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Internet of Things Authentication Protocols: Comparative Study

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

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Adaptation of Federated Explainable Artificial Intelligence for Efficient and Secure E-Healthcare Systems

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Computers, Materials & Continua 2024年第3期78卷 3413-3429页

作者： Rabia Abid Muhammad Rizwan Abdulatif Alabdulatif abdullah Alnajim Meznah Alamro Mourade Azrour Department of Computer Science Kinnaird College for WomenLahorePakistan College of Science and Engineering University of DerbyDerbyDE221GBUK Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia STI Laboratory IDMS TeamFaculty of Sciences and TechniquesMoulay Ismail University of MeknèsMeknesMorocco

Explainable Artificial Intelligence(XAI)has an advanced feature to enhance the decision-making feature and improve the rule-based technique by using more advanced Machine Learning(ML)and Deep Learning(DL)based *** this paper,we chose e-healthcare systems for efficient decision-making and data classification,especially in data security,data handling,diagnostics,laboratories,and *** Machine Learning(FML)is a new and advanced technology that helps to maintain privacy for Personal Health Records(PHR)and handle a large amount of medical data *** this context,XAI,along with FML,increases efficiency and improves the security of e-healthcare *** experiments show efficient system performance by implementing a federated averaging algorithm on an open-source Federated Learning(FL)*** experimental evaluation demonstrates the accuracy rate by taking epochs size 5,batch size 16,and the number of clients 5,which shows a higher accuracy rate(19,104).We conclude the paper by discussing the existing gaps and future work in an e-healthcare system.

关键词： Artificial intelligence data privacy federated machine learning healthcare system security

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A Review of Image Steganography Based on Multiple Hashing Algorithm

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Computers, Materials & Continua 2024年第8期80卷 2463-2494页

作者： abdullah Alenizi Mohammad Sajid Mohammadi Ahmad A.Al-Hajji Arshiya Sajid Ansari Department of Information Technology College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Computer Science College of Engineering and Information TechnologyOnaizah CollegesQassim56312Saudi Arabia

Steganography is a technique for hiding secret messages while sending and receiving communications through a cover *** ancient times to the present,the security of secret or vital information has always been a significant *** development of secure communication methods that keep recipient-only data transmissions secret has always been an area of ***,several approaches,including steganography,have been developed by researchers over time to enable safe data *** this review,we have discussed image steganography based on Discrete Cosine Transform(DCT)algorithm,*** have also discussed image steganography based on multiple hashing algorithms like the Rivest–Shamir–Adleman(RSA)method,the Blowfish technique,and the hash-least significant bit(LSB)*** this review,a novel method of hiding information in images has been developed with minimal variance in image bits,making our method secure and effective.A cryptography mechanism was also used in this *** encoding the data and embedding it into a carry image,this review verifies that it has been ***,embedded text in photos conveys crucial signals about the *** review employs hash table encryption on the message before hiding it within the picture to provide a more secure method of data *** the message is ever intercepted by a third party,there are several ways to stop this operation.A second level of security process implementation involves encrypting and decrypting steganography images using different hashing algorithms.

关键词： Image steganography multiple hashing algorithms Hash-LSB approach RSA algorithm discrete cosine transform(DCT)algorithm blowfish algorithm

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Efficient Object Segmentation and Recognition Using Multi-Layer Perceptron Networks

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Computers, Materials & Continua 2024年第1期78卷 1381-1398页

作者： Aysha Naseer Nouf abdullah Almujally Saud S.Alotaibi Abdulwahab Alazeb Jeongmin Park Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Information System Department Umm Al-Qura UniversityMakkahSaudi Arabia Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Computer Engineering Tech University of KoreaGyeonggi-do15073South Korea

Object segmentation and recognition is an imperative area of computer vision andmachine learning that identifies and separates individual objects within an image or video and determines classes or categories based on their *** proposed system presents a distinctive approach to object segmentation and recognition using Artificial Neural Networks(ANNs).The system takes RGB images as input and uses a k-means clustering-based segmentation technique to fragment the intended parts of the images into different regions and label thembased on their ***,two distinct kinds of features are obtained from the segmented images to help identify the objects of *** Artificial Neural Network(ANN)is then used to recognize the objects based on their *** were carried out with three standard datasets,MSRC,MS COCO,and Caltech 101 which are extensively used in object recognition research,to measure the productivity of the suggested *** findings from the experiment support the suggested system’s validity,as it achieved class recognition accuracies of 89%,83%,and 90.30% on the MSRC,MS COCO,and Caltech 101 datasets,respectively.

