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Öğe Amassing the Security: An ECC-Based Authentication Scheme for Internet of Drones(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141, 2021) Hussain, Sajid; Chaudhry, Shehzad Ashraf; Alomari, Osama Ahmad; Alsharif, Mohammed H.; Khan, Muhammad Khurram; Kumar, NeerajThe continuous innovation and progression in hardware, software and communication technologies helped the expansion and accelerated growth in Internet of Things based drone networks (IoD), for the devices, applications and people to communicate and share data. IoD can enhance comfort in many applications including, daily life, commercial, and military/rescue operations in smart cities. However, this growth in infrastructure smartness is also subject to new security threats and the countermeasures require new customized solutions for IoD. Many schemes to secure IoD environments are proposed recently; however, some of those were proved as insecure and some degrades the efficiency. In this article, using elliptic curve cryptography, we proposed a new authentication scheme to secure the communication between a user and a drone flying in some specific flying zone. The security of the proposed scheme is solicited using formal Random oracle method along with a brief discussion on security aspects provided by proposed scheme. Finally, the comparisons with some related and latest schemes is illustrated.Öğe Analyzing and evaluating the energy efficiency based on multi-5G small cells with a mm-waves in the next generation cellular networks(Institute of Advanced Engineering and Science, 2020) Alsharif, Mohammed H.; Yahya, Khalid; Chaudhry, Shehzad AshrafThis paper evaluates the impact of multi-5G small cell systems on the energy efficiency (EE) in a Fifth Generation (5G) of cellular networks. Both the proposed model and the analysis of the EE in this study take into account (i) the path losses, fading, and shadowing that affect the received signal at the user equipment (UE) within the same cell, and (ii) the interference effects of adjacent cells. In addition, the concepts of new technologies such as large MIMO in millimeter range communication have also been considered. The simulation results show that the interference from adjacent cells can degrade the EE of a multi-cell cellular network. With the high interference the number of bits that will be transferred per joule of energy is 1.29 Mb/J with a 0.25 GHz bandwidth and 16 transmit antennas. While, with a 1 GHz bandwidth the transfer rate increases to 5.17 Mb/J. Whereas, with 64 transmit antennas the EE improved to 5.17 Mb/J with a 0.25 GHz BW and 20.70 Mb/J with a 1 GHz BW. These results provide insight into the impact of the number of antennas in millimeter range communication and the interference from adjacent cells on achieving real gains in the EE of multi-5G small cells cellular network. Copyright © 2020 Institute of Advanced Engineering and Science. All rights reserved.Öğe Application of machine intelligence technology in the detection of vaccines and medicines for SARS-CoV-2(VERDUCI PUBLISHER, VIA GREGORIO VII, ROME 186-00165, ITALY, 2020) Alsharif, Mohammed H.; Alsharif, Yahia H.; Albreem, Mahmoud A. M.; Jahid, Abu; Solyman, Ahmad Amin Ahmad; Yahya, Khalid O. Moh.; Alomari, Osama Ahmad; Hossain, Md. SanwarResearchers have found many similarities between the 2003 severe acute respiratory syndrome (SARS) virus and SARSCoV-19 through existing data that reveal the SARS’s cause. Artificial intelligence (AI) learning models can be created to predict drug structures that can be used to treat COVID-19. Despite the effectively demonstrated repurposed drugs, more repurposed drugs should be recognized. Furthermore, technological advancements have been helpful in the battle against COVID-19. Machine intelligence technology can support this procedure by rapidly determining adequate and effective drugs against COVID-19 and by overcoming any barrier between a large number of repurposed drugs, laboratory/clinical testing, and final drug authorization. This paper reviews the proposed vaccines and medicines for SARSCoV-2 and the current application of AI in drug repurposing for COVID-19 treatment.