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• Open Access   Article

  Information Systems Research Methodologies: A Systematic Review on Cloud Adoption, Usage and Performance

  Atuluku Amichi Ruth, Osang Francis Bukie, Adebiyi Ayodele Ariyo

  Review Paper | Journal-Paper (IJSRCSE)

  Vol.11 , Issue.5 , pp.1-15, Oct-2023

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  Abstract
  Research design and outcome are significantly influenced by the research methodology used in a study. Therefore, using the appropriate approach for each research project will allow researchers to obtain the desired outcome, whereas using the incorrect methodology will produce unreliable and inaccurate results. Nowadays, inexperienced researchers tend to focus more on the outcome than the process. The study of ICT research methods is therefore crucial. This study is based on secondary data that is already available. In this study, the components of ICT research methodologies were covered, with a focus on comparing the methodologies in terms of their strengths and limitations. The study also provided a methodological analysis of the body of research on the adoption, use, and performance of cloud computing across a five-year period. Between 2018 and 2022, 51 papers from peer-reviewed journals were analyzed. The results showed that most of the literature currently available on the adoption, usage, and performance of cloud computing uses a quantitative study methodology. For data analysis, the investigations primarily used partial least squares structural equation modeling (PLS-SEM). This paper makes a novel contribution to the field of information systems research by helping researchers comprehend the standards they might use to select methods for tackling particular issues. The ability to distinguish between research methodology/design and research data collection methods/method choices will also help scholars choose an appropriate research methodology for ICT research in the future.

  Key-Words / Index Term
  Research Methodology, Research Method, Methodology, ICT, Software Development Methodology, Cloud Computing, and Information Systems

  References
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  Citation
  Atuluku Amichi Ruth, Osang Francis Bukie, Adebiyi Ayodele Ariyo, "Information Systems Research Methodologies: A Systematic Review on Cloud Adoption, Usage and Performance," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.5, pp.1-15, 2023

• Open Access   Article

  A Survey on the Applications of Machine Learning in Identifying Predominant Network Attacks

  Heyshanthini Pandiyakumari S., Jaya R.

  Survey Paper | Journal-Paper (IJSRCSE)

  Vol.11 , Issue.5 , pp.16-22, Oct-2023

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  Abstract
  Over the past decade, there has been an unprecedented surge in the number of intelligent devices, and in recent years, the proliferation of intelligent machines has surged significantly. Computer networks play a vital role in ensuring uninterrupted connectivity among interconnected IoT devices. The substantial increase in the use of smart devices has unfortunately paved the way for substantial unethical activities within networks. This study focuses on the predominant network threat known as the “Low Rate/Slow Denial of Service (LDoS) attack” which poses a substantial risk to the internet`s integrity. Detecting the source of these attacks is exceptionally challenging because they do not generate high volumes of traffic or sudden spikes in network activity. This survey explores the application of machine learning to enhance the detection of such attacks, aiming to achieve improved performance.

  Key-Words / Index Term
  LDoS attack, DDoS attack, Anomaly detection, ML, RL, IDS, Hyperparameter optimization

  References
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  [12] Wei shi, Dann tang, Sijia Zhan, Zheng Qin and Xiyin wang, “An approach for detecting LDoS attack based on cloud model,” Forensics of computer science, Springer, Vol.16, Issue.166821, 2022, https://doi.org/10.1007/s11704-022-0486-1.
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  Citation
  Heyshanthini Pandiyakumari S., Jaya R., "A Survey on the Applications of Machine Learning in Identifying Predominant Network Attacks," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.5, pp.16-22, 2023

• Open Access   Article

  Economic Effects of Covid-19 Outbreak on Airlines’ Performance in Nigeria

  M.S. Stephens, I. Njoku, K.E. Andero

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.11 , Issue.5 , pp.23-38, Oct-2023

