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EBAKE-SE: A novel ECC-based authenticated key exchange between industrial IoT devices using secure element

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Digital Communications and Networks 2023年第2期9卷 358-366页

作者： Chintan Patel ali kashif bashir Ahmad ali AlZubi Rutvij Jhaveri School of Artificial Intelligence Information Technology and Cyber SecurityRashtriya Raksha UniversityGujaratIndia Department of Computing and Mathematics Manchester Metropolitan UniversityUnited Kingdom Woxsen School of Business Woxsen UniversityIndia Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon Computer Science Department Community CollegeKing Saud UniversityP.O.Box 28095Riyadh11437Saudi Arabia Department of Computer Science and Engineering School of TechnologyPandit Deendayal Energy UniversityGujaratIndia

Industrial IoT(IIoT)aims to enhance services provided by various industries,such as manufacturing and product *** suffers from various challenges,and security is one of the key challenge among those *** and access control are two notable challenges for any IIoT based industrial *** IoT based Industry 4.0 enterprise designs networks between hundreds of tiny devices such as sensors,actuators,fog devices and ***,articulating a secure authentication protocol between sensing devices or a sensing device and user devices is an essential step in IoT *** this paper,first,we present cryptanalysis for the certificate-based scheme proposed for a similar environment by Das et *** prove that their scheme is vulnerable to various traditional attacks such as device anonymity,MITM,and *** then put forward an interdevice authentication scheme using an ECC(Elliptic Curve Cryptography)that is highly secure and lightweight compared to other existing schemes for a similar ***,we set forth a formal security analysis using the random oracle-based ROR model and informal security analysis over the Doleve-Yao *** this paper,we present comparison of the proposed scheme with existing schemes based on communication cost,computation cost and security index to prove that the proposed EBAKE-SE is highly efficient,reliable,and trustworthy compared to other existing schemes for an inter-device *** long last,we present an implementation for the proposed EBAKE-SE using MQTT protocol.

关键词： Internet of things Authentication Elliptic curve cryptography Secure key exchange Message Queuing telemetry transport

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Cache in fog computing design,concepts,contributions,and security issues in machine learning prospective

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Digital Communications and Networks 2023年第5期9卷 1033-1052页

作者： Muhammad ali Naeem Yousaf Bin Zikria Rashid ali Usman Tariq Yahui Meng ali kashif bashir School of Science Guangdong University of Petrochemical TechnologyMaoming525000China Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Republic of Korea Department of Information and Communication Technologies Universitat Pompeu FabraBarcelonaSpain College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Computing and Mathematics Manchester Metropolitan UniversityManchesterUnited Kingdom Woxsen School of Business Woxsen UniversityHyderabadIndia Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon

The massive growth of diversified smart devices and continuous data generation poses a challenge to communication *** deal with this problem,communication networks consider fog computing as one of promising technologies that can improve overall communication *** brings on-demand services proximate to the end devices and delivers the requested data in a short *** computing faces several issues such as latency,bandwidth,and link utilization due to limited resources and the high processing demands of end *** this end,fog caching plays an imperative role in addressing data dissemination *** study provides a comprehensive discussion of fog computing,Internet of Things(IoTs)and the critical issues related to data security and dissemination in fog ***,we determine the fog-based caching schemes and contribute to deal with the existing issues of fog ***,this paper presents a number of caching schemes with their contributions,benefits,and challenges to overcome the problems and limitations of fog *** also identify machine learning-based approaches for cache security and management in fog computing,as well as several prospective future research directions in caching,fog computing,and machine learning.

