IoT Data Transmission Research Articles

RETRACTED ARTICLE: Modified sailfish optimization for energy efficient data transmission in IOT based sensor network

RETRACTED ARTICLE: Modified sailfish optimization for energy efficient data transmission in IOT based sensor network

Secure Data Validation and Transmission in Cloud and IoT Through Ban Logic and KP-ABE

Background: Cloud computing is a service that is being accelerating its growth in the field of information technology in recent years. Privacy and security are challenging issues for cloud users and providers. Obective: This work aims at ensuring secured validation of user and protects data during transmission for users in a public IoT-cloud environment. Existing security measures however fails by their single level of security, adaptability for large amount of data and reliability. Therefore, to overcome these issues and to achieve a better solution for vulnerable data. Method: The suggested method utilizes a secure transmission in cloud using key policy attribute based encryption (KPABE). Initially, user authentication is verified. Then the user data is encrypted with the help of KP-ABE algorithm. Finally, data validation and privacy preservation are done by Burrows-Abadi-Needham (BAN) logic. This verified, and shows that the proposed encryption is correct, secure and efficient to prevent unauthorized access and prevention of data leakage so that less chances of data/identity, theft of a user is the analysis and performed by KP-ABE, that is access control approach. Results: Here the method attains the maximum of 88.35% of validation accuracy with a minimum 8.78ms encryption time, which is better when, compared to the existing methods. The proposed mechanism is done by MATLAB. The performance of the implemented method is calculated based on the time of encryption and decryption, execution time and validation accuracy. Conclusion: Thus the proposed approach attains the high IoT-cloud data security and increases the speed for validation and transmission with high accuracy and used for cyber data science processing.

Интернет вещей и комплаенс-контроль

The article examines the main directions of the organization and conduct of compliance control in the use and application of Internet of Things technology (English Internet of things, IoT) in the organization for information security. In the course of the study, the authors identify the main areas and problem areas of IoT (data transmission networks between physical objects («things»)) that need constant monitoring and modernization. As a result of the analysis, the authors prepared and formulated four main steps in conducting compliance control of the area under consideration: to determine requirements, to carry out risk analysis, to conduct testing and to carry out systematic checks of the system. In order to minimize the risk of user interaction, the authors have prepared recommendations that must be implemented on an ongoing basis when using IoT technologies, namely, the following characteristics and capabilities of the IoT system are subject to strict control: shelf life (of a product or service), methods and reliability of authorization and authentication, data storage and protection, feasibility of comprehensive testing, availability of system flexibility, permissibility of remote administration, anomaly detection, compliance with applicable industry standards, for which an IoT product or service was developed

Modeling of Occupancy-Based Energy Consumption in a Campus Building Using Embedded Devices and IoT Technology

Since occupancy affects energy consumption, it is common to model and simulate occupancy using simulation software. One drawback of simulation software is that it cannot provide data transmission information from the sensors, which is essential for real-time energy monitoring systems. This paper proposes an approach to integrating an occupancy model and a real-time monitoring system for real-time modeling. The integration was performed by implementing a model on embedded devices and employing an IoT-based real-time monitoring application. The experimental results showed that the proposed approach effectively configured and monitored the model using a smartphone. Moreover, the data generated by the model were stored in an IoT cloud server for monitoring and further analysis. The evaluation result showed that the model ran perfectly in real-time embedded devices. The assessment of the IoT data transmission performances yielded a maximum latency of 9.0348 s, jitter of 0.9829 s, inter-arrival time of 5.5085 s, and packet loss of 10.8%, which are adequate for real-time modeling of occupancy-based energy consumption.

Secure Healthcare Data Aggregation and Transmission in IoT—A Survey

Internet of medical things (IoMT) is getting researchers' attention due to its wide applicability in healthcare. Smart healthcare sensors and IoT enabled medical devices exchange data and collaborate with other smart devices without human interaction to securely transmit collected sensitive healthcare data towards the server nodes. Alongside data communications, security and privacy is also quite challenging to securely aggregate and transmit healthcare data towards Fog and cloud servers. We explored the existing surveys to identify a gap in literature that a survey of fog-assisted secure healthcare data collection schemes is yet contributed in literature. This paper presents a survey of different data collection and secure transmission schemes where Fog computing based architectures are considered. A taxonomy is presented to categorize the schemes. Fog assisted smart city, smart vehicle and smart grids are also considered that achieve secure, efficient and reliable data collection with low computational cost and compression ratio. We present a summary of these scheme along with analytical discussion. Finally, a number of open research challenges are identified. Moreover, the schemes are explored to identify the challenges that are addressed in each scheme.

