Chaos Based Stego Color Image Encryption

M. I. Fath

doi:https://doi.org/10.54216/JCIM.100201

International Journal of Neutrosophic Science | 2023

n-Refined Indeterminacy of Some Modules

This article presents the notion of n-refined neutrosophic modules such as cyclic, simple, and finitely generated modules. n-refined neutrosophic is a generalization of neutrosophic properties. This paper presents new relations among n-refined neutrosophic modules. Finally, several examples and properties have been studied about the relations between these modules.

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M. Abdallah Salih mail -

D. Alawi Jarwan mail -

M. Mohammed Abed mail

link https://doi.org/10.54216/IJNS.200202

Volume & Issue

Vol. Volume 20 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2023

A New Modified Logistic Distribution: Properties and Applications in Uncertainty Data Modeling

The logistic distribution is widely used to model various types of applied data. The modified logistic distribution under neutrosophic statistics is introduced in this work. The neutrosophic logistic distribution (NLD) and its engineering applications are mainly emphasized. An appealing characteristic of the suggested NLD is that it is useful to many widely utilized survival assessment metrics, including the reliability function, hazard function, and survival function. Applications of some mathematical and statistical properties of the suggested model are discussed. Numerical investigations on simulated data are used to validate the theoretical findings experimentally. From an application point of view, it is inferred that the proposed distribution fits data with imprecise, hazy, and fuzzy information better than the usual model. In addition, the maximum likelihood (ML) technique for the proposed model is discussed under the neutrosophic inference framework. Eventually, some illustrative examples related to system reliability are provided to clarify further the implementation of the neutrosophic probabilistic model in real-world problems.

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A. M. Mohamed Ibrahim mail -

Zahid Khan mail -

Fuad S. Al-Duais mail

link https://doi.org/10.54216/IJNS.200203

Volume & Issue

Vol. Volume 20 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2023

Comparison Slice Inverse Regression Method with Machine Learning Techniques in Multivariate Data

In this study, the research aims to use some methods that deal with several independent variables with a dependent variable, where two methods were used to deal with, which is the method of slice inverse regression (SIR), which is considered a non-classical method, and two methods of machine learning, which is (TLBO, PSO), which is most popular of the teaching methods machine learning, the work of (SIR), (TLBO, PSO) is based on making reduced linear combinations of a partial set of the original explanatory variables, which may suffer from the problem of heterogeneity and the problem of multicollinearity between most of the explanatory variables. These new combinations of linear compounds resulting from the two methods will reduce the largest number of explanatory variables to reach one or more new dimensions called the effective dimension. The root mean square error criterion will be used to compare the two methods to indicate the preference of the methods.

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Omar A. abd Alwahab mail

link https://doi.org/10.54216/IJNS.200204

Volume & Issue

Vol. Volume 20 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2023

An integrated AHP MCDM based Type-2 Neutrosophic Model for Assessing the Effect of Security in Fog-based IoT Framework

The term "Internet of Things" (IoT) refers to a network of connected, intelligent devices that are responsible for the collecting and dissemination of data. Because technology automates the tasks we do daily, our lives have become simpler as a result. However, with a typical architecture for the cloud and the Internet of Things, real-time data processing is not always practicable. This is particularly true for latency-sensitive apps. This eventually resulted in the development of fog computing. On the one hand, the fog layer may perform computations and data processing at the very edge of the network, which enables it to provide results more quickly. On the other hand, this pushes the attack surface closer to the machines themselves, which is a security risk. Because of this, the sensitive data that is stored on the layer is now susceptible to assaults. Therefore, considering the security of the fog-IoT is of the utmost significance. A system or platform's level of security is determined by a number of different elements. When it comes to conducting an accurate risk assessment, the sequence in which these considerations are considered is of the utmost importance. Because of this, determining the level of security offered by fog and IoT devices becomes a Multi-Criteria Decision-Making (MCDM) dilemma. This article presents a two-stage hybrid multi-criteria decision-making model that is based on type-2 neutrosophic numbers (T2NNs). The goal of this article is to give scientists and practitioners a decision-making tool that is both easy and versatile. The initial step of this process is determining the weights of criteria by the AHP method in the T2NN environment. Second, the T2NN-based Multi-Attributive Border Approximation area Comparison (MABAC) method is used to rank the various fog security based on IoT. Both of these methods are described in more detail below. With the help of the comparison study, the high reliability and robustness of the combined AHP and MABAC based type-2 neutrosophic model have been proven.

