei Chen ◽  
Linyan Xu
Keyword(s):  
Internet Of Things ◽  
Speech Signal ◽  
Single Channel ◽  
Low Noise ◽  
Sensor Data ◽  
The Internet ◽  
Speech Separation ◽  
Adaptive Wavelet ◽  
Enhancement Technique ◽  
The Internet Of Things

As network supporting devices and sensors in the Internet of Things are leaping forward, countless real-world data will be generated for human intelligent applications. Speech sensor networks, an important part of the Internet of Things, have numerous application needs. Indeed, the sensor data can further help intelligent applications to provide higher quality services, whereas this data may involve considerable noise data. Accordingly, speech signal processing method should be urgently implemented to acquire low-noise and effective speech data. Blind source separation and enhancement technique refer to one of the representative methods. However, in the unsupervised complex environment, in the only presence of a single-channel signal, many technical challenges are imposed on achieving single-channel and multiperson mixed speech separation. For this reason, this study develops an unsupervised speech separation method CNMF+JADE, i.e., a hybrid method combined with Convolutional Non-Negative Matrix Factorization and Joint Approximative Diagonalization of Eigenmatrix. Moreover, an adaptive wavelet transform-based speech enhancement technique is proposed, capable of adaptively and effectively enhancing the separated speech signal. The proposed method is aimed at yielding a general and efficient speech processing algorithm for the data acquired by speech sensors. As revealed from the experimental results, in the TIMIT speech sources, the proposed method can effectively extract the target speaker from the mixed speech with a tiny training sample. The algorithm is highly general and robust, capable of technically supporting the processing of speech signal acquired by most speech sensors.

scholarly journals A Novel Sensor Data Pre-Processing Methodology for the Internet of Things Using Anomaly Detection and Transfer-By-Subspace-Similarity Transformation

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4536 ◽  
Author(s):  
Yan Zhong ◽  
Simon Fong ◽  
Shimin Hu ◽  
Raymond Wong ◽  
Weiwei Lin
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
Anomaly Detection ◽  
Sensor Data ◽  
Detection Methods ◽  
The Internet ◽  
Quality Of Data ◽  
Data Mining Algorithms ◽  
Sensing Applications ◽  
The Internet Of Things

The Internet of Things (IoT) and sensors are becoming increasingly popular, especially in monitoring large and ambient environments. Applications that embrace IoT and sensors often require mining the data feeds that are collected at frequent intervals for intelligence. Despite the fact that such sensor data are massive, most of the data contents are identical and repetitive; for example, human traffic in a park at night. Most of the traditional classification algorithms were originally formulated decades ago, and they were not designed to handle such sensor data effectively. Hence, the performance of the learned model is often poor because of the small granularity in classification and the sporadic patterns in the data. To improve the quality of data mining from the IoT data, a new pre-processing methodology based on subspace similarity detection is proposed. Our method can be well integrated with traditional data mining algorithms and anomaly detection methods. The pre-processing method is flexible for handling similar kinds of sensor data that are sporadic in nature that exist in many ambient sensing applications. The proposed methodology is evaluated by extensive experiment with a collection of classical data mining models. An improvement over the precision rate is shown by using the proposed method.

Low-power IPv6 for the Internet of Things

2012 ◽  
Author(s):  
Adam Dunkels ◽  
Joakim Eriksson ◽  
Niclas Finne ◽  
Fredrik Osterlind ◽  
Nicolas Tsiftes ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Low Power ◽  
The Internet ◽  
The Internet Of Things
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