Research on Music Wireless Control Based on Motion Tracking Sensor and Internet of Things

With the continuous development of society and rapid economic growth, intelligent music control technology has received more and more attention. At the same time, real-time motion tracking technology has also been developed more and more in the fields of virtual reality and human-machine control. This article is dedicated to developing a wireless music control system based on gesture tracking sensors. First, in the data collection part, an infrared sensor module based on the Internet of Things is used to automatically detect whether someone is approaching. When detecting that someone is approaching, the motion tracking sensor module captures and detects gestures and counts them through a counter. Then, the IoT data transmission module sends the acquired gesture information from the sending end to the receiving end. Finally, the particle swarm algorithm performs algorithmic intelligent processing and judgment on the transmitted data to realize wireless control of background music. After software and hardware debugging, a wireless music control model based on motion tracking was finally successfully established. The system has undergone a complete test, and the test results show that the system has strong stability. Users can easily control music equipment and achieve high accuracy of music control information.

A Comprehensive Access Point Placement for IoT Data Transmission Through Train-Wayside Communications in Multi-Environment Based Rail Networks

In this paper, we propose three algorithms for placement of access points (APs) for the purpose of data transportation via train-to-wayside (T2W) communications along a rail network. The first algorithm is proposed to find the minimum number of APs so that the path-loss (PL) does not exceed a desired threshold. Through the second algorithm, the most optimal places for a desired number of APs are determined so that the average PL is minimum. The goal of the third algorithm is to determine the required number and optimal places of APs in a rail network. Furthermore, we propose a model to consider the effects of changes of communication characteristics on the efficiency of the network in different environments. Through such model, the algorithms proposed for placement of APs can be used in different railway scenarios. The proposed algorithms are validated through extensive simulations in Sydney Trains of Australia. The simulation results show that the proposed approach can improve the efficiency of the system at least 21% and up to 165% within 10 different scenarios. We also show that we can approximately transmit over 250 Gigabit data through T2W communications over common WiFi networks.

Gradient-based adaptive modeling for IoT data transmission reduction

Spatial and temporal correlation between sensor observations in an Internet of Things environment can be exploited to eliminate unnecessary transmissions. Transmitting less data certainly contributes to meet the growing need for energy-saving and robust transmissions, thus prolong the lifespan of the entire WSN. Spatiotemporal correlation-based dual prediction (DP) and data compression (DC) schemes aim to reduce the amount of data transmission while ensuring data accuracy. In practice, however, the existing methods restrict the stability of the system when the model hyper-parameters are uncertain. Thus adaptive model has lately attracted extensive attention for the development of resource-constrained WSN. In this paper, we propose a gradient-based adaptive model that implements both schemes in a two-tier data reduction framework. To the best of our knowledge, the proposed scheme is the first attempt to introduce adaptiveness into both the DP and DC schemes by using a simple gradient optimization method. Gradient-based Optimal Step-size LMS (GO-LMS) is introduced to make the DP aspects adaptive, while a Gradient-based Adaptive PCA (GA-PCA) approach is used for the DC aspects. The Barzilai–Borwein method is incorporated into the gradient optimization to enable adaptive computation of the step-size for each iteration. Through extensive simulations, the developed framework was found to outperform other state-of-the-art schemes in terms of both the transmission reduction ratio and data recovery accuracy.

Guest Editorial: Special Section on Integration of Big Data and Artificial Intelligence for Internet of Things

These redundant data in IoT should be compressed or removed. Furthermore, the unstructured data in IoT plays an important role for analyzing the user behaviors, while transmitting and processing these unstructured data consumption of substantial energy. These unstructured data should be mined or restructured. In addition, the increasing number of users in IoT leads to a fast-growing data in IoT, while the Quality of Service (QoS) of IoT should be maintained regardless of the number of IoT users. Therefore, the data transmission and processing in IoT should be performed in a more intelligent manner. All these observations indicate that the integration of big data and artificial intelligence (AI) for IoT is a good propellant to improve the data transmission and processing in IoT, since big data technology (e.g., data integration, data mining, data prediction) could effectively handle various data while AI technology could further facilitate capturing and structuring big data.

