The rapid growth of Information and Communication Technology (ICT) in the 21st century has resulted in the emergence of a novel technological paradigm; known as the Internet of Things, or IoT. The IoT, which is at the heart of today's smart infrastructure, aids in the creation of a ubiquitous network of things by simplifying interconnection between smart digital devices and enabling Machine to Machine (M2M) communication. As of now, there are numerous examples of IoT use cases available, assisting every person in this world towards making their lives easier and more convenient. The latest advancement of IoT in a variety of domains such as healthcare, smart city, smart agriculture has led to an exponential growth of cyber-attacks that targets these pervasive IoT environments, which can even lead to jeopardizing the lives of people; that is involved with it. In general, this IoT can be considered as every digital object that is connected to the Internet for intercommunication. Hence in this regard to analyze cyber threats that come through the Internet, here we are doing an experimental evaluation to analyze the requests, received to exploit the opened Secure Shell (SSH) connection service of an IoT device, which in our case a Raspberry Pi devices, which connected to the Internet for more than six consecutive days. By opening the SSH service on Raspberry Pi, it acts as a Honeypot device where we can log and retrieve all login attempt requests received to the SSH service opened. Inspired by evaluating the IoT security attacks that target objects in the pervasive IoT environment, after retrieving all the login requests made through the open SSH connection we then provide a comprehensive analysis along with our observations about the origin of the requests and the focus areas of intruders; in this study.
{"title":"Cyber Attacks Evaluation Targeting Internet Facing IoT: An Experimental Evaluation","authors":"N. Thilakarathne, N. .., Rakesh Kumar Mahendran","doi":"10.54216/jcim.090102","DOIUrl":"https://doi.org/10.54216/jcim.090102","url":null,"abstract":"The rapid growth of Information and Communication Technology (ICT) in the 21st century has resulted in the emergence of a novel technological paradigm; known as the Internet of Things, or IoT. The IoT, which is at the heart of today's smart infrastructure, aids in the creation of a ubiquitous network of things by simplifying interconnection between smart digital devices and enabling Machine to Machine (M2M) communication. As of now, there are numerous examples of IoT use cases available, assisting every person in this world towards making their lives easier and more convenient. The latest advancement of IoT in a variety of domains such as healthcare, smart city, smart agriculture has led to an exponential growth of cyber-attacks that targets these pervasive IoT environments, which can even lead to jeopardizing the lives of people; that is involved with it. In general, this IoT can be considered as every digital object that is connected to the Internet for intercommunication. Hence in this regard to analyze cyber threats that come through the Internet, here we are doing an experimental evaluation to analyze the requests, received to exploit the opened Secure Shell (SSH) connection service of an IoT device, which in our case a Raspberry Pi devices, which connected to the Internet for more than six consecutive days. By opening the SSH service on Raspberry Pi, it acts as a Honeypot device where we can log and retrieve all login attempt requests received to the SSH service opened. Inspired by evaluating the IoT security attacks that target objects in the pervasive IoT environment, after retrieving all the login requests made through the open SSH connection we then provide a comprehensive analysis along with our observations about the origin of the requests and the focus areas of intruders; in this study.","PeriodicalId":169383,"journal":{"name":"Journal of Cybersecurity and Information Management","volume":"165 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114602919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Health care information has great potential for improving the health care system and also providing fast and accurate outcomes for patients, predicting disease outbreaks, gaining valuable information for prediction in future, preventing such diseases, reducing healthcare costs, and improving overall health. In any case, deciding the genuine utilization of information while saving the patient's identity protection is an overwhelming task. Regardless of the amount of medical data it can help advance clinical science and it is essential to the accomplishment of all medicinal services associations, at the end information security is vital. To guarantee safe and solid information security and cloud-based conditions, It is critical to consider the constraints of existing arrangements and systems for the social insurance of information security and assurance. Here we talk about the security and privacy challenges of high-quality important data as it is used mainly by the healthcare structure and similar industry to examine how privacy and security issues occur when there is a large amount of healthcare information to protect from all possible threats. We will discuss ways that these can be addressed. The main focus will be on recently analyzed and optimized methods based on anonymity and encryption, and we will compare their strengths and limitations, and this chapter closes at last the privacy and security recommendations for best practices for privacy of preprocessing healthcare data.
