Asian Journal of Research in Computer Science最新文献

{"title":"Design and Implementation of an Online Blood Donation System","authors":"Tahiru Abdul-Gafaru, D. S. Laar, Kennedy Kumangkem Kubuga","doi":"10.9734/ajrcos/2024/v17i4429","DOIUrl":"https://doi.org/10.9734/ajrcos/2024/v17i4429","url":null,"abstract":"Blood donation is a critical component of healthcare, saving countless lives each year. However, many regions, including Ghana, face chronic shortages of blood supply, often resulting in life-threatening delays for patients in need. Traditional blood donation methods are plagued with inefficiencies, causing delays in matching donors with recipients, and hindered by cumbersome paperwork that discourages potential donors. To address these challenges, this paper introduces an Online Blood Donation System, which offers an accessible, efficient, and secure platform for connecting blood donors with those in need. The project encompasses a comprehensive study, employing the Agile methodology, HTML, CSS, JavaScript, PHP, and MySQL, to design and develop the system. The system's objectives encompass facilitating blood donation, enhancing efficiency, increasing donor participation, ensuring data security, promoting awareness, and overall healthcare system improvement. This project aims to contribute to the healthcare sector by providing an innovative solution to blood donation challenges, ultimately saving lives and improving healthcare efficiency.","PeriodicalId":505559,"journal":{"name":"Asian Journal of Research in Computer Science","volume":"45 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139961985","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}

{"title":"Hybrid Approach to Classification of DDoS Attacks on a Computer Network Infrastructure","authors":"Enock Quansah Effah, E. O. Osei, Maxwell Dorgbefu Jnr., Abraham Tetteh","doi":"10.9734/ajrcos/2024/v17i4428","DOIUrl":"https://doi.org/10.9734/ajrcos/2024/v17i4428","url":null,"abstract":"The advancement in technology, its ease of use, and the competitive nature of its deployment in business operations have led to the wide spread of networking systems globally, and Ghana is not an exception. Most business operations and even personal activities are now conducted online leading to increased network connectivity, access to networked resources, and the corresponding cyber-attacks on these network systems. Distributed Denial-of-Service (DDoS) is one of the sophisticated attacks in the cyberspace. In DDOs, the attacker floods the network with massive and unsolicited traffic, causing the network infrastructure to exhaust all its resources in responding to the attacker’s request, thereby denying access to legitimate users of such resources. In this study, we designed and implemented a hybrid deep learning model (CRNN-Infusion) for detection and classification of DDoS attacks. Our model utilized the CNN, and RNN models, with the CICDDoS2019 dataset obtained from the Canadian Institute of Cybersecurity (CIC) for its training, with Random Search Hyperparameter Tuning (RSHT) and Feature Selection (FS) techniques for model efficiency and dimensionality reduction. Cybersecurity (CIC) for the model’s training, with Random Search Hyperparameter Tuning (RSHT) and FS techniques for model efficiency and dimensionality reduction. The results showed that, our proposed model is a better classifier for DDoS attacks compared to other deep learning (DL) models trained on the same dataset. With the highest accuracy of 98.92%, hybrid deep learning models are suitable for detecting and classifying DDoS attacks on network infrastructures. The findings point out that, with the appropriate choice of feature selection and hyperparameter tuning techniques, hybrid deep learning models perform optimally, with 98.92% accuracy, 99.02% precision, 98.92% recall, and 98.93% F1 score for our proposed model.","PeriodicalId":505559,"journal":{"name":"Asian Journal of Research in Computer Science","volume":"97 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139842351","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}

