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Internet of Things Authentication Protocols: Comparative Study

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Computers, Materials & Continua 2024年第4期79卷 65-91页

作者： Souhayla Dargaoui Mourade Azrour Ahmad ElAllaoui azidine guezzaz Abdulatif Alabdulatif Abdullah Alnajim Engineering Science and Technology Laboratory IDMS TeamFaculty of Sciences and TechniquesMoulay Ismail University of MeknesErrachidia52000Morocco Higher School Essaouira Cadi Ayyad UniversityMarrakesh44000Morocco Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia

Nowadays, devices are connected across all areas, from intelligent buildings and smart cities to Industry 4.0 andsmart healthcare. With the exponential growth of Internet of Things usage in our world, IoT security is still thebiggest challenge for its deployment. The main goal of IoT security is to ensure the accessibility of services providedby an IoT environment, protect privacy, and confidentiality, and guarantee the safety of IoT users, infrastructures,data, and devices. Authentication, as the first line of defense against security threats, becomes the priority ofeveryone. It can either grant or deny users access to resources according to their legitimacy. As a result, studyingand researching authentication issues within IoT is extremely important. As a result, studying and researchingauthentication issues within IoT is extremely important. This article presents a comparative study of recent researchin IoT security;it provides an analysis of recent authentication protocols from2019 to 2023 that cover several areaswithin IoT (such as smart cities, healthcare, and industry). This survey sought to provide an IoT security researchsummary, the biggest susceptibilities, and attacks, the appropriate technologies, and the most used simulators. Itillustrates that the resistance of protocols against attacks, and their computational and communication cost arelinked directly to the cryptography technique used to build it. Furthermore, it discusses the gaps in recent schemesand provides some future research directions.

关键词： Attacks cryptography Internet of Things security authentication

Mathematical Validation of Proposed Machine Learning Classifier for Heterogeneous Traffic and Anomaly Detection

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Big Data Mining and Analytics 2021年第1期4卷 18-24页

作者： azidine guezzaz Younes Asimi Mourade Azrour Ahmed Asimi Department of Computer Science and Mathematics High School of TechnologyCadi Ayyad UniversityEssaouira 44000Morocco Department of Computer Science High School of TechnologyIbn Zohr UniversityGuelmim 81000Morocco IDMS Team Department of Computer ScienceFaculty of Science and TechnologyMoulay Ismail UniversityErrachidia 52000Morocco Department of Computer Science and Mathematics Faculty of Sciences AgadirIbn Zohr UniversityAgadir 80000Morocco

The modeling of an efficient classifier is a fundamental issue in automatic training involving a large volume of representative ***,automatic classification is a major task that entails the use of training methods capable of assigning classes to data objects by using the input activities presented to learn *** recognition of new elements is possible based on predefined *** detection systems suffer from numerous vulnerabilities during analysis and classification of data *** overcome this problem,new analysis methods should be derived so as to implement a relevant system to monitor circulated *** main objective of this study is to model and validate a heterogeneous traffic classifier capable of categorizing collected events within *** new model is based on a proposed machine learning algorithm that comprises an input layer,a hidden layer,and an output layer.A reliable training algorithm is proposed to optimize the weights,and a recognition algorithm is used to validate the *** is applied to the collected traffic prior to the analysis *** work aims to describe the mathematical validation of a new machine learning classifier for heterogeneous traffic and anomaly detection.

关键词： anomaly detection heterogeneous traffic preprocessing machine learning training classification

Cloud-Based Intrusion Detection Approach Using Machine Learning Techniques

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Big Data Mining and Analytics 2023年第3期6卷 311-320页

作者： Hanaa Attou azidine guezzaz Said Benkirane Mourade Azrour Yousef Farhaoui Technology Higher School Essaouira Cadi Ayyad UniversityMarrakech 44000Morocco STI Laboratory the IDMS teamFaculty of Sciences and TechniquesMoulay Ismail University of MeknesErrachidia 25003`Morocco

Cloud computing(CC)is a novel technology that has made it easier to access network and computer resources on demand such as storage and data management *** addition,it aims to strengthen systems and make them *** of these advantages,cloud providers suffer from many security ***,the security of resources and services represents a real challenge for cloud *** this reason,a set of solutions have been implemented to improve cloud security by monitoring resources,services,and networks,then detect ***,intrusion detection system(IDS)is an enhanced mechanism used to control traffic within networks and detect abnormal *** paper presents a cloud-based intrusion detection model based on random forest(RF)and feature ***,the RF classifier is obtained and integrated to enhance accuracy(ACC)of the proposed detection *** proposed model approach has been evaluated and validated on two datasets and gives 98.3%ACC and 99.99%ACC using Bot-IoT and NSL-KDD datasets,***,the obtained results present good performances in terms of ACC,precision,and recall when compared to the recent related works.

