Efficient Share Generator for Slicing and Securely Retrieving the Cloud-Hosted Heterogeneous Multimedia Data

Khaled

doi:https://doi.org/10.54216/JISIoT.050103

Journal of Intelligent Systems and Internet of Things | 2021

Intelligent Image Detection System Based on Internet of Things and Cloud Computing

Images are the most intuitive way for humans to perceive and obtain information, and they are one of the most important sources of information. With the development of information technology, the use of digital image processing methods to locate and identify targets is widely used, so it is particularly important to detect the targets of interest quickly and accurately in the image. The traditional image detection system has the problems of low detection accuracy, long time consumption, and poor stability. Therefore, this paper proposes the design and research of artificial intelligence image detection system based on Internet of Things and cloud computing. The system designed in this article mainly includes three links, namely: image processing analysis design link in cloud computing environment, image feature collection module design link, and image integration detection link. The main technologies used in image processing and analysis in the cloud computing environment are virtualization technology, distributed massive data storage, and distributed computing. In the image feature collection module, before the image is input to the neural network, it is necessary to perform preprocessing operations on the distorted image and perform perspective correction; then use the deep residual network in deep learning to extract features. Finally, there is the image integration detection link. First, the target category judgment and position correction are performed on the regions generated by the candidate region generation network, and then the integrated image detection is performed through the improved target detection method based on the frame difference method. Through simulation experiments, compared with the traditional image detection system, the speed advantage of the artificial intelligence image detection system designed in this paper is obvious in the case of a large increase in the number of images. On images at different pixel levels, the accuracy of the image detection system proposed in this paper is always higher than that of traditional image detection systems, and the CPU usage and memory usage are at a lower level. In addition, within three months, the stability is also at a relatively high level of 0.9.

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Ossama Embarak mail -

Mhmed Algrnaodi mail

link https://doi.org/10.54216/JISIoT.040202

Volume & Issue

Vol. Volume 4 / Iss. Issue 2

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International Journal of Wireless and Ad Hoc Communication | 2021

Geological Landslide Disaster Monitoring Based on Wireless Network Technology

With the comprehensive influence of natural evolution and human activities, the damage degree of geological disasters is increasing. How to effectively early warning geological disasters has become a problem of concern. How to effectively provide early warning of geological disasters has become a concern of people. This research mainly discusses the geological landslide disaster monitoring based on wireless network technology. First, establish two important early warning indicators of rainfall and geological landslide displacement. The monitoring system is powered by a rechargeable 12V lithium battery, combined with solar panels, which can be charged when the sun is full to ensure the stable operation of the system. The AT45DB161B chip with 16M bytes storage capacity is selected to store data such as geological landslide displacement and rainfall. Use Microsoft SQL Server 2008 database management system to complete database content query, addition, modification, and deletion operations. The TLP521-2 photocoupler is used to isolate the GPIO interface of STM32 from the external unit to improve the anti-interference ability. The communication between the field data collector and the monitoring center data server adopts the GPRS packet data transmission method based on the TCP/IP protocol. Currently, the PDU in the network is an IP data packet. The realization of the TCP/IP protocol at the field data collector is all completed in the master single-chip microcomputer. Use SIEMENSMC35GSM/GPRS module as data transmission terminal. The monitoring results show that the absolute error of the test data does not exceed 6mm in the horizontal distance, the vertical height difference does not exceed 9mm. The results show that the monitoring of geological landslide based on wireless network technology improves the accuracy of distance estimation and reduces the positioning error, which can provide scientific guidance for the planning, monitoring and early warning of landslide area.

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Xiaohui Yuan mail -

Reem Atassi mail

link https://doi.org/10.54216/IJWAC.020102

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

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International Journal of Wireless and Ad Hoc Communication | 2021

Optimal Algorithm for Shared Network Communication Bandwidth in IoT Applications

In recent years, a variety of wired and wireless network communication protocols in the field of industrial control have become increasingly mature. The purpose of this paper is to provide a Shared network communication bandwidth optimization management algorithm for large-scale industrial networked control systems in Internet of things applications. This algorithm is based on the generalized geometric convex optimization method and can realize the optimal allocation of Shared network communication bandwidth resources. L2 networked control systems is used in this paper for the establishment of various numerical relations between the control performance and the communication network parameters. Based on the generalized geometric convex optimization method for the numerical relationship between convex analysis and fitting, convexity, and with the convex analysis and the numerical relationship between convexity fitting as constraint conditions, the results of integrity for networked control systems with large-scale resource allocation target will share the optimal management of network resources as a generalized geometric convex optimization problem. Using convex optimization software package for optimizing the optimal global solution of management problem, i. e. the optimal allocation of resources, the algorithm realizes the stability of each networked control system and achieve optimal L2 control performance. It is concluded that the predetermined transmission rate between the network node one and network node two, the data flow information sent by the network node two to the network node one is read, the delay time and packet loss rate between the two nodes are determined, the delay time is reduced by about 8 seconds, and the packet loss rate is greatly reduced by 78%.