Öğe Artificial intelligence technology for diagnosing COVID-19 cases: a review of substantial issues(VERDUCI PUBLISHER, VIA GREGORIO VII, ROME 186-00165, ITALY, 2020) Alsharif, Mohammed H.; Alsharif, Yahia H.; Chaudhry, Shehzad Ashraf; Albreem, Mahmoud A. M.; Jahid, Abu; Hwang, EenjunToday, the world suffers from the rapid spread of COVID-19, which has claimed thousands of lives. Unfortunately, its treatment is yet to be developed. Nevertheless, this phenomenon can be decelerated by diagnosing and quarantining patients with COVID-19 at early stages, thereby saving numerous lives. In this study, the early diagnosis of this disease through artificial intelligence (AI) technology is explored. AI is a revolutionizing technology that drives new research opportunities in various fields. Although this study does not provide a final solution, it highlights the most promising lines of research on AI technology for the diagnosis of COVID-19. The major contribution of this work is a discussion on the following substantial issues of AI technology for preventing the severe effects of COVID-19: (1) rapid diagnosis and detection, (2) outbreak and prediction of virus spread, and (3) potential treatments. This study profoundly investigates these controversial research topics to achieve a precise, concrete, and concise conclusion. Thus, this study provides significant recommendations on future research directions related to COVID-19.Öğe Automated Triage System for Intensive Care Admissions during the COVID-19 Pandemic Using Hybrid XGBoost-AHP Approach(MDPI, ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND, 2021) Deif, Mohanad A.; Solyman, Ahmad Amin Ahmad; Alsharif, Mohammed H.; Uthansakul, PeerapongThe sudden increase in patients with severe COVID-19 has obliged doctors to make admissions to intensive care units (ICUs) in health care practices where capacity is exceeded by the demand. To help with difficult triage decisions, we proposed an integration system Xtreme Gradient Boosting (XGBoost) classifier and Analytic Hierarchy Process (AHP) to assist health authorities in identifying patients’ priorities to be admitted into ICUs according to the findings of the biological laboratory investigation for patients with COVID-19. The Xtreme Gradient Boosting (XGBoost) classifier was used to decide whether or not they should admit patients into ICUs, before applying them to an AHP for admissions’ priority ranking for ICUs. The 38 commonly used clinical variables were considered and their contributions were determined by the Shapley’s Additive explanations (SHAP) approach. In this research, five types of classifier algorithms were compared: Support Vector Machine (SVM), Decision Tree (DT), K-Nearest Neighborhood (KNN), Random Forest (RF), and Artificial Neural Network (ANN), to evaluate the XGBoost performance, while the AHP system compared its results with a committee formed from experienced clinicians. The proposed (XGBoost) classifier achieved a high prediction accuracy as it could discriminate between patients with COVID19 who need ICU admission and those who do not with accuracy, sensitivity, and specificity rates of 97%, 96%, and 96% respectively, while the AHP system results were close to experienced clinicians’ decisions for determining the priority of patients that need to be admitted to the ICU. Eventually, medical sectors can use the suggested framework to classify patients with COVID-19 who require ICU admission and prioritize them based on integrated AHP methodologies.Öğe Correcting design flaws: An improved and cloud assisted key agreement scheme in cyber physical systems(ELSEVIER, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS, 2020) Chaudhry, Shehzad Ashraf; Shon, Taeshik; Al-Turjman, Fadi; Alsharif, Mohammed H.The on demand availability of resources in Cyber physical system (CPS) has emerged as a viable service providing platform to improve the resource usability and reducing the infrastructure costs. Nevertheless, the development recompenses can only be realized after avoiding security and privacy issues. A secure and reliable CPS can offer improved efficiency, usability and reliability along with autonomy. To secure such systems, in 2018 Challa a al. (2018) proposed a security system to extend an authenticated key agreement between a user and a cloud server via trusted authority; as an application, they also customized their system to work with autonomous smart meter and cloud server. Challa a al. then claimed the security of their proposed scheme through formal, informal and automated validations. However, this paper unveils the weaknesses of their scheme and shows that their scheme cannot facilitate in forming a session key between the user/smart meter and the cloud server. Precisely, in the presence of more than one registered users/smart meters, the latter in their scheme may never receive a response message because of a critical design error. Moreover, their scheme lacks the untraceable anonymity and the lack of request verification on cloud server side may also lead to replay and/or denial of services attack. The article then