关键词： K-region fusion segmentation recognition feature extraction artificial neural network computer vision

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Video Summarization Approach Based on Binary Robust Invariant Scalable Keypoints and Bisecting K-Means

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Computers, Materials & Continua 2024年第3期78卷 3565-3583页

作者： Sameh Zarif Eman Morad Khalid Amin abdullah Alharbi Wail S.Elkilani Shouze Tang Department of Information Technology Faculty of Computers and InformationMenoufia UniversityMenoufia32511Egypt Department of Artificial Intelligence Faculty of Artificial IntelligenceEgyptian Russian UniversityBader11829Egypt Department of Computer Science Community CollegeKing Saud UniversityRiyadh11362Saudi Arabia College of Applied Computer Science King Saud UniversityAl-Muzahmiya19676Saudi Arabia School of Communication and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing400065China

Due to the exponential growth of video data,aided by rapid advancements in multimedia *** became difficult for the user to obtain information from a large video *** process of providing an abstract of the entire video that includes the most representative frames is known as static video *** method resulted in rapid exploration,indexing,and retrieval of massive video *** propose a framework for static video summary based on a Binary Robust Invariant Scalable Keypoint(BRISK)and bisecting K-means clustering *** current method effectively recognizes relevant frames using BRISK by extracting keypoints and the descriptors from video *** video frames’BRISK features are clustered using a bisecting K-means,and the keyframe is determined by selecting the frame that is most near the cluster *** applying any clustering parameters,the appropriate clusters number is determined using the silhouette *** were carried out on a publicly available open video project(OVP)dataset that contained videos of different *** proposed method’s effectiveness is compared to existing methods using a variety of evaluation metrics,and the proposed method achieves a trade-off between computational cost and quality.

关键词： BRISK bisecting K-mean video summarization keyframe extraction shot detection

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Investigation of risk factors in the development of recurrent urethral stricture after internal urethrotomy

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World Journal of Clinical Cases 2024年第14期12卷 2324-2331页

作者： abdullah Gul Ozgur Ekici Salim Zengin Deniz Barali Tarik Keskin Department of Urology University of Health SciencesBursa Yüksekİhtisas Education and Research HospitalBursa 16100Türkiye Department of Urology University of Health SciencesBursa City HospitalBursa 16000Türkiye

BACKGROUND Urethral stricture is a condition that often develops with trauma and results in narrowing of the urethral *** endoscopic methods are mostly used in its treatment,it has high recurrence ***,open urethroplasty is recommended after unsuccessful endoscopic *** To investigate the risk factors associated with urethral stricture *** The data of male patients who underwent internal urethrotomy for urethral stricture between January 2017 and January 2023 were retrospectively *** data,comorbidities,preoperative haemogram,and biochemical values obtained from peripheral blood and operative data were *** were divided into two groups in terms of recurrence development;recurrence and *** recorded data were compared between the two *** A total of 303 patients were included in the *** mean age of the patients was 66.6±13.6 *** mean duration of recurrence development was 9.63±9.84(min-max:1-39)months in the recurrence *** did not occur in non-recurrence group throughout the follow-up period with an average time of 44.15±24.07(min-max:12-84)*** the comparison of both groups,the presence of diabetes mellitus(DM),hypertension(HT),and multiple comorbidi-ties were significantly higher in the recurrence(+)group(P=0.038,P=0.012,P=0.013).Blood group,postoperative use of non-steroidal anti-inflammatory drugs,preoperative cystostomy,cause of stricture,iatrogenic cause of stricture,location and length of stricture,indwelling urinary cathater size and day of catheter removal did not differ between the two *** statistically significant difference was observed between the two groups in terms of age,uroflowmetric maximum flow rate value,hemo-gram parameters,aspartate aminotransferase(AST),alanine aminotransferase(ALT),fasting blood sugar,creati-nine,glomerular filtration rate,neutrophil-lymphocyte ratio,platelet-lymphocyte ratio,lymphocyte-