{"title":"A review on Privacy-Preserving Data Preprocessing","authors":"M. Soni, Yashkumar Barot, S. Gomathi","doi":"10.54216/jcim.040202","DOIUrl":"https://doi.org/10.54216/jcim.040202","url":null,"abstract":"Health care information has great potential for improving the health care system and also providing fast and accurate outcomes for patients, predicting disease outbreaks, gaining valuable information for prediction in future, preventing such diseases, reducing healthcare costs, and improving overall health. In any case, deciding the genuine utilization of information while saving the patient's identity protection is an overwhelming task. Regardless of the amount of medical data it can help advance clinical science and it is essential to the accomplishment of all medicinal services associations, at the end information security is vital. To guarantee safe and solid information security and cloud-based conditions, It is critical to consider the constraints of existing arrangements and systems for the social insurance of information security and assurance. Here we talk about the security and privacy challenges of high-quality important data as it is used mainly by the healthcare structure and similar industry to examine how privacy and security issues occur when there is a large amount of healthcare information to protect from all possible threats. We will discuss ways that these can be addressed. The main focus will be on recently analyzed and optimized methods based on anonymity and encryption, and we will compare their strengths and limitations, and this chapter closes at last the privacy and security recommendations for best practices for privacy of preprocessing healthcare data.","PeriodicalId":169383,"journal":{"name":"Journal of Cybersecurity and Information Management","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126312247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The paper discusses major components of the proposed intrusion detection system as well as associated ideas. Dimensionality reduction solutions are highly valued for their potential to improve the efficiency of anomaly detection. Furthermore, feature selection and fusion methods are applied to optimise the system's capabilities. The following summary of network control, management, and cloud-based network processing aspects highlights operations managers, cloud resources, network function virtualization (NFV), and hardware and software components. We discuss prospective Deep Autoencoders (DAEs) applications, such as their use in the dimensionality reduction module, training methodologies, and benefits. Data transformation utilising coded representations is also graphically displayed and described in the text using an encoder and decoder system. The role of the anomaly detection via virtual network function in the suggested technique is also investigated. This component leverages a deep neural network (DNN) to identify anomalies in the 5G network's peripherals. DNN design issues, optimisation methodologies, and the trade-off between model complexity and detection efficacy are also discussed. Overall, the passage provides an overview of the proposed intrusion detection scheme, its components, and the techniques employed, underscoring their contributions to improving efficiency, accuracy, and security in Next Generation Networks.
{"title":"Maximizing Anomaly Detection Performance in Next-Generation Networks","authors":"P. ., Sarika Chaudhary","doi":"10.54216/jcim.120203","DOIUrl":"https://doi.org/10.54216/jcim.120203","url":null,"abstract":"The paper discusses major components of the proposed intrusion detection system as well as associated ideas. Dimensionality reduction solutions are highly valued for their potential to improve the efficiency of anomaly detection. Furthermore, feature selection and fusion methods are applied to optimise the system's capabilities. The following summary of network control, management, and cloud-based network processing aspects highlights operations managers, cloud resources, network function virtualization (NFV), and hardware and software components. We discuss prospective Deep Autoencoders (DAEs) applications, such as their use in the dimensionality reduction module, training methodologies, and benefits. Data transformation utilising coded representations is also graphically displayed and described in the text using an encoder and decoder system. The role of the anomaly detection via virtual network function in the suggested technique is also investigated. This component leverages a deep neural network (DNN) to identify anomalies in the 5G network's peripherals. DNN design issues, optimisation methodologies, and the trade-off between model complexity and detection efficacy are also discussed. Overall, the passage provides an overview of the proposed intrusion detection scheme, its components, and the techniques employed, underscoring their contributions to improving efficiency, accuracy, and security in Next Generation Networks.","PeriodicalId":169383,"journal":{"name":"Journal of Cybersecurity and Information Management","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115945901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The digital age has ushered in a new era of connectivity and opportunity. However, it has also made us more vulnerable to cyber threats. In recent years, we have seen a rise in the number and sophistication of cyberattacks. These attacks can have a devastating impact on businesses, governments, and individuals. This paper provides a comprehensive overview of cybersecurity threats and countermeasures. It begins by discussing the different types of cybersecurity threats, including malware, phishing, denial-of-service attacks, and data breaches. The paper then discusses the different types of cybersecurity countermeasures, including firewalls, antivirus software, and intrusion detection systems. The paper concludes by discussing strategies for mitigating risks in the digital age including 1) Investing in cybersecurity solutions, 2) Educating employees about cybersecurity best practices, and 3) Having a plan in place to respond to cyberattacks. By following these strategies, businesses, governments, and individuals can help to protect themselves from cyber threats.