introduces an improved and secure authentication system free of correctness issues, to facilitate a key agreement between user and cloud server via trusted authority. As an application, the proposed system also works for smart meter and cloud server to reach a key agreement. Based on the hardness assumption of Elliptic Curve Decisional Diffi-Hellman Problem (ECDDHP), the formal Random oracle model proves the security of the proposed scheme. Moreover, the robustness of the scheme is explained through informal analysis. The proposed system while providing all known security features has slightly increased the computation and communication costs as compared with the scheme of Challa a al. The proposed scheme completes a cycle of authentication by exchanging 2080 bits in just 13.4066 ms.Öğe Deep learning applications to combat the dissemination of COVID-19 disease: a review(VERDUCI PUBLISHER, VIA GREGORIO VII, ROME 186-00165, ITALY, 2020) Alsharif, Mohammed H.; Alsharif, Yahia H.; Yahya, Khalid O. Moh.; Alomari, Osama Ahmad; Albreem, Mahmoud A. M.; Jahid, AbuRecent Coronavirus (COVID-19) is one of the respiratory diseases, and it is known as fast infectious ability. This dissemination can be decelerated by diagnosing and quarantining patients with COVID-19 at early stages, thereby saving numerous lives. Reverse transcription-polymerase chain reaction (RTPCR) is known as one of the primary diagnostic tools. However, RT-PCR tests are costly and time-consuming; it also requires specific materials, equipment, and instruments. Moreover, most countries are suffering from a lack of testing kits because of limitations on budget and techniques. Thus, this standard method is not suitable to meet the requirements of fast detection and tracking during the COVID-19 pandemic, which motived to employ deep learning (DL)/ convolutional neural networks (CNNs) technology with X-ray and CT scans for efficient analysis and diagnostic. This study provides insight about the literature that discussed the deep learning technology and its various techniques that are recently developed to combat the dissemination of COVID-19 disease.Öğe Design of Biodegradable Mg Alloy for Abdominal Aortic Aneurysm Repair (AAAR) Using ANFIS Regression Model(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141, 2022) Hammam, Rania E.; Solyman, Ahmad Amin Ahmad; Alsharif, Mohammed H.; Uthansakul, Peerapong; Deif, Mohanad A.ABSTRACT Abdominal aortic aneurysm (AAA) is among the most widespread and dangerous diseases that may cause death. Recently, Endovascular Aneurysm Repair outperformed open aortic surgery, since it is a safe and reliable technique where a stent graft system is placed within the aortic aneurysm. It was aimed to design an Mg biodegradable alloy with bio-friendly alloying elements that enhance the corrosion resistance and mechanical properties of the alloy for the design of stents for Abdominal Aortic Aneurysm (AAA) repair. Adaptive Neuro-Fuzzy Inference System (ANFIS) was proposed for the design of the Mg alloy and compared to other traditional machine learning regression models (Multiple Linear Regression (MLR) and Gradient Boosting (GB). The dataset utilized in this work consisted of 600 samples of Mg alloys that were collected from the mat web database and additional papers from Google Scholar. The results revealed the superior prediction capability of the ANFIS model since it attained maximum R 2 scores of 0.926, 0.958, and 0.988 for the prediction of UTS, YS, and Ductility respectively. Furthermore, the ANFIS model was capable of designing an Mg biodegradable alloy having a UTS, YS, and Ductility of 346.148 Mpa, 230.8 Mpa, and 15.4% respectively which are excellent mechanical properties satisfying vascular stents requirements The ANFIS model can be further applied to speed up the design of other alloys in the future for various medical applications, reducing the time, cost, and effort of large searching space.Öğe Energy efficiency of multi-LTE macro cell cellular networks: Modelling and analysis(Little Lion Scientific, 2019) Alsharif, Mohammed H.This paper evaluates the impact of multi-macro cell systems on the energy efficiency of Long Term Evolution (LTE) cellular networks. Both the proposed model and the analysis of the EE in this study take into account (i) the path losses, fading, and shadowing that affect the received signal at the UE within the same cell, and (ii) the interference effects of adjacent cells. The simulation results show that the interference from adjacent cells can degrade the EE of a multi-cell cellular network. With the high interference from cell2 and cell3 (at the edge of the cell1), the number of