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Fusion: Practice and Applications | 2023

Recent Trends on Sophisticated types of Flooding Attacks and Detection Methods based on Multi Sensors Fusion Data for Cloud Computing Systems

Data storage, software services, infrastructure services, and platform services are only some of the benefits of today's widespread use of cloud computing. Since most cloud services run via the internet, they are vulnerable to a comprehensive range of attacks that might end it the disclosure of sensitive information. The distributed denial-of-service (DDoS) is amongst the attacks that pose an active threat to the cloud environment and disrupts the provided services for the legitimate participants. The main aim of this review paper is to present the recent trends on sophisticated flooding attacks detection methods for cloud computing systems. The review only considers the papers published within the period of 2014 until 2022.This study aims to examine the various deep learning-based DDoS detection algorithms and machine learning used across different cloud environments. Also, the study covers the Sophisticated types of Flooding Attacks and the testing dataset. The review outcomes several research challenges, gaps and future research guidelines related to protection of DDoS attack in cloud computing environment.

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Nafea A. Majeed Alhammadi mail -
Mohamed Mabrouk mail -
Mounir Zrigui mail
link https://doi.org/10.54216/FPA.110103

Volume & Issue

Vol. Volume 11 / Iss. Issue 1

Details open_in_new
Fusion: Practice and Applications | 2023

A Hybrid Pelican Optimization Algorithm and Black Hole Algorithm for Kernel Semi-Parametric Fusion Modeling

This paper investigates the process of selecting a hyperparameter for use in a kernel semiparametric regression model for fusion data, which is an important tool in various scientific study fields. The selection of the best model to use in advance is not a simple task, and one of the most fascinating current advances in the application is the use of hybrid metaheuristics algorithms to increase the exploration and exploitation capacity of traditional meta-heuristic algorithms. In this study, a hybrid optimization method that combines the pelican algorithm with the black hole algorithm is presented, which achieves a lower mean squared error (MSE) in comparison to other competing techniques. Data merging through the suggested hybrid metaheuristics algorithm gives superior performance in terms of computing time when compared to both the CV-method and the GCV-method. This work has practical implications for researchers and practitioners who use statistical modeling techniques in their work, especially those dealing with data merging for improved accuracy and efficiency.

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Firas A. Yonis AL-Taie mail -
Zakariya Yahya Algamal mail -
Omar Saber Qasim mail
link https://doi.org/10.54216/FPA.110104

Volume & Issue

Vol. Volume 11 / Iss. Issue 1

Details open_in_new
Fusion: Practice and Applications | 2023

Improving Penalized-Based Clustering Model in Big Fusion Data by Hybrid Black Hole Algorithm

This paper presents an improved penalized regression-based clustering algorithm using a nature-inspired approach. Clustering is an unsupervised learning method widely used in data fusion mining, including gene analysis, to group unclassified fusion data based on their features. The proposed algorithm is an extension of the "Sum of Norms" model and aims to better estimate the data by fusing information from various sources. The performance of the proposed algorithm is evaluated on gene expression data. Results show that our approach outperforms other methods, indicating its potential impact on clustering research with data fusion.

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Sarah G. M. Al- Kababchee mail -
Zakariya Y. Algamal mail -
Omar S. Qasim mail
link https://doi.org/10.54216/FPA.110105

Volume & Issue

Vol. Volume 11 / Iss. Issue 1

Details open_in_new
Fusion: Practice and Applications | 2023

The Steering Actuator System to Improve Driving of Autonomous Vehicles based on Multi-Sensor Data Fusion

In autonomous vehicles, the control unit must be based on two main goals, first maintains the stability of the car second follows the desired path. All things considered, the controller's effectiveness is heavily dependent on the details of the steering system actuators. The necessary steering is set by a higher-order controller. The time delay of the steering actuator is one of the main features affecting the performance of the controller. While the artificial intelligence and artificial ethic are new apparatuses in autonomous vehicles but their ICs and electrical component are exposed to fusion. This paper primarily presents a more reliable system work during the fusion of multi-sensor information. We design the requirements of the steering system and the sureness of stability control in autonomous vehicles, also finding the suitable parameters for high-level control algorithms to compensate for time delay and ensure vehicle stability. The vehicle's steering angle response was obtained by testing the actuator of electric power steering (EPS) undergoing different speeds. In fact, using the identification of the system has been beneficial because obtaining the transfer function is easier than the actual methods which need the implementation of a mathematical model of the system.  The system response of the Input-output has been defined via MATLAB. Full vehicle model simulation results indicate that the found adjustment parameter improves lane-tracking performance in a basic architecture by reducing oscillation and lateral error relative to other instances. The simplified steering system is the primary improvement brought by this effort.

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Nasseer K. Bachache mail -
Ali Muhssen Abdul-Sadah mail -
Bashar Ahmed Khalaf mail
link https://doi.org/10.54216/FPA.110106

Volume & Issue

Vol. Volume 11 / Iss. Issue 1

Details open_in_new
International Journal of Neutrosophic Science | 2023

Neutrosophic Crisp Generalized sg-Closed Sets and their Continuity

In this paper, we delivered pioneering notions of closed sets in the neutrosophic crisp sense. In other words, we discussed -closed sets, -closed sets, and -closed sets in neutrosophic crisp topological space. Moreover, the subsequent innovative ideas are established, for instance, -closure and -interior in neutrosophic crisp topological space, and obtaining numerous of their highlights. Besides, we submitted different kinds of neutrosophic crisp continuous functions and their associations.