{"title":"Hybrid Approach to Classification of DDoS Attacks on a Computer Network Infrastructure","authors":"Enock Quansah Effah, E. O. Osei, Maxwell Dorgbefu Jnr., Abraham Tetteh","doi":"10.9734/ajrcos/2024/v17i4428","DOIUrl":"https://doi.org/10.9734/ajrcos/2024/v17i4428","url":null,"abstract":"The advancement in technology, its ease of use, and the competitive nature of its deployment in business operations have led to the wide spread of networking systems globally, and Ghana is not an exception. Most business operations and even personal activities are now conducted online leading to increased network connectivity, access to networked resources, and the corresponding cyber-attacks on these network systems. Distributed Denial-of-Service (DDoS) is one of the sophisticated attacks in the cyberspace. In DDOs, the attacker floods the network with massive and unsolicited traffic, causing the network infrastructure to exhaust all its resources in responding to the attacker’s request, thereby denying access to legitimate users of such resources. In this study, we designed and implemented a hybrid deep learning model (CRNN-Infusion) for detection and classification of DDoS attacks. Our model utilized the CNN, and RNN models, with the CICDDoS2019 dataset obtained from the Canadian Institute of Cybersecurity (CIC) for its training, with Random Search Hyperparameter Tuning (RSHT) and Feature Selection (FS) techniques for model efficiency and dimensionality reduction. Cybersecurity (CIC) for the model’s training, with Random Search Hyperparameter Tuning (RSHT) and FS techniques for model efficiency and dimensionality reduction. The results showed that, our proposed model is a better classifier for DDoS attacks compared to other deep learning (DL) models trained on the same dataset. With the highest accuracy of 98.92%, hybrid deep learning models are suitable for detecting and classifying DDoS attacks on network infrastructures. The findings point out that, with the appropriate choice of feature selection and hyperparameter tuning techniques, hybrid deep learning models perform optimally, with 98.92% accuracy, 99.02% precision, 98.92% recall, and 98.93% F1 score for our proposed model.","PeriodicalId":505559,"journal":{"name":"Asian Journal of Research in Computer Science","volume":"15 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139782216","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}

{"title":"An Overview of Iot Architecture Security Issues and Countermeasures","authors":"Walla Khalaifat","doi":"10.9734/ajrcos/2024/v17i4427","DOIUrl":"https://doi.org/10.9734/ajrcos/2024/v17i4427","url":null,"abstract":"The Internet of Things (IoT) has revolutionized the way we interact with our surroundings. As the number of IoT devices continues to increase, along with limited resources and diverse technologies, the risk of security attacks increases. Therefore, it is important to integrate security measures throughout the development process and system architecture. However, it is crucial to continually assess and update security measures to avoid emerging threats and ensure the confidentiality, integrity, and availability of IoT systems. This study aims to explore security issues in the IoT, highlighting the associated challenges. It examines various threats, attacks, and vulnerabilities that arise within a three-layer architecture and discusses potential solutions to enhance security in each layer. By addressing these concerns, it is possible to establish a secure and reliable foundation for expanding IoT systems.","PeriodicalId":505559,"journal":{"name":"Asian Journal of Research in Computer Science","volume":"70 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139854798","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}

{"title":"An Overview of Iot Architecture Security Issues and Countermeasures","authors":"Walla Khalaifat","doi":"10.9734/ajrcos/2024/v17i4427","DOIUrl":"https://doi.org/10.9734/ajrcos/2024/v17i4427","url":null,"abstract":"The Internet of Things (IoT) has revolutionized the way we interact with our surroundings. As the number of IoT devices continues to increase, along with limited resources and diverse technologies, the risk of security attacks increases. Therefore, it is important to integrate security measures throughout the development process and system architecture. However, it is crucial to continually assess and update security measures to avoid emerging threats and ensure the confidentiality, integrity, and availability of IoT systems. This study aims to explore security issues in the IoT, highlighting the associated challenges. It examines various threats, attacks, and vulnerabilities that arise within a three-layer architecture and discusses potential solutions to enhance security in each layer. By addressing these concerns, it is possible to establish a secure and reliable foundation for expanding IoT systems.","PeriodicalId":505559,"journal":{"name":"Asian Journal of Research in Computer Science","volume":"6 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139795001","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}