关键词： Internet of things Cloud computing Fog computing Caching Latency

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Intelligent cache and buffer optimization for mobile VR adaptive transmission in 5G edge computing networks

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Digital Communications and Networks 2024年第5期10卷 1234-1244页

作者： Junchao Yang ali kashif bashir Zhiwei Guo Keping Yu Mohsen Guizani Chongqing Key Laboratory of Intelligent Perception and BlockChain Technology School of Artificial Intelligence Chongqing Technology and Business University Department of Computing and Mathematics Manchester Metropolitan University Woxsen School of Business Woxsen University Department of Computer Science and Mathematics Lebanese American University Graduate School of Science and Engineering Hosei University Machine Learning Department Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI)

Virtual Reality(VR) is a key industry for the development of the digital economy in the *** VR has advantages in terms of mobility,lightweight and cost-effectiveness,which has gradually become the mainstream implementation of *** this paper,a mobile VR video adaptive transmission mechanism based on intelligent caching and hierarchical buffering strategy in Mobile Edge Computing(MEC)-equipped 5G networks is proposed,aiming at the low latency requirements of mobile VR services and flexible buffer management for VR video adaptive *** support VR content proactive caching and intelligent buffer management,users' behavioral similarity and head movement trajectory are jointly used for viewpoint *** tile-based content is proactively cached in the MEC nodes based on the popularity of the VR ***,a hierarchical buffer-based adaptive update algorithm is presented,which jointly considers bandwidth,buffer,and predicted viewpoint status to update the tile chunk in client ***,according to the decomposition of the problem,the buffer update problem is modeled as an optimization problem,and the corresponding solution algorithms are ***,the simulation results show that the adaptive caching algorithm based on 5G intelligent edge and hierarchical buffer strategy can improve the user experience in the case of bandwidth fluctuations,and the proposed viewpoint prediction method can significantly improve the accuracy of viewpoint prediction by 15%.

关键词： Virtual reality Adaptive transmission Edge cache Buffer management 5G Mobile edge computing

Allocation and Migration of Virtual Machines Using Machine Learning

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Computers, Materials & Continua 2022年第2期70卷 3349-3364页

作者： Suruchi Talwani Khaled Alhazmi Jimmy Singla Hasan JAlyamani ali kashif bashir School of Computer Science&Engg. Lovely Professional UniversityPunjabIndia National Center for Robotics and Internet of Things Technology Communication and Information Technology Research InstituteKing Abdulaziz City for Science and Technology(KACST)Riyadh11442Saudi Arabia Department of Information Systems Faculty of Computing and Information Technology in RabighKing Abdulaziz UniversityRabigh21911Saudi Arabia Department of Computing and Mathematics ManchesterMetropolitan UniversityManchesterM156BHUK

Cloud computing promises the advent of a new era of service boosted by means of virtualization *** process of virtualization means creation of virtual infrastructure,devices,servers and computing resources needed to deploy an application *** extensively practiced technology involves selecting an efficient Virtual Machine(VM)to complete the task by transferring applications from Physical Machines(PM)to VM or from VM to *** whole process is very challenging not only in terms of computation but also in terms of energy and *** research paper presents an energy aware VM allocation and migration approach to meet the challenges faced by the growing number of cloud data *** Learning(ML)based Artificial Bee Colony(ABC)is used to rank the VM with respect to the load while considering the energy efficiency as a crucial *** most efficient virtual machines are further selected and thus depending on the dynamics of the load and energy,applications are migrated fromoneVMto *** simulation analysis is performed inMatlab and it shows that this research work results in more reduction in energy consumption as compared to existing studies.

关键词： Cloud computing VM allocation VM migration machine learning

A Comprehensive Review on Medical Diagnosis Using Machine Learning

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Computers, Materials & Continua 2021年第5期67卷 1997-2014页

作者： Kaustubh Arun Bhavsar Ahed Abugabah Jimmy Singla Ahmad ali AlZubi ali kashif bashir Nikita Lovely Professional University Jalandhar144411India College of Technical Innovation Zayed UniversityDubaiUnited Arab Emirates Department of Computer Science King Saud UniversitySaudi Arabia Department of Computing and Mathematics Manchester Metropolitan UniversityManchesterM156BHUK School of Computer Science and Engineering Lovely Professional UniversityJalandhar144411India

The unavailability of sufficient information for proper diagnosis,incomplete or miscommunication between patient and the clinician,or among the healthcare professionals,delay or incorrect diagnosis,the fatigue of clinician,or even the high diagnostic complexity in limited time can lead to diagnostic *** errors have adverse effects on the treatment of a *** treatments increase the medical bills and deteriorate the health of a *** diagnostic errors that harm the patient in various ways could be minimized using machine *** learning algorithms could be used to diagnose various diseases with high *** use of machine learning could assist the doctors in making decisions on time,and could also be used as a second opinion or supporting *** study aims to provide a comprehensive review of research articles published from the year 2015 to mid of the year 2020 that have used machine learning for diagnosis of various *** present the various machine learning algorithms used over the years to diagnose various *** results of this study show the distribution of machine learning methods by medical *** on our review,we present future research directions that could be used to conduct further research.

