| 1 |
Author(s):
Ele. B. I..
Page No : 1-17
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An Enhanced Mechanism for Protecting Web Applications from Cross Site Request Forgery (CSRF)
Abstract
Cross-Site Request Forgery (CSRF) is considered one of the top vulnerabilities in today’s web, where an untrusted website can force the user browser to send an unauthorized valid request to the trusted site. Legitimate users will lose their integrity over the website when the CSRF takes place. So far, many solutions have been proposed for the CSRF attacks such as the referrer HTTP header, custom HTTP header, origin header, client site proxy, a browser plug-in, and random token validation, but in this research, the use of random token validation to solve the problem of CSRF attacks was implemented. The proposed solution in the study used a concept known as Nonce which is a type of random token attached to requests sent over a server. This solution proved to be effective enough to protect and prevent web applications from CSRF attacks. Although no system can be secured against attacks, this study recommends that the random token validation (Nonce) approach of protecting web applications should be adopted by all web applications developers and users to improve on the already established solutions to reduce the chances of attacks on web applications to a very slim percentage, if not eliminated.
| 2 |
Author(s):
Ele B. I., Obono I. O., Iwinosa A. A..
Page No : 18-24
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Problem Spaces and Algorithms in Data Mining
Abstract
Data mining has been described severally as the best thing to have happened to data and information management, especially these days that the cost of computing technologies and storage media are falling, data gathering tools becoming varied and very efficient and the boom in network computing becoming very rewarding. The challenges presented by the management and meaningful usage of large data sets have stimulated so much research in data mining. Consequently, the birth of a number of algorithms to provide insights to these big data has equally presented more complications in information processing computing. Therefore, this paper presents different problem spaces in data mining, available algorithms to mine these data and then mapping specific algorithms to specific problem spaces. Analysis of datasets from a typical financial institution suggests that no one algorithm is necessarily better than the other, but all have strengths and weaknesses depending on the particular problem spaces in use.
| 3 |
Author(s):
Ele B. I., Ele A. A., Agaba F..
Page No : 25-46
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Intelligent-Based Job Applicants’ Assessment and Recruitment System
Abstract
In recent years, companies faced the challenge of sorting resumes from job applicants, assessing, recruiting, and notifying applicants manually. This study is centered on creating a system that will automate this process and resolve the problems associated with manual recruitment processes. The waterfall model was employed in the analysis and design of the system in this study due to its simplicity and sequential nature. The system was built using PHP programming language and the database was designed using MySQL. In this study, an intelligent-based job applicants’ assessment and recruitment system was developed using artificial intelligence techniques. It brings phenomenal success to Human Resource Management in a very short time. The recruitment process, in general, would experience a foremost modification, delivering rapid, efficient, and cost-effective methods of discovering prospective workers. Numerous opportunities were identified when utilizing this technology in recruitment, which include speeding up the staffing procedure, computerization of responsibilities, and rising detachment. Results obtained during the evaluation display that this method enhances the correctness of toning the right applicants with the right jobs. However, this system is still open to upgrading in the future for any researcher who finds this to be of interest.
| 4 |
Author(s):
Helena Kravarikova.
Page No : 47-57
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Verification of the Analytical Solution and Numerical Simulation for Tension – Pressure
Abstract
The proposed constructions have to meet their use in terms of shape, dimensions and above all, strength. Parts of the structure are loaded by external forces. The load on the structure is examined in all parts and directions. Parts of the structure are stressed by a combination of basic types of stress. One of the basic types of stress is pull or pressure. The investigation of the part of the structure under tensile-compression stress is important because of the deformation, stability and strength of the structure as a whole. Analytical solution, classical experiment or modelling FEM can be used to predict the stress of structural parts. Currently, the most preferred solution is FEM numerical simulation. Numerical simulation has a more purposeful use in the solution of structural stability. The article contains the solution, tensile stresses for a steel rod, numerical simulation using the FEM method in the ANSYS program and analytically.
| 5 |
Author(s):
Gideon Uchechukwu Nwafor, PhD.
Page No : 58-71
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Using Data Mining Techniques to Develop Climate Change Mitigation and Adaptation Strategies in Nigeria.
Abstract
Climate change is a severe and growing challenge facing Nigeria, with significant impacts on the country's economy, environment, and society. To cope with this challenge, there is a need for climate change mitigation and adaptation strategies that are evidence-based and tailored to the country's unique vulnerabilities and opportunities. This study aimed to develop such strategies using data mining techniques. A range of climate and non-climate data sources were explored to identify key drivers of climate change in Nigeria and their associated impacts on different sectors, such as agriculture, water resources, and energy. Subsequently, data mining algorithms, including decision trees, clustering, and association rule mining, were applied to model and analyze the complex relationships between these drivers and their impacts on the sectors. The study found that a combination of mitigation and adaptation measures could be effective in reducing the severity of climate change impacts in Nigeria. These measures include promoting the use of renewable energy sources, improving water-use efficiency, and developing climate-smart agricultural practices. The data mining techniques used in this study proved useful for identifying these measures and for predicting their effectiveness under different scenarios. The results of this study provide important insights to policymakers and practitioners in Nigeria and other countries facing similar climate change challenges. It also highlights the potential of data mining techniques for developing climate change mitigation and adaptation strategies that are evidence-based, effective, and tailored to specific local contexts. Overall, this study contributes to the growing body of literature on leveraging data mining and machine learning techniques for addressing complex environmental and societal challenges.
| 6 |
Author(s):
Adegbite Ismaila Olawale, Odetayo Tajudeen Adewale.
Page No : 72-83
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Optimal Scaling Appraisal of Maturity Status of Nigerian Polytechnic Education in Industry 4.0
Abstract
The first industrial revolution in the 18th century is related to the transformation to mechanization by using hydro power and steam power to second, third and a new concept referred to as Cyber-Physical Systems (CPS) that combine Internet of Things (IoT) technologies with the manufacturing which is seen as a significant paradigm shift in industrial manufacturing, named as Industry 4.0 (4IR). This study explored the perspectives of people on the lingering issue of maturity of Nigerian Polytechnics in terms of 4th industrial revolution; thus, the paper aimed at appraising the maturity status of Nigerian polytechnics in the industry 4.0 using Optimal Categorical Scaling Regression (Catreg). Data collection was cross-region in Nigeria. This research used the stratified sampling method to ensure a proper spread and it was designed in line with descriptive survey, systematically examining the maturity status of their institution on 4IR through the primary data collected with the aid of questionnaire and focus group discussion from the stakeholders in private and public Nigerian polytechnics. The data were sourced from 18 Polytechnics, 1 each from federal, state and private in each geographical zone. Inferential statistical tools of optimal scaling regression analysis were deployed. The analysis inferred that eagerness of leaders and competence as well as modern ICT and mobile devices are fully mature but implementation of 4IR road-map, decentralization, modelling and simulation, sharing knowledge and open innovation, ICT competence and openness to new technology are still maturing. It is recommended that the educational policy and a blueprint of education for Industry 4.0 should be formulated and implemented to meet the global standard of education.
