Multi-Tier Stack of Block Chain with Proxy Re-Encryption Method Scheme on the Internet of Things Platform

Block chain provides an innovative solution to information storage, transaction execution, security, and trust building in an open environment. The block chain is technological progress for cyber security and cryptography, with efficiency-related cases varying in smart grids, smart contracts, over the IoT, etc. The movement to exchange data on a server has massively increased with the introduction of the Internet of Things. Hence, in this research, Splitting of proxy re-encryption method (Split-PRE) has been suggested based on the IoT to improve security and privacy in a private block chain. This study proposes a block chain-based proxy re-encryption program to resolve both the trust and scalability problems and to simplify the transactions. After encryption, the system saves the Internet of Things data in a distributed cloud. The framework offers dynamic, smart contracts between the sensor and the device user without the intervention of a trustworthy third party to exchange the captured IoT data. It uses an efficient proxy re-encryption system, which provides the owner and the person existing in the smart contract to see the data. The experimental outcomes show that the proposed approach enhances the efficiency, security, privacy, and feasibility of the system when compared to other existing methods.

Using deep learning to detecting abnormal behavior in internet of things

<span lang="EN-US">The development of the internet of things (IoT) has increased exponentially, creating a rapid pace of changes and enabling it to become more and more embedded in daily life. This is often achieved through integration: IoT is being integrated into billions of intelligent objects, commonly labeled “things,” from which the service collects various forms of data regarding both these “things” themselves as well as their environment. While IoT and IoT-powered decices can provide invaluable services in various fields, unauthorized access and inadvertent modification are potential issues of tremendous concern. In this paper, we present a process for resolving such IoT issues using adapted long short-term memory (LSTM) recurrent neural networks (RNN). With this method, we utilize specialized deep learning (DL) methods to detect abnormal and/or suspect behavior in IoT systems. LSTM RNNs are adopted in order to construct a high-accuracy model capable of detecting suspicious behavior based on a dataset of IoT sensors readings. The model is evaluated using the Intel Labs dataset as a test domain, performing four different tests, and using three criteria: F1, Accuracy, and time. The results obtained here demonstrate that the LSTM RNN model we create is capable of detecting abnormal behavior in IoT systems with high accuracy.</span>

A dynamic data encryption method based on addressing the data importance on the internet of things

The rapid growth of internet of things (IoT) in multiple areas brings research challenges closely linked to the nature of IoT technology. Therefore, there has been a need to secure the collected data from IoT sensors in an efficient and dynamic way taking into consideration the nature of collected data due to its importance. So, in this paper, a dynamic algorithm has been developed to distinguish the importance of data collected and apply the suitable security approach for each type of data collected. This was done by using hybrid system that combines block cipher and stream cipher systems. After data classification using machine learning classifiers the less important data are encrypted using stream cipher (SC) that use rivest cipher 4 algorithm, and more important data encrypted using block cipher (BC) that use advanced encryption standard algorithm. By applying a performance evaluation using simulation, the proposed method guarantees that it encrypts the data with less central processing unit (CPU) time with improvement in the security over the data by using the proposed hybrid system.

The Aquaponic Ecosystem Using IoT and IA Solutions

For solving the negative impact of the human evolution in earth, water, pollution and quality of feed. A system of aquaponic is proposed to manage gardening and recover up to 90% of water used for plants. Aquaponic is a system that combines two names: aquaculture which is the farming of fish and hydroponic which is the cultivation of plants (off-soil). On the other hand, the possibility of using the phytotron system. The objective of this solution is to collect performance measures, to control the watering conditions of plants (water level, temperature, humidity, ...) With a cloud support and other possibilities offered by the internet of things (IoT). The paper at hand aim to provide a smart solution integrates the phytotron solution in order to control the first part wish is the hydroponic and the second part concerning the aquaculture in order to offer a smart environment for the cycle of fish’s life.

Design and Analysis of a RFID Reader Microstrip Array antenna for IoT Applications in Smart Cities

This paper presents the design of 2*1 and 4*1 RFID reader microstrip array antenna at 2.4GHz for the Internet of things (IoT) networks which are Zigbee, Bluetooth and WIFI. The proposed antenna is composed of identical circular shapes radiating patches printed in FR4 substrate. The dielectric constant εr and substrate thickness h are 4.4 and 1.6mm, respectively. The 2*1 and 4*1 array antennas present a gain improvement of 27.3% and 61.9%, respectively. The single,2*1 and 4*1 array antennas were performed with CADFEKO.