bits that will be transferred per joule of energy is 0.78 kb/J with a 1.4 MHz bandwidth and two transmit antennas. With a 20 MHz bandwidth and two transmit antennas, the transfer rate increases to 11.17 kb/J. However, the EE will improve if the number of antennas is increased. The results of this study provide insight into the impact of the number of antennas and the interference from adjacent cells on achieving real gains in the EE of multi-cell LTE cellular networks. © 2005 – ongoing JATIT & LLSÖğe Energy Harvesting Techniques for Wireless Sensor Networks/Radio-Frequency Identification: A Review(MDPI, ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND, 2019) Alsharif, Mohammed H.; Kim, Sunghwan; Kuruoğlu, NuriIn the near future, symmetry technologies for the Internet of Things (IoT), along with symmetry and asymmetry applications for IoT security and privacy, will re-design the socio-ecological human terrain morphology. The IoT ecosystem deploys diverse sensor platforms connecting billions of heterogeneous objects through the Internet. Most sensors are low-energy consuming devices which are designed to transmit sporadically or continuously. However, when we consider the billions/trillions of connected sensors powering various user applications, their energy efficiency (EE) becomes a critical issue. Therefore, the importance of EE in IoT technology cannot be overemphasised, specifically the development of EE solutions for sustainable IoT technology. Propelled by this need, EE proposals are expected to address IoT's EE issues. Consequently, many developments have been displayed, and highlighting them to provide clear insights into eco-sustainable and green IoT technologies is becoming a crucial task. To pursue a clear vision of green IoT, this article aims to describe the current state-of-the art insights into energy-saving practices and strategies on green IoT. The major contribution of this study is the review and discussion of the substantial issues enabling hardware green IoT to focus on green wireless sensor networks and green radio-frequency identification. This review paper will contribute significantly to the future implementation of green and eco-sustainable IoT.Öğe The Four-C Framework for High Capacity Ultra-Low Latency in 5G Networks: A Review(MDPI, ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND, 2019) Kelechi, Anabi Hilary; Alsharif, Mohammed H.; Ramly, Athirah Mohd; Abdullah, Nor Fadzilah; Nordin, RosdiadeeNetwork latency will be a critical performance metric for the Fifth Generation (5G) networks expected to be fully rolled out in 2020 through the IMT-2020 project. The multi-user multiple-input multiple-output (MU-MIMO) technology is a key enabler for the 5G massive connectivity criterion, especially from the massive densification perspective. Naturally, it appears that 5G MU-MIMO will face a daunting task to achieve an end-to-end 1 ms ultra-low latency budget if traditional network set-ups criteria are strictly adhered to. Moreover, 5G latency will have added dimensions of scalability and flexibility compared to prior existing deployed technologies. The scalability dimension caters for meeting rapid demand as new applications evolve. While flexibility complements the scalability dimension by investigating novel non-stacked protocol architecture. The goal of this review paper is to deploy ultra-low latency reduction framework for 5G communications considering flexibility and scalability. The Four (4) C framework consisting of cost, complexity, cross-layer and computing is hereby analyzed and discussed. The Four (4) C framework discusses several emerging new technologies of software defined network (SDN), network function virtualization (NFV) and fog networking. This review paper will contribute significantly towards the future implementation of flexible and high capacity ultra-low latency 5G communications.Öğe Guest Editorial: Introduction to the special section on security and privacy in the big data era (VSI-spbd)(PERGAMON-ELSEVIER SCIENCE LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND, 2022) Karuppiah, Marimuthu; Chaudhry, Shehzad Ashraf; Alsharif, Mohammed H.There is a rising need to secure data in the era of big data. But with the rapid development of technologies such as IoT and cloud computing, users’ security and privacy measures are under tremendous pressure. Big data has led the world to an inflection point in machine learning and analytics, where powerful software tools are able to analyze vast amounts of information and often make better decisions than humans can. A major challenge for preserving privacy in the big data era is that it is hard to anonymize data without losing valuable information. Furthermore, big data has huge potential as a force for good, but numerous security and privacy concerns will dramatically reshape how big data is governed in the years and decades to come. Security, privacy, and related issues have become critical because of the wide applications in many areas.