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Qays Hatem Imran mail -
Murtadha M. Abdulkadhim mail -
Ali H. M. Al-Obaidi mail -
Said Broumi mail
link https://doi.org/10.54216/IJNS.200408

Volume & Issue

Vol. Volume 20 / Iss. Issue 4

Details open_in_new
Fusion: Practice and Applications | 2023

Crime Anomaly Detection using CNN and Ensemble Model

Every single day, thousands of crimes are perpetrated, and hundreds may be probably taking place right now throughout the world. Without a doubt, crime is viewed as a social blight. Nothing can truly stop it, no matter what is done. Surveillance cameras, on the other hand, can dramatically minimize it. Using public surveillance camera systems to prevent, document, and minimize crime can be a cost-effective solution. Installing enough cameras to detect crimes in progress and integrating technology to automate the monitoring of the live stream from these cameras will result in the most effective systems. Because of its self-learning characteristics, the advanced Artificial Intelligence surveillance system is constantly learning and improving. The Deep Learning Algorithms applied in this work processes videos using electronic devices like cameras in real-time termed as image processing, saving both human resources and a great deal of time. The highest accuracy of 86.6% was attained by Ensemble Model, followed by Inception Model with SGD Optimizer, Leaky Relu Activation Function giving an accuracy of 83.43%. Hence, anomalies were detected efficiently using decision making in real-time surveillance scenarios.  

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Gautam Gupta mail -
Prachi Aggarwal mail -
Achin Jain mail -
Puneet Singh Lamba mail -
Arun Kumar Dubey mail -
Gopal Chaudhary mail
link https://doi.org/10.54216/FPA.110107

Volume & Issue

Vol. Volume 11 / Iss. Issue 1

Details open_in_new
Galoitica: Journal of Mathematical Structures and Applications | 2023

On The Topolpgical Properties of Pairwise Compactness in Intuitionistic Double Topological Spaces

The concept of intuitionistic topological space was introduced by Coker. The aim of this paper is to discuss the relation between bi-topological spaces and double-topological spaces and give a notion of pairwise compact for double topological spaces.

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Othman Al-basheer mail
link https://doi.org/10.54216/GJMSA.040203

Volume & Issue

Vol. Volume 4 / Iss. Issue 2

Details open_in_new
Galoitica: Journal of Mathematical Structures and Applications | 2023

Results on Completely Semi Prime Ideals in Near Rings

The goal of this paper is to study the notions of completely semi prime ideal with respect to an element x (x-C.S.P.I) of a near ring and the completely semi prime ideal near ring with respect to an element x (x-C.S.P.I ), where the direct images and endomorphisms will be represented and discussed.

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Murat Ozcek mail
link https://doi.org/10.54216/GJMSA.040204

Volume & Issue

Vol. Volume 4 / Iss. Issue 2

Details open_in_new
International Journal of Neutrosophic Science | 2023

Analyzing and Evaluation of Quick Switching System using Neutrosophic Poisson Distribution

In Statistical Quality Control (SQC), the judgement of the accepting the lot or rejecting the lot s carried out with the help of acceptance sampling plans in the inspection process of any manufacturing industry. Based on the predefined risk the output is attained with minimum inspection cost based on the optimum sample size. Generally Classical statistics is used based on the deterministic nature of the information and measurements. In some circumstances, the quality characteristics may not be certain enough leading to vagueness or impreciseness situation. Accordingly, in past few decades Fuzzy logic is one of the most popular techniques to model the uncertainty in the manufacturing industries. As an advent of technology and knowledge data era, an extension of Fuzzy, a new concept known as Neutrosophic Logic is in progress to apply to achieve these uncertainties. In this, such vagueness, imprecise is called as indeterminants. Thus, Neutrosophic Logic taken its role in Acceptance Sampling Plans with Probability distributions for various plan parameters such as AQL, LQL and Neutrosophic defection status are offered for Poisson distribution in the first time. The chief formulations of Acceptance Sampling plans for Single Sampling were derived based on Neutrosophic Statistics. As an advanced step the mixture of Acceptance Sampling plans with the shifting ruling for swapping from one plan to another plan are named as Sampling System and one such system is Quick Switching System the most widely applicable to safeguard from bad quality which give high level protection as well as to reduce the cost of inspection and time. In this study, Quick Switching System (QSS) with Single Sampling Plan (SSP) as reference plan is constructed based on Neutrosophic sets on Poisson distribution as baseline distribution. The procedures, OC Curves and tables have been redesigned and presented with numerical example.

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Uma G. mail -
Nandhitha S. mail
link https://doi.org/10.54216/IJNS.200409

Volume & Issue

Vol. Volume 20 / Iss. Issue 4

Details open_in_new