{"title":"A Comprehensive Study of Cybersecurity Threats and Countermeasures: Strategies for Mitigating Risks in the Digital Age","authors":"A. Sleem","doi":"10.54216/jcim.100204","DOIUrl":"https://doi.org/10.54216/jcim.100204","url":null,"abstract":"The digital age has ushered in a new era of connectivity and opportunity. However, it has also made us more vulnerable to cyber threats. In recent years, we have seen a rise in the number and sophistication of cyberattacks. These attacks can have a devastating impact on businesses, governments, and individuals. This paper provides a comprehensive overview of cybersecurity threats and countermeasures. It begins by discussing the different types of cybersecurity threats, including malware, phishing, denial-of-service attacks, and data breaches. The paper then discusses the different types of cybersecurity countermeasures, including firewalls, antivirus software, and intrusion detection systems. The paper concludes by discussing strategies for mitigating risks in the digital age including 1) Investing in cybersecurity solutions, 2) Educating employees about cybersecurity best practices, and 3) Having a plan in place to respond to cyberattacks. By following these strategies, businesses, governments, and individuals can help to protect themselves from cyber threats.","PeriodicalId":169383,"journal":{"name":"Journal of Cybersecurity and Information Management","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122335744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we have proposed a system that will be able to forecast the sales of the e-commerce systems by using the techniques of the deep learning, the main goal of this paper is to help the business and the top management level of the company in decision making in order to provide the workplace the effectiveness and the efficiency in the workplace and to provide an efficient and effective system that it is intelligence to forecast and increase the sales of an e-commerce system, this paper will start with building an e-commerce website using different programming languages which are HTML, CSS, Django, JavaScript Bootstrap, and it this e-commerce website will have a specific database that contains different tables for the product list, the orders, and for the user information and many other tables, then the deep learning algorithms such as Deep Belief Networks and Convolutional Neural Networks will be applied in order to provide an effective system for digital marketing usage, so, it will be able to function as a marketing manager.
{"title":"Deep Learning Model for Digital Sales Increasing and Forecasting: Towards Smart E-Commerce","authors":"A. Admin","doi":"10.54216/jcim.080103","DOIUrl":"https://doi.org/10.54216/jcim.080103","url":null,"abstract":"In this paper, we have proposed a system that will be able to forecast the sales of the e-commerce systems by using the techniques of the deep learning, the main goal of this paper is to help the business and the top management level of the company in decision making in order to provide the workplace the effectiveness and the efficiency in the workplace and to provide an efficient and effective system that it is intelligence to forecast and increase the sales of an e-commerce system, this paper will start with building an e-commerce website using different programming languages which are HTML, CSS, Django, JavaScript Bootstrap, and it this e-commerce website will have a specific database that contains different tables for the product list, the orders, and for the user information and many other tables, then the deep learning algorithms such as Deep Belief Networks and Convolutional Neural Networks will be applied in order to provide an effective system for digital marketing usage, so, it will be able to function as a marketing manager.","PeriodicalId":169383,"journal":{"name":"Journal of Cybersecurity and Information Management","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126766649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cyber-attacks are the attacks that target organizations and individuals either as a tool for other activities like identity theft, stalking, etc. or with a computer as a crime object like phishing, hacking, and spamming. Cyber-attacks are rapidly increasing and making cyber security a major concern currently. When launched successfully, cyber-attacks can cause massive damage to individuals and businesses. Hence, immediate response is mandatory to contain the situation in case cyber-attacks occur. In this paper, we will discuss the history, present and future of cyber-attacks and measures for organizations to prevent those attacks in future. The ever-elusive strategies and suspicious nature of criminals should also be identified. We have outlined some of the practices to prevent those attacks while recommending incidence response measures and updates in enterprises.