Öğe A Hybrid Multi-Objective Optimizer-Based SVM Model for Enhancing Numerical Weather Prediction: A Study for the Seoul Metropolitan Area(MDPI, ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND, 2022) Deif, Mohanad A.; Solyman, Ahmad Amin Ahmad; Alsharif, Mohammed H.; Jung, Seungwon; Hwang, EenjunTemperature forecasting is an area of ongoing research because of its importance in all life aspects. However, because a variety of climate factors controls the temperature, it is a never-ending challenge. The numerical weather prediction (NWP) model has been frequently used to forecast air temperature. However, because of its deprived grid resolution and lack of parameterizations, it has systematic distortions. In this study, a gray wolf optimizer (GWO) and a support vector machine (SVM) are used to ensure accuracy and stability of the next day forecasting for minimum and maximum air temperatures in Seoul, South Korea, depending on local data assimilation and prediction system (LDAPS; a model of local NWP over Korea). A total of 14 LDAPS models forecast data, the daily maximum and minimum air temperatures of in situ observations, and five auxiliary data were used as input variables. The LDAPS model, the multimodal array (MME), the particle swarm optimizer with support vector machine (SVM-PSO), and the conventional SVM were selected as comparison models in this study to illustrate the advantages of the proposed model. When compared to the particle swarm optimizer and traditional SVM, the Gray Wolf Optimizer produced more accurate results, with the average RMSE value of SVM for T max and T min Forecast prediction reduced by roughly 51 percent when combined with GWO and 31 percent when combined with PSO. In addition, the hybrid model (SVM-GWO) improved the performance of the LDAPS model by lowering the RMSE values for T max Forecast and T min Forecast forecasting from 2.09 to 0.95 and 1.43 to 0.82, respectively. The results show that the proposed hybrid (GWO-SVM) models outperform benchmark models in terms of prediction accuracy and stability and that the suggested model has a lot of application potentials.Öğe Machine Learning Algorithms for Smart Data Analysis in Internet of Things Environment: Taxonomies and Research Trends(MDPI, ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND, 2020) Alsharif, Mohammed H.; Kelechi, Anabi Hilary; Chaudhry, Shehzad AshrafMachine learning techniques will contribution towards making Internet of Things (IoT) symmetric applications among the most significant sources of new data in the future. In this context, network systems are endowed with the capacity to access varieties of experimental symmetric data across a plethora of network devices, study the data information, obtain knowledge, and make informed decisions based on the dataset at its disposal. This study is limited to supervised and unsupervised machine learning (ML) techniques, regarded as the bedrock of the IoT smart data analysis. This study includes reviews and discussions of substantial issues related to supervised and unsupervised machine learning techniques, highlighting the advantages and limitations of each algorithm, and discusses the research trends and recommendations for further study.Öğe Optimization Analysis of Sustainable Solar Power System for Mobile Communication Systems(TECH SCIENCE PRESS, 871 CORONADO CENTER DR, SUTE 200, HENDERSON, NV 89052, 2022) Alsharif, Mohammed H.; Kannadasan, Raju; Hassan, Amir Y.; Tawfik, Wael Z.; Kim, Mun-Kyeom; Khan, Muhammad Asghar; Solyman, Ahmad Amin AhmadCellular mobile technology has witnessed tremendous growth in recent times. One of the challenges facing the operators to extend the coverage of the networks to meet the rising demand for cellular mobile services is the power sources used to supply cellular towers with energy, especially in remote. Thus, switch from the conventional sources of energy to a greener and sustainable power model became a target of the academic and industrial sectors in many fields; one of these important fields is the telecommunication sector. Accordingly, this study aims to find the optimum sizing and technoeconomic investigation of a solar photovoltaic scheme to deploy cellular mobile technology infrastructure cleanly and sustainably. The optimal solarpowered system is designed by employing the energy-balance procedures of the HOMER software tool. The problem objective is considered in terms of cost, but the energy system is constrained to meet the power demand reliably. Process simulations were performed to determine the optimum sizing, performance and monetary cost of the power system, using long-term meteorological datasets for a case study site with defined longitude (31? 