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  Abstract
  The outbreak of the Covid-19 pandemic really affected all airlines across the globe. It was not the first of its kind, as we have had several other outbreaks like Lassa fever, Ebola, etc. The study however focuses on the effect of covid-19 outbreak on airlines in Nigeria. This research then made comparison of the data collected from five airlines which include Air Peace, Arik Air, Dana Air, Overland Air, and Aero Contractor. The period of data collection was from the year 2012 to 2022, and the data gathered were analyzed based on the distance, Kl traffic and Output (RPK) to compare the performance of each airline before the outbreak of the Covid-19 disease in the year 2019. The objectives were to examine how the outbreak of covid-19 has affected the passenger flow of airlines in Nigeria, to assess the effect of the outbreak on routes of airlines flying to and within of Nigeria; and to determine the adequacy of measures that were put in place by the airlines to regain market shares and revenue to pre covid-19 era. The study then examines the data using the Distance, K traffic as the independent variables and the Output as the Dependent variable. The study recommends that Airlines should put all necessary health measures in place in order to discover the possibility of any disease that could lead to a global pandemic thereby shutting down all economic activities. Airlines should ensure that all Covid-19 protocols are put in place in order to stop the further spread of the disease.

  Key-Words / Index Term
  Covid-19 pandemic, performance, passenger flow, market shares, revenue, variables

  References
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  Citation
  M.S. Stephens, I. Njoku, K.E. Andero, "Economic Effects of Covid-19 Outbreak on Airlines’ Performance in Nigeria," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.5, pp.23-38, 2023

• Open Access   Article

  Application of Self Adaptive Differential Evolution for Design of Modern Intrusion Detection System

  Manas Kumar Yogi, Yamuna Mundru

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.11 , Issue.5 , pp.39-47, Oct-2023

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  Abstract
  Intrusion detection plays a pivotal role in safeguarding modern computer networks and systems from evolving cyber threats. To enhance the efficacy of intrusion detection systems (IDS) in detecting diverse and dynamic attack patterns, researchers have increasingly turned to optimization algorithms. Among these, the Differential Evolution (DE) algorithm has emerged as a promising candidate due to its ability to iteratively refine parameter configurations for complex systems. This paper explores the application of the Self Adaptive DE algorithm in intrusion detection. It discusses the conceptual framework of integrating DE with intrusion detection, highlighting the steps involved in parameter optimization and its implications for improving IDS performance. The paper further delves into key challenges, such as addressing adversarial attacks, real-time adaptation, and hybridization with other techniques, scalability, and the interpretability of results. By analyzing the potential future directions and research avenues in this domain, this paper provides a comprehensive overview of the role of Self Adaptive DE in enhancing the capabilities of intrusion detection systems and bolstering cyber defense mechanisms.

  Key-Words / Index Term
  Differential Evolution, Security, Intrusion, Malicious, Mutation

  References
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  Citation
  Manas Kumar Yogi, Yamuna Mundru, "Application of Self Adaptive Differential Evolution for Design of Modern Intrusion Detection System," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.5, pp.39-47, 2023

• Open Access   Article

  Survey on Mobile Phone Threat: Detection and Prevention Techniques

  Adamu Shehu, Yakubu Ernest Nwuku, Egere N. Augustine, Muhammad A. Bilyaminu, Muhammed Usman, Ibrahim Abdu

  Survey Paper | Journal-Paper (IJSRCSE)

  Vol.11 , Issue.5 , pp.48-53, Oct-2023

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  Abstract
  The increasing popularity and convenience of mobile phones have made them indispensable tools for personal and corporate tasks. However, this portability also exposes sensitive data, such as credit card details, login credentials, and private contacts, to potential malware attacks, such malwares are Android GMBots, AceDeceiver IOS Malware, Marcher (ExoBot), backdoor and roots exploits, etc. As mobile phones are vulnerable to malware attacks, it is crucial to implement robust security methods such existing methods as anti-virus, Naïve-Bayes, SVM, MTM base mobile security, etc. to detect and prevent potential threats. In this research, we delineate diverse methods for identifying and thwarting mobile phone attacks. We undertake a comparative assessment of their susceptibilities and put forth the most efficacious approach and framework to bolster mobile security. The study discovered Pre-Crime Cloud Service Scheme and MTM base security are been rated the best mobile security defense against malware and potential security threats. It is recommended that continuous user awareness and exploring different new mobile security techniques for the detection and prevention of potential malware attacks.