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M. Z. A. Ab Kadir mail -

Mhmed Algrnaodi mail -

Ahmed N. Al-Masri mail

link https://doi.org/10.54216/IJWAC.020103

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

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International Journal of Wireless and Ad Hoc Communication | 2022

A Multi-level Features Fusion Model for Network Communication based on Machine Learning

Today's societies couldn't function without elaborate networks of communication. Many problems remain unresolved, but novel approaches to these problems are constantly being offered. Many of the problems plaguing existing works, such as high characteristic design cost, challenging feature selection, poor real-time performance, etc., stem from their focus on a wide range of characteristics. Worse still, the difficulty in training models due to data imbalance results in a poor detection rate for aberrant samples. To achieve a more effective and robust model, we present a multi-level feature fusion (MFFusion) model that utilizes a combination of data temporal, byte, and statistical characteristics to extract relevant information from different angles. Too far, MFFusion has outperformed the state-of-the-art on several real-world network datasets in terms of prediction performance and false alarm rate. We also use MFFusion for anomaly detection in an IoT network, using the most recent IoT malicious traffic information. The experimental results demonstrate the adaptability of MFFusion and its suitability for identifying network anomalies in an IoT context with system performance.

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Mahmoud A. Zaher mail -

Nabil M. Eldakhly mail

link https://doi.org/10.54216/IJWAC.050103

Volume & Issue

Vol. Volume 5 / Iss. Issue 1

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Fusion: Practice and Applications | 2021

A Comparative Analysis and Prediction over Bitcoin Price Using Machine Learning Technique

Bitcoin is one of the primary computerized monetary forms to utilize peer innovation to work with moment installments. The free people and organizations who own the overseeing figuring control and take part in the bitcoin network—bitcoin "miners"— are accountable for preparing the exchanges on the blockchain and are persuaded by remunerations (the arrival of new bitcoin) and exchange charges paid in bitcoin. These excavators can be considered as the decentralized authority implementing the believability of the bitcoin network. New bitcoin is delivered to the excavators at a fixed yet occasionally declining rate. There is just 21 million bitcoin that can be mined altogether. As of January 30, 2021, there are around 18,614,806 bitcoin in presence and 2,385,193 bitcoin left to be mined. This paper will predict the nature of bitcoin price because according to the reports of the past few years. The year 2020-present appeared to be a good time for bitcoin because, during this time duration, bitcoin has seen huge ups and downs. This paper will use various Machine Learning Techniques for the predictive analysis of bitcoin to accurately predict the price's nature. As the price of bitcoin depends upon various factors, and these factors directly affect the price, i.e., multiple factors of bitcoin are dependent on each other. After analyzing the results from multiple research papers and review papers, we discovered each algorithm has its advantages and disadvantages when predicting the bitcoin value. Keeping in mind all the findings, we will find algorithms that predict the bitcoin price accurately and without fewer disadvantages. So, if we go as per assumptions, regression would be the best choice for predicting the bitcoin value, but there are others algorithms also. So, in this paper, we will see the results of the multiple algorithms and then choose the correct algorithm after analyzing the results of all the implemented algorithms. This paper also includes the implementation of the comparison charts with each algorithm so that it will be easy to analyze the findings of each algorithm.

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Meenu Gupta mail -

Riya Srivastava mail

link https://doi.org/10.54216/FPA.050103

Volume & Issue

Vol. Volume 5 / Iss. Issue 1

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Journal of Intelligent Systems and Internet of Things | 2021

Intelligent Web Information Extraction Model for Agricultural Product Quality and Safety System

With the development of society, people pay more and more attention to the safety of food, and relevant laws and policies are gradually introduced and being improved. The research and development of agricultural product quality and safety system has become a research hot spot, and how to obtain the Web information of the system effectively and quickly is the focus of the research, so it is essential to carry out the intelligent extraction of Web information for agricultural product quality and safety system. The purpose of this paper is to solve the problem of how to efficiently extract the Web information of the agricultural product quality and safety system. By studying the Web information extraction methods of various systems, the paper makes a detailed analysis and research on how to realize the efficient and intelligent extraction of the Web information of the agricultural product quality and safety system. This paper analyzes in detail all kinds of template information extraction algorithms used at present, and systematically discusses a set of schemes that can automatically extract the Web information of agricultural product quality and safety system according to the template. The research results show that the proposed scheme is a dynamically extensible information extraction system, which can independently implement dynamic configuration templates according to different requirements without changing the code. Compared with the general way, the Web information extraction speed of agricultural product quality safety system is increased by 25%, the accuracy is increased by 12%, and the recall rate is increased by 30%.