{"title":"History, Present 2021 and Future of Cyber Attacks","authors":"Mohammed I. Alghamdi","doi":"10.54216/jcim.080204","DOIUrl":"https://doi.org/10.54216/jcim.080204","url":null,"abstract":"Cyber-attacks are the attacks that target organizations and individuals either as a tool for other activities like identity theft, stalking, etc. or with a computer as a crime object like phishing, hacking, and spamming. Cyber-attacks are rapidly increasing and making cyber security a major concern currently. When launched successfully, cyber-attacks can cause massive damage to individuals and businesses. Hence, immediate response is mandatory to contain the situation in case cyber-attacks occur. In this paper, we will discuss the history, present and future of cyber-attacks and measures for organizations to prevent those attacks in future. The ever-elusive strategies and suspicious nature of criminals should also be identified. We have outlined some of the practices to prevent those attacks while recommending incidence response measures and updates in enterprises.","PeriodicalId":169383,"journal":{"name":"Journal of Cybersecurity and Information Management","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127550920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Internet of Things (IoT) is an ever-expanding network of interconnected devices that enables various applications, such as smart homes, smart cities, and industrial automation. However, with the proliferation of IoT devices, security risks have increased significantly, making it necessary to develop effective intrusion detection systems (IDS) for IoT networks. In this paper, we propose an efficient IDS for complex IoT environments based on convolutional neural networks (CNNs). Our approach uses IoT traffics as input to our CNN architecture to capture representational knowledge required to discriminate different forms of attacks. Our system achieves high accuracy and low false positive rates, even in the presence of complex and dynamic network traffic patterns. We evaluate the performance of our system using public datasets and compare it with other cutting-edge IDS approaches. Our results show that the proposed system outperforms the other approaches in terms of accuracy and false positive rates. The proposed IDS can enhance the security of IoT networks and protect them against various types of cyber-attacks.
{"title":"Securing the IoT: An Efficient Intrusion Detection System Using Convolutional Network","authors":"H. Yas, Manal M. Nasir","doi":"10.54216/jcim.010105","DOIUrl":"https://doi.org/10.54216/jcim.010105","url":null,"abstract":"The Internet of Things (IoT) is an ever-expanding network of interconnected devices that enables various applications, such as smart homes, smart cities, and industrial automation. However, with the proliferation of IoT devices, security risks have increased significantly, making it necessary to develop effective intrusion detection systems (IDS) for IoT networks. In this paper, we propose an efficient IDS for complex IoT environments based on convolutional neural networks (CNNs). Our approach uses IoT traffics as input to our CNN architecture to capture representational knowledge required to discriminate different forms of attacks. Our system achieves high accuracy and low false positive rates, even in the presence of complex and dynamic network traffic patterns. We evaluate the performance of our system using public datasets and compare it with other cutting-edge IDS approaches. Our results show that the proposed system outperforms the other approaches in terms of accuracy and false positive rates. The proposed IDS can enhance the security of IoT networks and protect them against various types of cyber-attacks.","PeriodicalId":169383,"journal":{"name":"Journal of Cybersecurity and Information Management","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129014801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the field of cryptography, new tasks are generated when advancement has taken place from conventional computing to quantum computing. In the case of computer security, cryptography had always been a valuable and essential tool. When quantum mechanics principles are applied to cryptography, it gives rise to a new system that will secure communication and also assures that no spying can take place. The work below presents the review on quantum cryptography, which includes the concept of quantum cryptography and what can be its evaluation measures. Articles of quantum cryptography from various databases have been studied. In this SLR various research questions are identified and on the basis of the results of their answers have been formulated for this review along with that various performance measures are also discussed.