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Mohammad D. Alshehri mail

link https://doi.org/10.54216/IJNS.200205

Volume & Issue

Vol. Volume 20 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2023

A new class of NeutroOpen, NeutroClosed, AntiOpen and AntiClosed sets in NeutroTopological and AntiTopological spaces

A lot of research has been done on the types of open and closed sets in general topological spaces and also in general bitopological spaces. Types of sets like pre-open sets and pre-closed sets, semi-open sets and semi-closed sets, Alpha-open sets, and Alpha-closed sets, regular open sets and regular closed sets, g-open sets and g-closed sets, and many more have been defined and studied. In the current study, an attempt has been made to define and give examples of a new category of open and closed sets, namely, NeutroOpen and NeutroClosed sets. Further, the concept of neutron-topology is used to define NeutroPreOpen and NeutroPreClosed sets, NeutroSemiOpen and NeutroSemiClosed sets, NeutroAlphaOpen and NeutroAlphaClosed sets, NeutroRegularOpen and NeutroRegularClosed sets, NeutroBetaOpen, and NeutroBetaClosed sets, and several examples have been given to illustrate each of the new classes of sets. Also, the concept of AntiTopology has been used to define another class of sets, namely, AntiOpen and AntiClosed sets of the above five classes of sets, namely, regular-open/closed; semi-open/closed, Alpha-open/closed, Beta-open/closed pre-open/closed sets. Further, a new class of subsets is identified which are named as NeutroTauOpen and NeutroTauClosed sets. Similar subsets in anti-topological spaces are named as AntiTauOpen and AntiTauClosed sets.

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Jeevan K. Khaklary mail -

G. Chandra Ray mail

link https://doi.org/10.54216/IJNS.200206

Volume & Issue

Vol. Volume 20 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2023

NEP-2020's Implementation & Execution: A Study Conducted Using Neutrosophic PESTEL Analysis

It is evident how crucial education is to a person's overall development. The knowledge of the economy and society is still in its infancy. In terms of social and economic elements, education has emerged as the most significant factor for individual and national growth. Given this context, it would be worthwhile to examine the New Education Policy 2020 for the benefits and impacts it has on the various stakeholders. Such analysis is important to fulfill the needs and objectives of NEP-2020. Despite having many universities and schools, Indian education still needs some improvements.  Many Indian children still do not have access to education, and more importantly, the education system in India has not undergone significant reform in the last few decades, so changes must be made to keep up with the changing needs of society. The purpose of this study is to use the neutrosophic PESTEL analysis technique to mathematically identify and rank the major factors required to be identified for the successful implementation of NEP. Numerous factors that are grouped into six primary categories—political, economic, social, technological, legal, and environmental. These are presented by a thorough literature review of the subject. The present work employs neutrosophic PESTEL analysis, to identify the main obstacles to the implementation and execution of NEP-2020 in India. The study shows that social and economic factors, with 84% and 60% respectively play a significant role while political and technical factors are also important and come in second place since they each represent 25% and 34% of the barriers to the implementation of the NEP-2020. The last two factors are legal and environmental, contributing only 13% and 3%, respectively. The primary goal of the study is to identify and statistically rank the biggest obstacles to NEP-2020 implementation in India. In many aspects, this research will help government organizations and policymakers prioritize the main obstacles early in the implementation process as well as during execution, ensuring that the results are as anticipated and that the project is finished within the allotted time limit.

groups

Mohd Yasir mail -

Aasim Zafar mail -

M. Anas Wajid mail

link https://doi.org/10.54216/IJNS.200207

Volume & Issue

Vol. Volume 20 / Iss. Issue 2

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Journal of Cybersecurity and Information Management | 2022

An Enhanced Hybrid Chaotic Technique for Protecting Medical Images

Medical data has attracted much interest; a quick, lossless, and secure cryptosystem is required for saving and transferring images over open networks while maintaining the image's details. This paper shows how to protect medical images with an encryption method based on hybrid chaotic maps. The proposed hybrid method is constructed to deal with problems like confusion and diffusion with a large key space. The technique uses a mix of different chaos maps for a specific set of control settings. There is a complete explanation of how encryption and decryption operations work. The security analysis results showed that the suggested cryptosystem is safe from statistical, brute force, and differential attacks. Compared to already known methods, the estimated times for encryption and decryption make it likely that the proposed scheme can be applied in real-time applications.