Enhanced encryption technique for secure iot data transmission

<div class="page" title="Page 1"><div class="section"><div class="layoutArea"><div class="column"><p><span>Internet of things is the latest booming innovation in the current period, which lets the physical entity to process and intervene with the virtual entities. As all the entities are connected with each other, it generates load of data, which lacks proper security and privacy standards. Cryptography is one of the domains of Network Security, which is one such mechanism that helps the data transmission process to be secure enough over the wireless or wired channel and along with that, it provides authenticity, confidentiality, integrity of data and prevents repudiation. In this paper, we have proposed an alternate enhanced cryptographic solution combing the characteristic of symmetric, asymmetric encryption algorithms and Public Key Server. Here, the key pairs of end points (User’s Device and IoT device) are generated using Elliptic Curve Cryptography and the respective public keys are registered in Public Key Server along with their unique MAC address. Thereafter, both the ends will agree on one common private secret key, which will be the base for further cryptographic process using AES algorithm. This model can be called as multi-phase protection mechanism. It will make the process of data transmission secure enough that no intermediate can tamper the data.</span></p></div></div></div></div>

A PUF-based unified identity verification framework for secure IoT hardware via device authentication

In the era of Internet-of-Things (IoTs), millions of smart devices are interconnected and communicated through networks. To guarantee the security and reliability of data transmission in IoT, the underlying hardware of these devices must first be secure and trusted. However, due to the inherent mobility nature of current embedded devices, IoT hardware could be vulnerable to diverse security threats from multiple malicious participants. Among them, device theft is becoming one of the most challenging security issues that have incurred a serious impact on copyright. To effectively alleviate this threat, silicon physical unclonable function (PUF) has been presented and considered to be a reliable anti-piracy solution to complete the device authentication and key storage. However, current PUF solutions are mostly focused on chip-level verification and cannot provide systematic identification and authentication. To this end, this article proposes a unified identity verification framework which can provide fine-grained protection for embedded devices against theft attacks from the system level. This framework is established on a series of PUF circuits that have been implanted into each individual chip of the devices. We first improve the configurable ring oscillator (CRO) PUFs with the latch structure. Therefore, a unique sub-digital signature of each chip can be generated by performing the challenge-response strategy. We then reassemble all the sub-digital signatures and encode them to acquire the unique fingerprint of each embedded device, so as to achieve system-level device identification and authentication. Any substitution of an individual or all chips in the devices will result in the inconsistencies of the system-level fingerprint. We implement and verify the proposed scheme on the field programmable gate array (FPGA) platforms. Experimental results illustrate that the proposed framework can uniquely and accurately identify any or all of the thefts to the embedded system hardware at low silicon overhead.

A Secure and Efficient Scheduling Mechanism for Emergency Data Transmission in IOT

A Secure and Efficient Scheduling Mechanism for Emergency Data Transmission in IOT

Fractional Gravitational Grey Wolf Optimization to Multi-Path Data Transmission in IoT

The advancements of technology in the field of communication made WSN based IoT attractive and applicable to various areas. It is comprised IoT nodes that work on limited battery supplies. Hence, a high-performance routing protocol is essential for routing in such networks to overcome the energy constraint problems. In this paper, an energy efficient routing algorithm Fractional Gravitational Grey Wolf Optimization (FGGWO) is proposed for multipath data transmission. This work is motivated by the Ant Colony Optimization (ACO) algorithm that discovered multipaths based on clustering technique. The proposed algorithm improves the routing process of ACO in a two stage process. At first, the cluster heads are selected by utilizing the previous work Fractional Gravitational Search Algorithm (FGSA). Secondly, multiple paths are generated from the source to the destination using FGGWO, which modifies Grey Wolf Optimization by integrating FGSA in the algorithm. Objectives, such as, energy, inter and intra-cluster distance, delay and lifetime, considered in the fitness function provide optimal paths for the transmission. The experimental results show that the proposed FGSA + FGGWO algorithm has higher performance regarding energy and alive nodes, in comparison with the existing ABC + ACO, FABC + EACO, and Threshold + ACO techniques. The maximum number of alive nodes and energy estimated in FGSA + FGGWO is 25 and 0.1298 for 50 nodes; and 27 and 0.0876, for 100 nodes.

A lightweight hybrid encryption technique to secure IoT data transmission

Internet of Things(IOT) is the rising innovation without bounds is required to associate billions of devices. IoT is the future where many low power resources and constrained devices are connected by means of the internet for communication, compute process and take actions in the communication network. The increased number of communication is relied upon to produce heaps of information and the security of information can be a threat resulting a secure solution for communication is necessitates among heterogenous devices. Focus of the work is to provide confidentiality, authentication and integrity of data in transit between IoT edge devices and back-end systems. This paper proposes a lightweight hybrid encryption system using ECDH key exchange mechanism for generating keys and establishing connection, digital signature for authentication, thereafter AES algorithm for encryption and decryption of user data file. The proposed combination is referred to as “three way secured data encryption mechanism” which interpret all the 3 protection schemes of authentication, info security and verification with the characteristics of lower calculation cost and faster speed makes it robust for hackers to crack the security system, thereby protective data in transmission.