关键词： Diagnostic system machine learning medical diagnosis healthcare applications

Prediction Models for COVID-19 Integrating Age Groups, Gender, and Underlying Conditions

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Computers, Materials & Continua 2021年第6期67卷 3009-3044页

作者： Imran Ashraf Waleed SAlnumay Rashid ali Soojung Hur ali kashif bashir Yousaf Bin Zikria Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-si38541Korea Department of Computer Science King Saud UniversityRiyadhSaudi Arabia School of Intelligent Mechatronics Engineering Sejong UniversityKorea Department of Computing and Mathematics Manchester Metropolitan UniversityManchesterUnited Kingdom

The COVID-19 pandemic has caused hundreds of thousands of deaths,millions of infections worldwide,and the loss of trillions of dollars for many large *** poses a grave threat to the human population with an excessive number of patients constituting an unprecedented challenge with which health systems have to *** from many domains have devised diverse approaches for the timely diagnosis of COVID-19 to facilitate medical *** the same vein,a wide variety of research studies have investigated underlying medical conditions for indicators suggesting the severity and mortality of,and role of age groups and gender on,the probability of COVID-19 *** study aimed to review,analyze,and critically appraise published works that report on various factors to explain their relationship with *** studies span a wide range,including descriptive analyses,ratio analyses,cohort,prospective and retrospective *** studies that describe indicators to determine the probability of infection among the general population,as well as the risk factors associated with severe illness and mortality,are critically analyzed and these ndings are discussed in detail.A comprehensive analysis was conducted on research studies that investigated the perceived differences in vulnerability of different age groups and genders to severe outcomes of *** incorporating important demographic,health,and socioeconomic characteristics are highlighted to emphasize their ***,the lack of an appropriated dataset that contains demographic,personal health,and socioeconomic information implicates the efcacy and efciency of the discussed *** are overstated on the part of both exclusion of quarantined and patients with mild symptoms and inclusion of the data from hospitals where the majority of the cases are potentially ill.

关键词： COVID-19 age&gender vulnerability for COVID-19 machine learning-based prognosis COVID-19 vulnerability psychological factors prediction of COVID-19

Handling Class Imbalance in Online Transaction Fraud Detection

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Computers, Materials & Continua 2022年第2期70卷 2861-2877页

作者： Kanika Jimmy Singla ali kashif bashir Yunyoung Nam Najam UI Hasan Usman Tariq School of Computer Science and Engineering Lovely Professional UniversityPunjabIndia Department of Computing and Mathematics ManchesterMetropolitan UniversityUK&School of Electrical Engineering and Computer ScienceNational University of Science and TechnologyIslamabadPakistan Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea Department of Electrical and Computer Engineering Dhofar UniversitySalalahOman College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia

With the rise of internet facilities,a greater number of people have started doing online transactions at an exponential rate in recent years as the online transaction system has eliminated the need of going to the bank physically for every ***,the fraud cases have also increased causing the loss of money to the ***,an effective fraud detection system is the need of the hour which can detect fraudulent transactions automatically in ***,the genuine transactions are large in number than the fraudulent transactions which leads to the class imbalance *** this research work,an online transaction fraud detection system using deep learning has been proposed which can handle class imbalance problem by applying algorithm-level methods which modify the learning of the model to focus more on the minority class i.e.,fraud transactions.A novel loss function named Weighted Hard-Reduced Focal Loss(WH-RFL)has been proposed which has achieved maximum fraud detection rate i.e.,True PositiveRate(TPR)at the cost of misclassification of few genuine transactions as high TPR is preferred over a high True Negative Rate(TNR)in fraud detection system and same has been demonstrated using three publicly available imbalanced transactional ***,Thresholding has been applied to optimize the decision threshold using cross-validation to detect maximum number of frauds and it has been demonstrated by the experimental results that the selection of the right thresholding method with deep learning yields better results.