{"title":"Securing Tomorrow: The Intersection of AI, Data, and Analytics in Fraud Prevention","authors":"Pankaj Gupta","doi":"10.9734/ajrcos/2024/v17i3425","DOIUrl":"https://doi.org/10.9734/ajrcos/2024/v17i3425","url":null,"abstract":"Aim: This research investigates the interconnections among Data Analytics, Artificial Intelligence, and other cutting-edge technologies to enhance comprehension of fraud prevention. The advantages of integrating machine learning and data analytics into artificial intelligence systems for industry-wide fraud detection and prevention are examined in this study.\u0000Study Design: My approach involved conducting an extensive examination of existing literature and analysing numerous case studies to gather information on the role of artificial intelligence, data, and analytics in fraud prevention.\u0000Place and Duration of the Study: A broad spectrum of academic, corporate, and governmental sources is utilised to supply the research study with its international scope. This study examines publications and developments from 2019 to 2023.\u0000Methodology: The research procedure incorporated an exhaustive literature review. This assessment was composed of academic journals, conference proceedings, and official publications. A qualitative analysis was conducted to assess the data, identify commonalities, and evaluate the strengths and weaknesses of AI fraud protection solutions. A more comprehensive examination of practical implementations was facilitated by case studies, which enhanced comprehension of fraud prevention strategies propelled by AI.\u0000Results: The research revealed important findings concerning the various ways in which analytics, data, and artificial intelligence can be implemented to prevent fraudulent activities. An examination of comparisons between generative AI for social engineering, credit card analytics, and cyber-physical security for Internet of Things (IoT) networks illuminated the merits and demerits of different Artificial Intelligence (AI) approaches.\u0000Conclusion: According to the findings of the study, AI, data, and analytics may alter system defences against fraud. The above-mentioned results underscore the significance of flexible fraud prevention strategies. Constant collaboration, innovative technology, and ongoing investigation are required to remain ahead of evolving fraud techniques. The paper concludes by emphasising the significance of future challenges and orientations.","PeriodicalId":505559,"journal":{"name":"Asian Journal of Research in Computer Science","volume":"24 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139805842","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}

{"title":"Implementation of a Secured Scalable File Server System","authors":"Arnold Mashud Abukari, Fred Yao Mensah, Jhansi Bharathi Madavarapu","doi":"10.9734/ajrcos/2024/v17i3426","DOIUrl":"https://doi.org/10.9734/ajrcos/2024/v17i3426","url":null,"abstract":"This research paper proposed and developed a blueprint for a secured scalable file server system for organisations that can handle large volumes of data, accommodate numerous users with varying levels of access and permissions and adhere to all security and compliance standards of organisations. With the implementation of this secured and scalable file server system, users of all levels will be able to access, manipulate, transfer files easily devoid of any data lost, file corruption or fear of getting infested with virus when sharing using flash drives. System administrators will be able to backup files easily to forestall any unforeseen circumstances and finally the organisation’s Management will be able to have full control of all data that is used in the organisation. The proposed system is a scalable file server designed for digital file management. This secured and scalable file server system provided a secure and user-friendly interface allowing organisation's staff to efficiently store, retrieve, and share files. The proposed system at its heart, provide strong data storage capabilities that will easily meet data growing needs.","PeriodicalId":505559,"journal":{"name":"Asian Journal of Research in Computer Science","volume":"10 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139803887","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}

{"title":"Implementation of a Secured Scalable File Server System","authors":"Arnold Mashud Abukari, Fred Yao Mensah, Jhansi Bharathi Madavarapu","doi":"10.9734/ajrcos/2024/v17i3426","DOIUrl":"https://doi.org/10.9734/ajrcos/2024/v17i3426","url":null,"abstract":"This research paper proposed and developed a blueprint for a secured scalable file server system for organisations that can handle large volumes of data, accommodate numerous users with varying levels of access and permissions and adhere to all security and compliance standards of organisations. With the implementation of this secured and scalable file server system, users of all levels will be able to access, manipulate, transfer files easily devoid of any data lost, file corruption or fear of getting infested with virus when sharing using flash drives. System administrators will be able to backup files easily to forestall any unforeseen circumstances and finally the organisation’s Management will be able to have full control of all data that is used in the organisation. The proposed system is a scalable file server designed for digital file management. This secured and scalable file server system provided a secure and user-friendly interface allowing organisation's staff to efficiently store, retrieve, and share files. The proposed system at its heart, provide strong data storage capabilities that will easily meet data growing needs.","PeriodicalId":505559,"journal":{"name":"Asian Journal of Research in Computer Science","volume":"65 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139863451","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}