  Key-Words / Index Term
  Mobile phone, threat, detection, prevention, techniques

  References
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  Chao-Tung Yang, "An Internal Intrusion Detection and Protection System by Using Data Mining and Forensic Techniques," IEEE Systems Journal, vol. 11, no. 2, pp. 427-438, 2017.
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  Security Technology and Preventive Measures under the Information Environment," 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE), Harbin, China, pp. 1978-1981, 2020
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  Citation
  Adamu Shehu, Yakubu Ernest Nwuku, Egere N. Augustine, Muhammad A. Bilyaminu, Muhammed Usman, Ibrahim Abdu, "Survey on Mobile Phone Threat: Detection and Prevention Techniques," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.5, pp.48-53, 2023

• Open Access   Article

  An Efficient Context-dependent Lexical Information Detection using Word Embeddings and Deep Machine Learning Classifiers for Unstructured Textual Contents

  Amit Shukla, Rajendra Gupta

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.11 , Issue.5 , pp.54-59, Oct-2023

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  Abstract
  The term "context dependent" refers to a type of word representation that enables machine learning algorithms to distinguish words that have similar meanings. It is a feature learning technique that uses probabilistic models, dimension reduction, or neural networks on the word co-occurrence vector matrix to map words into real-number vectors. We address the problem of recognizing unstructured context-dependent lexical information in unstructured data containers in the research study. We investigate a method that employs word embedding for automatic context and relevant feature detection, as well as a deep neural network for classification. Using publicly accessible tweet and image datasets, we present an alternative model that use Conventional Machine Learning (CML) classifiers and a rule-based model. The proposed method outperforms the alternatives of earlier research. The CLID is analysed in terms of four aspects on the basis of Context-Centred Extraction of Concepts (CCEC). The proposed word embeddings method CCEC gives benefit from a neural-network methods ability to encode textual information by converting meaningful text information into numeric values.

  Key-Words / Index Term
  Context-dependent Lexical Information, Word Embeddings, Deep ML Classifier, Unstructured Textual Contents

  References
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  Citation
  Amit Shukla, Rajendra Gupta, "An Efficient Context-dependent Lexical Information Detection using Word Embeddings and Deep Machine Learning Classifiers for Unstructured Textual Contents," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.5, pp.54-59, 2023

• Open Access   Article

  Analysis of 419 Scams: The Trends and New Variants in Emerging Types

  Polra Victor Falade

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.11 , Issue.5 , pp.60-74, Oct-2023

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  Abstract
  The rapid advancement of technology has brought about significant transformations in various facets of human existence, ushering in an era of improved communication, streamlined business operations, enhanced healthcare, accessible education, and efficient environmental monitoring. Nonetheless, this escalating reliance on technology has also given rise to a notable upsurge in cybercrime, with cyber scams proliferating as a concerning subset of these criminal activities. Among the enduring cyber scams, the "419 scam," colloquially known as the Nigerian scam, has persisted for decades, encompassing a spectrum of fraudulent activities such as advance fee scams, counterfeit lotteries, and black money schemes. Originally disseminated via postal mail and subsequently through fax, this fraudulent endeavour has now transitioned to email as its primary medium of operation. This research endeavour seeks to discern contemporary manifestations of 419 scam emails, particularly in the aftermath of the COVID-19 pandemic, and delve into the prevalent email subjects employed in these deceptive communications. Examination of a sample of 419 scam emails has unveiled an array of trending scams, which include but are not limited to the "lucky winner," "threat of exposure," "business/partnership proposals," "investment," "cancer/long-term illness," "fund," and "compensation" scams. Concurrently, emerging scams in the post-pandemic landscape encompass COVID-related scams, cryptocurrency schemes, marketing contact swindles, and fraudulent software development offers. Irrespective of the specific scam archetype, a shared facet is the recurring utilization of specific email subjects such as `Re,` `Good day,` `Greetings,` `Dear friend,` `Confirm,` `Attention,` and `Hello dear` by these fraudulent actors. The implications of cybercrime, particularly the tenacious 419 scams, are profound, encompassing the erosion of trust, substantial financial losses incurred by individuals and organizations alike, and detriment to Nigeria`s international reputation and economic progress. Consequently, it is imperative to undertake concerted efforts to combat cyber scams and bolster cybersecurity measures. These endeavours are indispensable in safeguarding individuals and entities against the perils of these deceptive schemes, ultimately contributing to the preservation of digital integrity and security.