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Mohammad Ali Tofigh mail -

Zhendong Mu mail

link https://doi.org/10.54216/JISIoT.040203

Volume & Issue

Vol. Volume 4 / Iss. Issue 2

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Journal of Intelligent Systems and Internet of Things | 2021

Intelligent System for Forecasting Failure of Agile Projects

Revealing the failure of agile software projects is a great challenge faced by software companies. This paper focuses on the using of intelligent techniques such as fuzzy logic, multiple linear regressions, support vector machine, neural network to address this challenge. This paper also presents a review of some works related to this area of interest. In this paper, the researchers propose an approach for revealing the failure of agile software projects based on two intelligent techniques: fuzzy logic and multiple linear regressions (MLR). MLR is used to determine crucial failure factors of agile software projects. Fuzzy logic is used for revealing failure of agile software projects. 

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Ahmed Abdelaziz and Alia N Mahmoud mail

link https://doi.org/10.54216/JISIoT.050102

Volume & Issue

Vol. Volume 5 / Iss. Issue 1

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Journal of Cybersecurity and Information Management | 2021

BioPay: A Secure Payment Gateway through Biometrics

Due to emerging technological developments, major enhancements are taking place in the area of a secure and quick transaction. BioPay being a secure payment method is a one-step ahead. In the proposed methodology, there is no involvement of any credit or debit card or any other account information like OTP or CVV; it solely depends upon some unique identifying characteristic of a human known as biometrics. This work proposes a novel method that allows users to complete transactions quickly and securely using face and finger recognition. The transaction initiates with scanning face features and matching it with the database which in turn retrieves all the information associated with that customer account. After that, the system will scan the fingerprints of the subject and verify the transaction. This methodology can be implemented in ATMs and smartphones resulting in enhanced security and flexibility for payment purposes. 

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Gurpreet Singh mail -

Divyanshi Kaushik mail -

Hritik Handa mail -

Gagandeep Kaur mail -

Kumar Chawla mail -

Ahmed A. Elngar mail

link https://doi.org/10.54216/JCIM.070202

Volume & Issue

Vol. Volume 7 / Iss. Issue 2

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Fusion: Practice and Applications | 2021

Augmenting security for electronic patient health record (ePHR) monitoring system using cryptographic key management schemes

Security plays a major role in most fields including the pharmaceutical field. Authorization and Authentication are the key concepts in supporting notable areas of the cyber-health world. HIPAA's (Health Insurance Portability and Accountability Act) ultimate focus is to preserve the privacy of the health records of an individual without disclosing it and preventing the data from unauthorized access. A complaint key management solution is applied to the patient's health records to reduce the risk factor while engaging with cryptographic mechanisms. Though there are many existing cryptographic algorithms such as Elliptic curve cryptography, and Elgammal's key exchange algorithm which provides security to the access of patient's health records, the proposed key management solution will overlay the same variant of security to the Electronic Health Records (EHR). This paper provides the countermeasures for improving security and suggests a key recovery mechanism for the protection of keys used in the security mechanism.

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Shibin David mail -

Andrew J mail -

K. Martin Sagayam mail -

Ahmed A. Elngar mail

link https://doi.org/10.54216/FPA.050201

Volume & Issue

Vol. Volume 5 / Iss. Issue 2

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2021

Efficient Share Generator for Slicing and Securely Retrieving the Cloud-Hosted Heterogeneous Multimedia Data

Recently, the security of heterogeneous multimedia data becomes a very critical issue, substantially with the proliferation of multimedia data and applications. Cloud computing is the hidden back-end for storing heterogeneous multimedia data. Notwithstanding that using cloud storage is indispensable, but the remote storage servers are untrusted. Therefore, one of the most critical challenges is securing multimedia data storage and retrieval from the untrusted cloud servers. This paper applies a Shamir Secrete-Sharing scheme and integrates with cloud computing to guarantee efficiency and security for sensitive multimedia data storage and retrieval. The proposed scheme can fully support the comprehensive and multilevel security control requirements for the cloud-hosted multimedia data and applications. In addition, our scheme is also based on a source transformation that provides powerful mutual interdependence in its encrypted representation—the  Share Generator slices and encrypts the multimedia data before sending it to the cloud storage. The extensive experimental evaluation on various configurations confirmed the effectiveness and efficiency of our scheme, which showed excellent performance and compatibility with several implementation strategies.

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Khaled Riad mail

link https://doi.org/10.54216/JISIoT.050103

Volume & Issue

Vol. Volume 5 / Iss. Issue 1

Details open_in_new