Journal of Intelligent Systems and Internet of Things

Journal DOI

Submit Your Paper

2690-6791ISSN (Online) 2769-786XISSN (Print)

Computer Network Design for the teaching area of the Elvira Cape library

Yackelyn Dayanys Domínguez Izquierdo

Interconnected devices have provided companies and individuals with the advantage that information travels from one place to another, making information processes more viable. The interconnection networks are responsible for providing everything necessary for the machine to have an adequate passage of messages and use of commutations. In this document a design of a LAN network is developed for the area of ​​a library which needs to expand its communication network, thus forming a computer network to connect different types of computers sharing information links. These data links are established through means such as cable, optical cables, or wireless means such as WIFI.

Read More


Vol. 5 Issue. 1 PP. 49-53, (2021)

Intelligent System for Forecasting Failure of Agile Projects

Ahmed Abdelaziz and Alia N Mahmoud

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. 

Read More


Vol. 5 Issue. 1 PP. 08-19, (2021)

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

Khaled Riad

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.

Read More


Vol. 5 Issue. 1 PP. 20-32, (2021)

A Trustworthy Learning Technique for Securing Industrial Internet of Things Systems

Osama Maher , Elena Sitnikova

Since the Industrial Internet of Things (IIoT) networks comprise heterogeneous manufacturing and technological devices and services, discovering advanced cyber threats is an arduous and risk-prone process. Cyber-attack detection techniques have been recently emerged to understand the process of obtaining knowledge about cyber threats to collect evidence. These techniques have broadly employed for identifying malicious events of cyber threats to protect organizations’ assets. The main limitation of these systems is that they are not able to discover and interpret new attack activities. This paper proposes a new adversarial deep learning for discovering adversarial attacks in IIoT networks. Evaluation of correlation reduction has been used as a means of feature selection for reducing the impact of data poisoning attacks on the subsequent deep learning techniques. Feed Forward Deep Neural Networks have been developed using across various parameter permutations, at differing rates of data poisoning, to develop a robust deep learning architecture. The results of the proposed technique have been compared with previously developed deep learning models, proving the increased robustness of the new deep learning architectures across the ToN_IoT datasets.

Read More


Vol. 5 Issue. 1 PP. 33-48, (2021)

Intelligent Video Moving Target Detection Based on Multi-Attribute Single Value Medium Neutrosophic Method

Gopal Chaudhary , Manju Khari , Amena Mahmoud

Competition in social sports has many benefits for athlete training due to this competition gives researchers a chance to making and developing new methods and ways that support them. The competition in sport growth rapidly these days. During the last several years, there has been a significant increase in the volume of traffic using multimedia. In addition, some of the most recent paradigm shifts suggested, such as IoT, bring about the introduction of new kinds of traffic and applications. Software-defined networks, often known as SDNs, are beneficial to network management since they enhance its capabilities. When used with SDN, artificial intelligence (AI) has the potential to solve network issues using categorization and estimate strategies. So, in this paper discuss and develop a new method for sports video moving target detection. This method is based on multi-criteria decision making (MCDM) because targeting detection has many criteria and sub-criteria. This paper collected five main criteria and twenty sub-criteria impacts in target detection of sports video. We use the Analytical hierarchy Process (AHP) to determine the importance of these criteria and their weights. These criteria were evaluated under a neutrosophic environment. An application is provided to measure the outcome of the proposed method.

Read More


Vol. 5 Issue. 1 PP. 49-59, (2021)