  Key-Words / Index Term
  Scams, 419 scams, cybercrime, emails, Nigerian scams, cybersecurity

  References
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  Citation
  Polra Victor Falade, "Analysis of 419 Scams: The Trends and New Variants in Emerging Types," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.5, pp.60-74, 2023

• Open Access   Article

  Malaria Parasite Detection from RBCs Images Using Deep Learning Techniques

  Gais Alhadi Babikir, Awadallah M. Ahmed, Lamyaa Alser Mohammed

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.11 , Issue.5 , pp.75-81, Oct-2023

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  Abstract
  Malaria is one the life-threaten diseases spread in many countries worldwide with high infection rates in tropical and subtropical countries. According to WHO half of the world`s population is at risk of malaria, and nearly every minute malaria kills a child in the world. Fortunately, this disease is preventable and treatable but accurate and fast diagnosis is a crucial stage of malaria treatment. Many methods have been used in malaria detection ranging from traditional that are based on human experts and microscopes to machine-based methods that depend on machine learning and deep learning. This paper proposes a deep-learning method for malaria detection from RBCs images. Obviously, three transfer learning models (MobileNet, Xception, and InceptionV3) were proposed and compared based on their precision, recall, f1-Score, and accuracy. Hence, by comparing the three models, the MobileNet model is the best in terms of overall accuracy (99.04%), we can confirm that with the results of area under the curve (0.981). Therefore, the pre-trained MobileNet model can effectively contribute to malaria classification from RBCs images.

  Key-Words / Index Term
  Disease Detection, Malaria, CNN, Deep Learning Techniques, MobileNet, Xception, InceptionV3

  References
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  Citation
  Gais Alhadi Babikir, Awadallah M. Ahmed, Lamyaa Alser Mohammed, "Malaria Parasite Detection from RBCs Images Using Deep Learning Techniques," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.5, pp.75-81, 2023

• Open Access   Article

  Clustering Improvement in Homonym Detection using Concept Based Document Similarity with Conceptual Term Frequency Analysis

  Sunil Kumar, Rajendra Gupta

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.11 , Issue.5 , pp.82-87, Oct-2023

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  Abstract
  The homonym words have the same spelling but have different meanings and these words found in almost every language. The homonyms are a source of noise in most text analysis and are difficult to detect. It essentially understands to make correspond to combinations of identifying / difference in parameters like sound, writing, and meaning, according to how the terms are traditionally used; the combination of same sound, same spelling, but distinct meaning is for homonyms. The paper presents a clustering improvement analysis using concept based document similarity method for homonym recognition based on concept based document similarity, which allows a word to be comprehended based on its context. The results show the proposed method shows better performance in clustering improvement and entropy calculation.

  Key-Words / Index Term
  Concept based Document Similarity, Homonym Words, Clustering, Entropy

  References
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  Citation
  Sunil Kumar, Rajendra Gupta, "Clustering Improvement in Homonym Detection using Concept Based Document Similarity with Conceptual Term Frequency Analysis," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.5, pp.82-87, 2023

• Open Access   Article

  Integrated Management of Patient Health Records with Smart Card and Its Benefits

  Patel Karika Digesh

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.11 , Issue.5 , pp.88-92, Oct-2023

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  Abstract
  The healthcare system is facing critical issues with the effective and efficient storage and retention of patient health records. As information technology is gradually becoming more important nowadays, its use in health records has become crucial. The challenge of present documentation in electronic health records (EHRs) is that there is not enough documentation to demonstrate the quality and necessity of care. Common errors in using the EHRs were found to be more like scattered and discrete data without integration, which ultimately were not usable. Smart cards may be utilized for integrated health records and to simplify the prescription process, facilitate the delivery of care, and improve the standard of care given. Smart cards are portable integrated devices with data storage and data processing capabilities. The research paper focuses on how smart card technology can be applied to an essential and vital sector of healthcare. The system uses smartcards for personal identification and transfer of health data and provides data communication. In addition to personal information, general health information about the patient is also loaded onto the patient’s smart card. Healthcare providers use smart cards to access data about patients. Electronic health records with smart card usage enhance the integrated approach and have several advantages over paper records such as improving the accuracy, and quality of patient care, and reducing cost, efficiency, and productivity.

  Key-Words / Index Term
  Patient, Integrated, Smart card, patient health record (PHR), RFID, OTP, Cloud, Electronic Health Record (EHR), Accessibility, Availability, Security, Cloud storage.

  References
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  Citation
  Patel Karika Digesh , "Integrated Management of Patient Health Records with Smart Card and Its Benefits," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.5, pp.88-92, 2023