25 E) and latitude (30? 06 N). From the observed results, the total net present cost (NPC) of the proposed system is $28,187. Indeed, these outcomes can provide profound economic, technical, and ecological benefits to cellular operators. It also ensures a sizeable reduction in greenhouse gas that supports sustainable green wireless network (WN) deployment in remote areas.Öğe PFLUA-DIoT: A Pairing Free Lightweight and Unlinkable User Access Control Scheme for Distributed IoT Environments(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141, 2022) Chaudhry, Shehzad Ashraf; Farash, Mohammad Sabzinejad; Kumar, Neeraj; Alsharif, Mohammed H.The Internet of Things (IoT) connects enormous objects through various sensors to facilitate daily life by interconnecting the information space with the decision-makers. Security and privacy are, however, the main concerns in IoT due to the openness of communication channels and the unattended nature of common sensors. To provide security and privacy for sensors and users in IoT-based systems; in 2019, Zhou et al. proposed an unlinkable authentication scheme using bilinear pairings. However, the vulnerability of their scheme against sensor node impersonation attack as proved in this article renders the scheme of their work impractical and insecure. A pairing free lightweight and unlinkable authentication scheme for distributed IoT devices (PFLUA-DIoT) is then proposed in this article. The security of PFLUA-DIoT is proved using the formal method along with a discussion on its provision of security features. The performance and security comparisons show that PFLUA-DIoT provides known security features and provides better performance. Due to the avoidance of bilinear pairing-based expensive operations, PFLUA-DIoT completes authentication in less than half running time as compared with their and related schemes. Therefore, the PFLUA-DIoT can address the security and privacy issues of IoT, practically and efficiently.Öğe A Privacy Preserving Authentication Scheme for Roaming in IoT-Based Wireless Mobile Networks(MDPI, ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND, 2020) Alzahrani, Bander A.; Chaudhry, Shehzad Ashraf; Alsharif, Mohammed H.The roaming service enables a remote user to get desired services, while roaming in a foreign network through the help of his home network. The authentication is a pre-requisite for secure communication between a foreign network and the roaming user, which enables the user to share a secret key with foreign network for subsequent private communication of data. Sharing a secret key is a tedious task due to underneath open and insecure channel. Recently, a number of such schemes have been proposed to provide authentication between roaming user and the foreign networks. Very recently, Lu et al. claimed that the seminal Gopi-Hwang scheme fails to resist a session-specific temporary information leakage attack. Lu et al. then proposed an improved scheme based on Elliptic Curve Cryptography (ECC) for roaming user. However, contrary to their claim, the paper provides an in-depth cryptanalysis of Lu et al.'s scheme to show the weaknesses of their scheme against Stolen Verifier and Traceability attacks. Moreover, the analysis also affirms that the scheme of Lu et al. entails incorrect login and authentication phases and is prone to scalability issues. An improved scheme is then proposed. The scheme not only overcomes the weaknesses Lu et al.'s scheme but also incurs low computation time. The security of the scheme is analyzed through formal and informal methods; moreover, the automated tool ProVerif also verifies the security features claimed by the proposed scheme.