关键词： Inflammation Internal urethrotomy Recurrence Urethral stricture Urethra

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The circuitry landscape of perovskite solar cells:An in-depth analysis

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Journal of Energy Chemistry 2024年第7期94卷 393-413页

作者： Siddhi Vinayak Pandey Daniel Prochowicz Apurba Mahapatra Saravanan Pandiaraj abdullah N.Alodhayb Seckin Akin Pankaj Yadav Department of Solar Energy School of Energy TechnologyPandit Deendayal Energy UniversityGandhinagar 382007GujaratIndia Department of Physical Chemistry Polish Academy of SciencesKasprzaka 44/5201-224 WarsawPoland Department of Self-Development Skills King Saud UniversityRiyadh 11451Saudi Arabia Department of Physics and Astronomy College of ScienceKing Saud UniversityP.O.Box 2455Riyadh 11451Saudi Arabia Department of Metallurgical and Materials Engineering Necmettin Erbakan University42060 KonyaTurkey Department of Physics School of Energy TechnologyPandit Deendayal Energy UniversityGandhinagar 382007GujaratIndia

The extensive research and development in perovskite solar cells (PSCs) have rekindled the hopes of converting solar energy into *** elusive understanding of underlying mechanisms is required for the development of efficient *** the years,Impedance Spectroscopy (IS) characterization,along with complementary techniques,has proven to be an effective way to understand and analyze the charge transport and recombination at interface and bulk of *** IS of PSCs have been analyzed,interpreted,and improvised continuously,revealing intricate details about the ***,there is a lack of centralized source of these details,which make it tougher to account for the generalized approach to understand the device *** present work is focused on compiling the research done on various PSC device architectures via IS to construct a comprehensive foundation of information on impedance plots,equivalent circuits,and associated processes.

关键词： Impedance Spectroscopy Perovskite solar cells Equivalent Circuits

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Communication-less Management Strategy for Electric Vehicle Charging in Droop-controlled Islanded Microgrids

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Journal of Modern Power Systems and Clean Energy 2024年第4期12卷 1227-1238页

作者： abdullah Azhar Al-Obaidi Mohammed Zaki El-Sharafy Hany E.Z.Farag Saifullah Shafiq Ali Al-Awami Independent Electricity System Operator(IESO) MississaugaCanada Department of Electrical Engineering and Computer Science York UniversityTorontoCanada University of Queensland StLucia QLD 4067Australia Department of Electrical Engineering King Fahd University of Petroleum&MineralsDhahranSaudi Arabia

Adopting high penetration levels of electric vehicles(EVs)necessitates the implementation of appropriate charging management systems to mitigate their negative impacts on pow-er distribution ***,most of the proposed Ev charging management techniques rely on the availability of high-bandwidth communication *** techniques are far from realization due to①the lack of utility-grade communica-tion systems in many cases such as secondary(low-voltage)pow-er distribution systems to which EVs are connected,rural ar-eas,remote communities,and islands,and②existing fears and concerns about the data privacy of EV users and cyber-physical *** these cases,appropriate local control schemes are needed to ensure the adequate management of EV charging without violating the grid operation ***,this paper introduces a new communication-less management strategy for EV charging in droop-controlled islanded *** proposed strategy is autonomous,as it is based on the measurement of system frequency and local bus *** proposed strategy implements a social charging fairness policy during periods when the microgrid distributed genera-tors(DGs)are in short supply by allocating more system capaci-ty to the EVs with less charging in the ***,a novel communication-less EV load shedding scheme is incorpo-rated into the management strategy to provide relief to the mi-crogrid during events of severe undervoltage or underfrequency occurrences due to factors such as high loading or DG *** simulations demonstrate the superiority of the pro-posed strategy over the state-of-the-art controllers in modulat-ing the EV charging demand to counteract microgrid instability.