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Marwa M. Eid mail -

Shaimaa A. Hussien mail

link https://doi.org/10.54216/JCIM.100104

Volume & Issue

Vol. Volume 10 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2023

A new type of neutrosophic set in Pythagorean Fuzzy environment and Applications to multi-criteria decision making

In this paper, we introduce the concepts of Pythagorean fuzzy valued neutrosophic set (PFVNS) and Pythagorean fuzzy valued neutrosophic (PFVNV) constructed by considering Pythagorean fuzzy values (PFVs) instead of numbers for the degrees of the truth, the indeterminacy and the falsity, which is a new extension of intuitionistic fuzzy valued neutrosophic set (IFVNS). By means of PFVNSs, the degrees of the truth, the indeterminacy and the falsity can be given in Pythagorean fuzzy environment and more sensitive evaluations are made by a decision maker in decision making problems compared to IFVNSs. In other words, such sets enable a decision maker to evaluate the degrees of the truth, the indeterminacy and the falsity as PFVs to model the uncertainty in the evaluations. First of all, we propose the concepts of Pythagorean fuzzy t-norm and t-conorm and show that some Pythagorean fuzzy t-norms and t-conorms are expressed via ordinary continuous Archimedean tnorms and t-conorms. Then we define the concepts of PFVNS and PFVNV and provide a tool to construct a PFVNV from an ordinary neutrosophic fuzzy value. We also define some set theoretic operations between PFVNSs and some algebraic operations between PFVNVs via t-norms and t-conorms. With the help of these algebraic operations we propose some weighted aggregation operators. To measure discrimination information of PFVNVs, we define a simplified neutrosophic valued modified fuzzy cross-entropy measure. Moreover, we introduce a multi-criteria decision making method in Pythagorean fuzzy valued neutrosophic environment and practice the proposed theory to a real life multi-criteria decision making problem. Finally, we study the comparison analysis and the time complexity of the proposed method.

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Mahmut Can Boziygit mail -

Murat Olgun mail -

Florentin Smarandache mail -

Mehmet Unver mail

link https://doi.org/10.54216/IJNS.200208

Volume & Issue

Vol. Volume 20 / Iss. Issue 2

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Journal of Intelligent Systems and Internet of Things | 2023

Intelligent Model for Customer Churn Prediction using Deep Learning Optimization Algorithms

Business intelligence (BI) mentions to the technical and procedural structure which gathers, supplies, and examines the data formed by company action. BI is a wide term that includes descriptive analytics, procedure analysis, data mining, and performance benchmarking. Customer churn is a general problem across businesses from several sectors. Companies are working always for improving their supposed quality by way of providing timely and quality service to its customer. Customer churn is developed most initial challenges which several firms were facing currently. Many churn prediction techniques and methods were presented before in literature for predicting customer churn from the domains like telecom, finance, banking, and so on. Researchers are also working on customer churn prediction (CCP) from e-commerce utilizing data mining and machine learning (ML) approaches. This manuscript focuses on the development of Stacked Deep Learning with Wind Driven Optimization based Business Intelligence for Customer Churn Prediction model. The proposed model is considered an intelligent system that applies golden sine algorithm (GSA) based feature selection approach to derive a set of features. In addition, the stacked gated recurrent unit (SGRU) model is applied for the prediction of customer churns.

groups

Abedallah Zaid Abualkishik mail -

Rasha Almajed mail -

William Thompson mail

link https://doi.org/10.54216/JISIoT.080104

Volume & Issue

Vol. Volume 8 / Iss. Issue 1

Details open_in_new

Journal of Cybersecurity and Information Management | 2022

Chaos Based Stego Color Image Encryption

Intensive studies have been done to get robust encryption algorithms. Due to the importance of image information, image encryption has become played a vital rule in information security. Many image encryption schemes have been proposed but most of them suffer from poor robustness against severe types of attacks. In this paper two proposed techniques will be presented for color image encryption to be robust to severe attacks: composite attack. One of these approaches is represented by hybrid use of both steganography and Discrete Wavelet Transform (DWT) based encryption and the other one in which Fractional Fast Fourier Transform (FRFFT) has been used with DWT. Not only new techniques will be presented but also a new chaotic map has been used as random keys for both algorithms. After extensive comparative study with some traditional techniques, it has been found that the proposed algorithms have achieved better performance.

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M. I. Fath Allah mail

link https://doi.org/10.54216/JCIM.100201

Volume & Issue

Vol. Volume 10 / Iss. Issue 2

Details open_in_new