{"title":"Securing Tomorrow: The Intersection of AI, Data, and Analytics in Fraud Prevention","authors":"Pankaj Gupta","doi":"10.9734/ajrcos/2024/v17i3425","DOIUrl":"https://doi.org/10.9734/ajrcos/2024/v17i3425","url":null,"abstract":"Aim: This research investigates the interconnections among Data Analytics, Artificial Intelligence, and other cutting-edge technologies to enhance comprehension of fraud prevention. The advantages of integrating machine learning and data analytics into artificial intelligence systems for industry-wide fraud detection and prevention are examined in this study.\u0000Study Design: My approach involved conducting an extensive examination of existing literature and analysing numerous case studies to gather information on the role of artificial intelligence, data, and analytics in fraud prevention.\u0000Place and Duration of the Study: A broad spectrum of academic, corporate, and governmental sources is utilised to supply the research study with its international scope. This study examines publications and developments from 2019 to 2023.\u0000Methodology: The research procedure incorporated an exhaustive literature review. This assessment was composed of academic journals, conference proceedings, and official publications. A qualitative analysis was conducted to assess the data, identify commonalities, and evaluate the strengths and weaknesses of AI fraud protection solutions. A more comprehensive examination of practical implementations was facilitated by case studies, which enhanced comprehension of fraud prevention strategies propelled by AI.\u0000Results: The research revealed important findings concerning the various ways in which analytics, data, and artificial intelligence can be implemented to prevent fraudulent activities. An examination of comparisons between generative AI for social engineering, credit card analytics, and cyber-physical security for Internet of Things (IoT) networks illuminated the merits and demerits of different Artificial Intelligence (AI) approaches.\u0000Conclusion: According to the findings of the study, AI, data, and analytics may alter system defences against fraud. The above-mentioned results underscore the significance of flexible fraud prevention strategies. Constant collaboration, innovative technology, and ongoing investigation are required to remain ahead of evolving fraud techniques. The paper concludes by emphasising the significance of future challenges and orientations.","PeriodicalId":505559,"journal":{"name":"Asian Journal of Research in Computer Science","volume":"46 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139865743","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}

{"title":"How can Blockchain be Integrated into Autonomous Systems to Ensure Data Integrity and Trustworthiness, and What are the Potential Pitfalls in Decentralized Autonomous System Operations?","authors":"Arda Mesci, Efe Eren","doi":"10.9734/ajrcos/2024/v17i2413","DOIUrl":"https://doi.org/10.9734/ajrcos/2024/v17i2413","url":null,"abstract":"Real-time applications always have security issues present in their ecosystem which needs to be improved. Blockchain technology can be considered as a solution that can ensure network security. The integration of blockchain technology into autonomous systems has now become an important candidate to resolve network security issues in devices that work on p2p communications. As humans become more reliant on autonomous vehicles, the importance of finding a solution to the problems linked with data security needs to be addressed to comply with international security laws. The paper aims to find the importance of blockchain technology and how it can be integrated into different classes of autonomous vehicles. In the research, an analysis of existing papers will be included along with a proposed design that can be deployed to solve the problems associated with data security using blockchain technology. Besides the improvements offered by blockchain technology, all the additional challenges associated with designing a new system and deploying this technology will be reviewed. The limitations of the works along with the future research opportunities that might open up will be presented in this paper.","PeriodicalId":505559,"journal":{"name":"Asian Journal of Research in Computer Science","volume":"2 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139380497","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}