关键词： Charging battery management communication-less control droop control electric vehicle islanded microgrid

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Intelligent Solution System for Cloud Security Based on Equity Distribution:Model and Algorithms

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Computers, Materials & Continua 2024年第1期78卷 1461-1479页

作者： Sarah Mustafa Eljack Mahdi Jemmali Mohsen Denden Mutasim Al Sadig abdullah M.Algashami Sadok Turki Department of Computer Science and Information College of Science at ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Computer Science College of Computing and InformaticsUniversity of SharjahSharjahUnited Arab Emirates Higher Institute of Computer Science and Mathematics University of MonastirMonastir5000Tunisia Mars Laboratory University of SousseSousseTunisia Department of Logistic and Maintenance UFR MIM at MetzUniversity of LorraineMetzFrance Department of Computer and Information Technologies College of Telecommunicationand Information Riyadh CTITechnical and Vocational Training Corporation TVTCRiyadh12464Saudi Arabia Department of Computer Science Higher Institute of Applied Sciences of SousseSousse UniversitySousse4000Tunisia

In the cloud environment,ensuring a high level of data security is in high *** planning storage optimization is part of the whole security process in the cloud *** enables data security by avoiding the risk of data loss and data *** development of data flow scheduling approaches in the cloud environment taking security parameters into account is *** our work,we propose a data scheduling model for the cloud *** is made up of three parts that together help dispatch user data flow to the appropriate *** first component is the Collector Agent whichmust periodically collect information on the state of the network *** second one is the monitoring agent which must then analyze,classify,and make a decision on the state of the link and finally transmit this information to the *** third one is the scheduler who must consider previous information to transfer user data,including fair distribution and reliable *** should be noted that each part of the proposedmodel requires the development of its *** this article,we are interested in the development of data transfer algorithms,including fairness distribution with the consideration of a stable link *** algorithms are based on the grouping of transmitted files and the iterative *** proposed algorithms showthe performances to obtain an approximate solution to the studied problem which is an NP-hard(Non-Polynomial solution)*** experimental results show that the best algorithm is the half-grouped minimum excluding(HME),with a percentage of 91.3%,an average deviation of 0.042,and an execution time of 0.001 s.

关键词： Cyber-security cloud computing cloud security algorithms heuristics

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Fine-Tuning Cyber Security Defenses: Evaluating Supervised Machine Learning Classifiers for Windows Malware Detection

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Computers, Materials & Continua 2024年第8期80卷 2917-2939页

作者： Islam Zada Mohammed Naif Alatawi Syed Muhammad Saqlain abdullah Alshahrani Adel Alshamran Kanwal Imran Hessa Alfraihi Department of Software Engineering International Islamic UniversityIslamabad25000Pakistan Information Technology Department Faculty of Computers and Information TechnologyUniversity of TabukTabuk71491Saudi Arabia Department of Computer Science and Artificial Intelligence College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia Department of Cybersecurity College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia Department of Computer Science University of PeshawarPeshawar25121Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Malware attacks on Windows machines pose significant cybersecurity threats,necessitating effective detection and prevention *** machine learning classifiers have emerged as promising tools for malware ***,there remains a need for comprehensive studies that compare the performance of different classifiers specifically for Windows malware *** this gap can provide valuable insights for enhancing cybersecurity *** numerous studies have explored malware detection using machine learning techniques,there is a lack of systematic comparison of supervised classifiers for Windows malware *** the relative effectiveness of these classifiers can inform the selection of optimal detection methods and improve overall security *** study aims to bridge the research gap by conducting a comparative analysis of supervised machine learning classifiers for detecting malware on Windows *** objectives include Investigating the performance of various classifiers,such as Gaussian Naïve Bayes,K Nearest Neighbors(KNN),Stochastic Gradient Descent Classifier(SGDC),and Decision Tree,in detecting Windows *** the accuracy,efficiency,and suitability of each classifier for real-world malware detection *** the strengths and limitations of different classifiers to provide insights for cybersecurity practitioners and *** recommendations for selecting the most effective classifier for Windows malware detection based on empirical *** study employs a structured methodology consisting of several phases:exploratory data analysis,data preprocessing,model training,and *** data analysis involves understanding the dataset’s characteristics and identifying preprocessing *** preprocessing includes cleaning,feature encoding,dimensionality reduction,and optimization to prepare the data for *** training utilizes various

关键词： Security and privacy challenges in the context of requirements engineering supervisedmachine learning malware detection windows systems comparative analysis Gaussian Naive Bayes K Nearest Neighbors Stochastic Gradient Descent Classifier Decision Tree

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