{"title":"Systematic Literature Review on Quantum Cryptography","authors":"M. Sandhu, Manav .., Rupinder Kaur","doi":"10.54216/jcim.070101","DOIUrl":"https://doi.org/10.54216/jcim.070101","url":null,"abstract":"In the field of cryptography, new tasks are generated when advancement has taken place from conventional computing to quantum computing. In the case of computer security, cryptography had always been a valuable and essential tool. When quantum mechanics principles are applied to cryptography, it gives rise to a new system that will secure communication and also assures that no spying can take place. The work below presents the review on quantum cryptography, which includes the concept of quantum cryptography and what can be its evaluation measures. Articles of quantum cryptography from various databases have been studied. In this SLR various research questions are identified and on the basis of the results of their answers have been formulated for this review along with that various performance measures are also discussed.","PeriodicalId":169383,"journal":{"name":"Journal of Cybersecurity and Information Management","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130291237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Internet of Things (IoT) has revolutionized the way we interact with everyday objects, enabling devices to collect and share data seamlessly. However, this increased connectivity has also increased the security risks associated with these devices, as they often lack the necessary security mechanisms to prevent malicious attacks. To address this issue, we propose using blockchain technology to secure IoT devices. In this paper, we present a proof-of-concept implementation of a blockchain-based IoT security system and analyze its effectiveness. Our system leverages blockchain's distributed ledger technology to ensure data integrity, decentralization, and transparency, making it more resilient to attacks. We evaluate our system's performance and compare it with other existing IoT security solutions. Our results show that our blockchain-based approach outperforms traditional security measures and is a viable solution for securing IoT devices. Finally, we discuss the limitations of our study and suggest future research directions for improving the security of IoT devices.
{"title":"Securing the Internet of Things (IoT) with Blockchain: A Proof-of-Concept Implementation and Analysis","authors":"Mahmoud A. Zaher, N. M. Eldakhly","doi":"10.54216/jcim.100203","DOIUrl":"https://doi.org/10.54216/jcim.100203","url":null,"abstract":"The Internet of Things (IoT) has revolutionized the way we interact with everyday objects, enabling devices to collect and share data seamlessly. However, this increased connectivity has also increased the security risks associated with these devices, as they often lack the necessary security mechanisms to prevent malicious attacks. To address this issue, we propose using blockchain technology to secure IoT devices. In this paper, we present a proof-of-concept implementation of a blockchain-based IoT security system and analyze its effectiveness. Our system leverages blockchain's distributed ledger technology to ensure data integrity, decentralization, and transparency, making it more resilient to attacks. We evaluate our system's performance and compare it with other existing IoT security solutions. Our results show that our blockchain-based approach outperforms traditional security measures and is a viable solution for securing IoT devices. Finally, we discuss the limitations of our study and suggest future research directions for improving the security of IoT devices.","PeriodicalId":169383,"journal":{"name":"Journal of Cybersecurity and Information Management","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116023637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We introduce our idea about a new face mask against Covid-19. Herein our novel face mask is a polymeric matrix of nanofibers. These nanofibers are decorated with special engineered nanocomposite. The later possesses antiviral, antimicrobial. A well-established IR temperature biosensor will be implanted in the face mask and connected to the mobile phone using App (Seek thermal) to allow temperature monitoring. Artificial Intelligence can play a vital role in the fight against COVID-19. AI is being successfully used in the identification of disease clusters, monitoring of cases, prediction of the future outbreaks, mortality risk, diagnosis of COVID-19, disease management by resource allocation, facilitating training, record maintenance and pattern recognition for studying the disease trend. Therefore, AI is used as a type of alarm which be connected through Global Position System (GPS) to a central networking system to monitor the crowded areas of probable infections. In this case, the hospital in this neighborhood will be charged to let a mobile unit of assessment travel quickly to the infected people areas.
{"title":"A Novel Artificial Face Mask based Nanofibers with Special Intelligent Engineered Nanocomposite Against Covid-19","authors":"Ahmed A. Elngar, S. El-dek","doi":"10.54216/jcim.050203","DOIUrl":"https://doi.org/10.54216/jcim.050203","url":null,"abstract":"We introduce our idea about a new face mask against Covid-19. Herein our novel face mask is a polymeric matrix of nanofibers. These nanofibers are decorated with special engineered nanocomposite. The later possesses antiviral, antimicrobial. A well-established IR temperature biosensor will be implanted in the face mask and connected to the mobile phone using App (Seek thermal) to allow temperature monitoring. Artificial Intelligence can play a vital role in the fight against COVID-19. AI is being successfully used in the identification of disease clusters, monitoring of cases, prediction of the future outbreaks, mortality risk, diagnosis of COVID-19, disease management by resource allocation, facilitating training, record maintenance and pattern recognition for studying the disease trend. Therefore, AI is used as a type of alarm which be connected through Global Position System (GPS) to a central networking system to monitor the crowded areas of probable infections. In this case, the hospital in this neighborhood will be charged to let a mobile unit of assessment travel quickly to the infected people areas.","PeriodicalId":169383,"journal":{"name":"Journal of Cybersecurity and Information Management","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114432785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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