关键词： Class imbalance deep learning fraud detection loss function thresholding

Secure and Reliable Routing in the Internet of Vehicles Network:AODV-RL with BHA Attack Defense

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 633-659页

作者： Nadeem Ahmed Khalid Mohammadani ali kashif bashir Marwan Omar Angel Jones Fayaz Hassan School of Electronic Science Beijing University of Post and TelecommunicationBeijing100086China Department of Computer Science Huanggang Normal UniversityHuanggangChina Department of Computing and Mathematics Manchester Metropolitan UniversityManchesterUK Woxsen School of Business Woxsen UniversityHyderabad502345India Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon Information Technology and Management Illinois Institute of TechnologyChicagoUSA College of Computing Capital Technology UniversityLaurelUSA

Wireless technology is transforming the future of transportation through the development of the Internet of Vehicles(IoV).However,intricate security challenges are intertwinedwith technological progress:Vehicular ad hoc Networks(VANETs),a core component of IoV,face security issues,particularly the Black Hole Attack(BHA).This malicious attack disrupts the seamless flow of data and threatens the network’s overall reliability;also,BHA strategically disrupts communication pathways by dropping data packets from legitimate nodes *** the importance of this challenge,we have introduced a new solution called ad hoc On-Demand Distance Vector-Reputation-based mechanism Local Outlier Factor(AODV-RL).The significance of AODVRL lies in its unique approach:it verifies and confirms the trustworthiness of network components,providing robust protection against *** additional safety layer is established by implementing the Local Outlier Factor(LOF),which detects and addresses abnormal network *** testing of our solution has revealed its remarkable ability to enhance communication in ***,Our experimental results achieve message delivery ratios of up to 94.25%andminimal packet loss ratios of just 0.297%.Based on our experimental results,the proposedmechanismsignificantly improves VANET communication reliability and *** results promise a more secure and dependable future for IoV,capable of transforming transportation safety and efficiency.

关键词： Black hole attack IoV vehicular ad hoc network AODV routing protocol

Multi-Modal Data Analysis Based Game Player Experience Modeling Using LSTM-DNN

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Computers, Materials & Continua 2021年第9期68卷 4087-4108页

作者： Sehar Shahzad Farooq Mustansar Fiaz Irfan Mehmood ali kashif bashir Raheel Nawaz KyungJoong Kim Soon Ki Jung School of Computer Science and Engineering Kyungpook National UniversityDaeguKorea Faculty of Engineering&Informatics School of MediaDesign and TechnologyUniversity of BradfordBradfordBD71DPUK Department of Computing and Mathematics Manchester Metropolitan UniversityManchesterUK Department of Operations TechnologyEvents and Hospitality ManagementManchester Metropolitan UniversityUK Institute of Integrated Technology Gwangju Institute of Science and TechnologyKorea

Game player modeling is a paradigm of computational models to exploit players’behavior and experience using game and player *** modeling refers to descriptions of players based on frameworks of data derived from the interaction of a player’s behavior within the game as well as the player’s experience with the *** behavior focuses on dynamic and static information gathered at the time of *** experience concerns the association of the human player during gameplay,which is based on cognitive and affective physiological measurements collected from sensors mounted on the player’s body or in the player’s *** this paper,player experience modeling is studied based on the board puzzle game“Candy Crush Saga”using cognitive data of players accessed by physiological and peripheral *** Short-Term Memory-based Deep Neural Network(LSTM-DNN)is used to predict players’effective states in terms of valence,arousal,dominance,and liking by employing the concept of transfer *** learning focuses on gaining knowledge while solving one problem and using the same knowledge to solve different but related *** homogeneous transfer learning approach has not been implemented in the game domain before,and this novel study opens a new research area for the game industry where the main challenge is predicting the significance of innovative games for entertainment and players’*** not only from a player’s point of view,it is also a benchmark study for game developers who have been facing problems of“cold start”for innovative games that strengthen the game industrial economy.

关键词： Game player modeling experience modeling player analytics deep learning LSTM game play data Candy Crush Saga