关键词： cloud security anomaly detection features engineering random forest

An Ensemble Learning Based Intrusion Detection Model for Industrial IoT Security

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Big Data Mining and Analytics 2023年第3期6卷 273-287页

作者： Mouaad Mohy-Eddine azidine guezzaz Said Benkirane Mourade Azrour Yousef Farhaoui Technology Higher School Cadi Ayyad UniversityEssaouira 44000Morocco IDMS Team Faculty of Sciences and TechniquesMoulay Ismail University of MeknesErrachidia 52000Morocco

Industrial Internet of Things(IIoT)represents the expansion of the Internet of Things(IoT)in industrial *** is designed to implicate embedded technologies in manufacturing fields to enhance their ***,IIoT involves some security vulnerabilities that are more damaging than those of ***,Intrusion Detection Systems(IDSs)have been developed to forestall inevitable harmful *** survey the environment to identify intrusions in real *** study designs an intrusion detection model exploiting feature engineering and machine learning for IIoT *** combine Isolation Forest(IF)with Pearson’s Correlation Coefficient(PCC)to reduce computational cost and prediction *** is exploited to detect and remove outliers from *** apply PCC to choose the most appropriate *** and IF are applied exchangeably(PCCIF and IFPCC).The Random Forest(RF)classifier is implemented to enhance IDS *** evaluation,we use the Bot-IoT and NF-UNSW-NB15-v2 ***-PCCIF and RF-IFPCC show noteworthy results with 99.98%and 99.99%Accuracy(ACC)and 6.18 s and 6.25 s prediction time on Bot-IoT,*** two models also score 99.30%and 99.18%ACC and 6.71 s and 6.87 s prediction time on NF-UNSW-NB15-v2,*** prove that our designed model has several advantages and higher performance than related models.

关键词： Industrial Internet of Things(IIoT) isolation forest Intrusion Detection Dystem(IDS) intrusion Pearson’s Correlation Coefficient(PCC) random forest

Adapted Speed System in a Road Bend Situation in VANET Environment

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Computers, Materials & Continua 2023年第2期74卷 3781-3794页

作者： Said Benkirane azidine guezzaz Mourade Azrour Akber Abid Gardezi Shafiq Ahmad Abdelaty Edrees Sayed Salman Naseer Muhammad Shafiq EST Essaouira Cadi Ayad UniversityEssaouira44000Morocco Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia Department of Information Technology University of the Punjab Gujranwala CampusGujranwala52250Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

Today,road safety remains a serious concern for governments around the *** fact,approximately 1.35 million people die and 2–50 million are injured on public roads worldwide each *** bends in road traffic are the main cause of many road accidents,and excessive and inappropriate speed in this very critical area can cause drivers to lose their vehicle *** these reasons,new solutions must be considered to stop this disaster and save ***,it is necessary to study this topic very carefully and use new technologies such as Vehicle Ad Hoc Networks(VANET),Internet of Things(IoT),Multi-Agent Systems(MAS)and Embedded Systems to create a new system to serve the ***,the efficient and intelligent operation of the VANET network can avoid such problems as it provides drivers with the necessary real-time traffic ***,drivers are able to drive their vehicles under correct and realistic *** this document,we propose a speed adaptation scheme for winding road *** proposed scheme is based on MAS technology,the main goal of which is to provide drivers with the information they need to calculate the speed limit they must not exceed in order to maintain balance in dangerous areas,especially in *** proposed scheme provides flexibility,adaptability,and maintainability for traffic information,taking into account the state of infrastructure and metering conditions of the road,as well as the characteristics and behavior of vehicles.

关键词： ITS VANET multi-agent systems road safety