Öğe Role of Drone Technology Helping in Alleviating the COVID-19 Pandemic(MDPI, ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND, 2022) Mohsan, Syed Agha Hassnain; Zahra, Qurat ul Ain; Khan, Muhammad Asghar; Alsharif, Mohammed H.; Elhaty, Ismail A. M.; Jahid, AbuThe COVID-19 pandemic, caused by a new coronavirus, has affected economic and social standards as governments and healthcare regulatory agencies throughout the world expressed worry and explored harsh preventative measures to counteract the disease’s spread and intensity. Several academics and experts are primarily concerned with halting the continuous spread of the unique virus. Social separation, the closing of borders, the avoidance of big gatherings, contactless transit, and quarantine are important methods. Multiple nations employ autonomous, digital, wireless, and other promising technologies to tackle this coronary pneumonia. This research examines a number of potential technologies, including unmanned aerial vehicles (UAVs), artificial intelligence (AI), blockchain, deep learning (DL), the Internet of Things (IoT), edge computing, and virtual reality (VR), in an effort to mitigate the danger of COVID-19. Due to their ability to transport food and medical supplies to a specific location, UAVs are currently being utilized as an innovative method to combat this illness. This research intends to examine the possibilities of UAVs in the context of the COVID-19 pandemic from several angles. UAVs offer intriguing options for delivering medical supplies, spraying disinfectants, broadcasting communications, conducting surveillance, inspecting, and screening patients for infection. This article examines the use of drones in healthcare as well as the advantages and disadvantages of strict adoption. Finally, challenges, opportunities, and future work are discussed to assist in adopting drone technology to tackle COVID-19-like diseases.Öğe A secure and improved multi server authentication protocol using fuzzy commitment(SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS, 2021) Rehman, Hafeez Ur; Ghani, Anwar; Chaudhry, Shehzad Ashraf; Alsharif, Mohammed H.; Nabipour, NarjesThe advancement in communication and computation technologies has paved a way for connecting large number of heterogeneous devices to offer specified services. Still, the advantages of this advancement are not realized completely due to inherent security issues. Most of the existing authentication mechanisms ensure the legitimacy of requesting user thorough single server leading towards multiple registrations and corresponding credentials storage on user side. Intelligent multimedia networks (IMN) may encompass wide range of networks and applications. However, the privacy and security of IMN cannot be apprehended through traditional multi sign on/single server authentication systems. The multi-server authentication systems can enable a user to acquire services from multiple servers using single registration and with single set of credentials (i.e.Password/smart card etc.) and can be accomplish IMN security and privacy needs. In 2018, Barman et al. proposed a multi-server authentication protocol using fuzzy commitment. The authors claimed that their protocol provides anonymity while resisting all known attacks. In this paper, we analyze that Barman et al.’s protocol is still vulnerable to anonymity violation attack and impersonation based on stolen smart card attack; moreover, it has incomplete login request and is prone to scalability issues. We then propose an enhanced protocol to overcome the security weaknesses of Barman et al.’s scheme. The security of the proposed protocol is verified using BAN logic and widely accepted automated AVISPA tool. The BAN logic and automated AVISPA along with the informal analysis ensure the robustness of the scheme against all known attacks.Öğe Sixth Generation (6G) Wireless Networks: Vision, Research Activities, Challenges and Potential Solutions(MDPI, ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND, 2020) Alsharif, Mohammed H.; Kelechi, Anabi Hilary; Albreem, Mahmoud A. M.; Chaudhry, Shehzad Ashraf; Zia, Muhammad Sultan; Kim, SunghwanThe standardization activities of the fifth generation communications are clearly over and deployment has commenced globally. To sustain the competitive edge of wireless networks, industrial and academia synergy have begun to conceptualize the next generation of wireless communication systems (namely, sixth generation, (6G)) aimed at laying the foundation for the stratification of the communication needs of the 2030s. In support of this vision, this study highlights the most promising lines of research from the recent literature in common directions for the 6G project. Its core contribution involves exploring the critical issues and key potential features of 6G communications, including: (i) vision and key features; (ii) challenges and potential solutions; and (iii) research activities. These controversial research topics were profoundly examined in relation to the motivation of their various sub-domains to achieve a precise, concrete, and concise conclusion. Thus, this article will contribute significantly to opening new horizons for future research directions.