Construction of e-commerce system based on 5G and Internet of Things technology

In order to improve the comprehensive performance of the e-commerce system, this paper combines 5G communication technology and the Internet of Things technology to improve the e-commerce system, and conduct end-point analysis on the e-commerce client data analysis system and smart logistics system. Moreover, this paper uses 5G technology to improve machine learning algorithms to process e-commerce back-end data and improve the efficiency of e-commerce client data processing. In addition, this paper combines the Internet of Things to build an e-commerce smart logistics system model to improve the overall efficiency of the logistics system. Finally, this paper combines the demand analysis to construct the functional module structure of the e-commerce system, and verifies the practical functions of the system through experimental research. From the experimental research results, it can be seen that the e-commerce system based on 5G communication technology and Internet of Things technology constructed in this paper is very reliable.

A Comprehensive Survey on Interoperability for IIoT: Taxonomy, Standards, and Future Directions

In the era of Industry 4.0, the Internet-of-Things (IoT) performs the driving position analogous to the initial industrial metamorphosis. IoT affords the potential to couple machine-to-machine intercommunication and real-time information-gathering within the industry domain. Hence, the enactment of IoT in the industry magnifies effective optimization, authority, and data-driven judgment. However, this field undergoes several interoperable issues, including large numbers of heterogeneous IoT gadgets, tools, software, sensing, and processing components, joining through the Internet, despite the deficiency of communication protocols and standards. Recently, various interoperable protocols, platforms, standards, and technologies are enhanced and altered according to the specifications of the applicability in industrial applications. However, there are no recent survey papers that primarily examine various interoperability issues that Industrial IoT (IIoT) faces. In this review, we investigate the conventional and recent developments of relevant state-of-the-art IIoT technologies, frameworks, and solutions for facilitating interoperability between different IIoT components. We also discuss several interoperable IIoT standards, protocols, and models for digitizing the industrial revolution. Finally, we conclude this survey with an inherent discussion of open challenges and directions for future research.

Design and development of an intelligent system based on the Internet of Things for the early detection of forest fires

Automatic environmental monitoring is a field that encompasses several scientific practices for the assessment of risks that may negatively impact a given environment, such as the forest. A forest is a natural environment that hosts various forms of plant and animal life, so preserving the forest is a top priority. To this end, the authors of this paper will focus on the development of an intelligent system for the early detection of forest fires, based on an IoT solution. This latter will thus facilitate the exploitation of the functionalities offered by the Cloud and mobile applications. Detecting and predicting forest fires with accuracy is a difficult task that requires machine learning and an in-depth analysis of environmental conditions. This leads the authors to adopt the forward neural network algorithm by highlighting its contribution through real experiments, performed on the prototype developed in this paper.

Design and Analysis of a RFID Reader Microstrip Array Antenna for IoT Applications in Smart Cities

This paper presents the design of 2*1 and 4*1 RFID reader microstrip array antenna at 2.4GHz for the Internet of things (IoT) networks which are Zigbee, Bluetooth and WIFI. The proposed antenna is composed of identical circular shapes radiating patches printed in FR4 substrate. The dielectric constant εr and substrate thickness h are 4.4 and 1.6mm, respectively. The 2*1 and 4*1 array antennas present a gain improvement of 27.3% and 61.9%, respectively. The single,2*1 and 4*1 array antennas were performed with CADFEKO.

The Aquaponic Ecosystem Using IoT and IA Solutions

For solving the negative impact of the human evolution in earth, water, pollution and quality of feed. A system of aquaponic is proposed to manage gardening and recover up to 90% of water used for plants. Aquaponic is a system that combines two names: aquaculture which is the farming of fish and hydroponic which is the cultivation of plants (off-soil). On the other hand, the possibility of using the phytotron system. The objective of this solution is to collect performance measures, to control the watering conditions of plants (water level, temperature, humidity, ...) With a cloud support and other possibilities offered by the internet of things (IoT). The paper at hand aim to provide a smart solution integrates the phytotron solution in order to control the first part wish is the hydroponic and the second part concerning the aquaculture in order to offer a smart environment for the cycle of fish’s life.