FACULTY OF COMPUTING

Cloud computing has revolutionized the way businesses manage their IT infrastructure, offering scalable, cost-effective, and flexible solutions. However, as organizations migrate to the cloud, cybersecurity becomes a critical concern. This paper explores how cloud computing enhances cybersecurity for businesses by leveraging advanced security mechanisms such as encryption, multi-factor authentication, artificial intelligence (AI)-driven threat detection, and automated compliance management. Cloud service providers (CSPs) offer robust security frameworks, including real-time monitoring, distributed denial of service (DDoS) protection, and secure access controls, reducing the risk of cyber threats. Additionally, cloud-based security facilitates disaster recovery, data loss prevention, and regulatory compliance, strengthening overall business resilience. While cloud computing introduces new security challenges, implementing best practices and leveraging CSP security measures can significantly enhance an organization's cybersecurity posture. This study highlights the benefits, challenges, and future trends of cloud computing
in securing business operations against evolving cyber threats. To this purpose, this project designs and implements an encryption and multi-factor authentication system for cloud computing environments using a two-factor authentication approach: first-factor authentication via user ID/email and password, and second-factor authentication via OTP sent to user email. The system is developed using HTML, CSS, JavaScript, and Viejas for the front-end, Laravel and PHP for the backend, and MySQL for the database.

The management of personnel records in many organizations remains largely manual, leading to inefficiencies, data redundancy, and delays in decision-making. This study focuses on the design and implementation of a computerized Personnel Management Information System (PMIS) to address these challenges and improve human resource management processes. The system was developed using Python as the programming language, MySQL as the database management system, and a web-based framework to ensure ease of access and usability. The proposed system automates key human resource functions, including employee registration, attendance tracking, leave management, payroll computation, and report generation. A modular approach was adopted during implementation, ensuring each system component operates independently while maintaining seamless interaction with the central database. Testing was conducted using unit testing, integration testing, system testing, and user acceptance testing, demonstrating that the system is reliable, accurate, and efficient. The results show that the developed system significantly improves personnel data management by reducing errors, enhancing data security, and providing timely reports for informed decision making. This system offers a scalable solution that can be adopted by organizations seeking to modernize their human resource management operations, thereby demonstrating the importance of information technology in enhancing organizational efficiency.

This project is to evaluate privacy policies in mobile applications. It revealed Assess the clarity, readability, and structure of privacy policies used in selected mobile applications, evaluate the consistency between the stated privacy policies and the actual data handling practices of the mobile applications, identify specific areas within mobile privacy policies where vague or misleading terms are commonly used, examine the extent to which user input data is collected, processed, and shared without clear disclosure in the privacy statements, use Python-based tools to automate the detection and analysis of discrepancies between privacy policies and app behaviors, recommend practical improvements for making mobile application privacy policies more transparent, accurate, and user-friendly. This study designed and evaluation approach to examine how mobile applications present and apply their privacy policies. Selected mobile apps were reviewed based on their popularity and relevance to everyday users. Their privacy policies were extracted and assessed for clarity, length, and language. Python scripts were then used to carry out static and dynamic analysis on these apps. The static part inspected permissions and data access points declared within the app files, while the dynamic part monitored how the app behaves when in use, especially in handling user data. Any mismatch between what is written in the privacy policy and what the app does will be recorded and analyzed. Focus was also be placed on how user input data is managed, as this is often not clearly addressed in policy statements. Results were compared across apps from different categories to detect patterns or risks that repeat across multiple apps

Cloud computing has revolutionized the way businesses manage their IT infrastructure, offering scalable, cost-effective, and flexible solutions. However, as organizations migrate to the cloud, cybersecurity becomes a critical concern. This paper explores how cloud computing enhances cybersecurity for businesses by leveraging advanced security mechanisms such as encryption, multi-factor authentication, artificial intelligence (AI)-driven threat detection, and automated compliance management. Cloud service providers (CSPs) offer robust security frameworks, including real-time monitoring, distributed denial-of service (DDoS) protection, and secure access controls, reducing the risk of cyber threats. Additionally, cloud-based security facilitates disaster recovery, data loss prevention, and regulatory compliance, strengthening overall business resilience. While cloud computing introduces new security challenges, implementing best practices and leveraging CSP security measures can significantly enhance an organization's cybersecurity posture. This study highlights the benefits, challenges, and future trends of cloud computing in
securing business operations against evolving cyber threats. To this purpose, this project designs and implements an encryption and multi-factor authentication system for cloud computing environments using a two-factor authentication approach: first-factor authentication via user ID/email and password, and second-factor authentication via OTP sent to user email.
The system is developed using HTML, CSS, JavaScript, and VueJS for the front-end, Laravel and PHP for the backend, and MySQL for the database.

This study explores the implementation of Large Language Models (LLMs) for analyzing open-ended survey responses in software engineering. Traditional surveys often focus on structured, multiple-choice questions, which provide quantitative insights but overlook the depth of qualitative developer feedback. To address this limitation, the project designed and implemented an LLM-powered system capable of summarizing responses, detecting sentiments, identifying recurring themes, and revealing open research problems from unstructured text. The system architecture was built using a three-tier design comprising a frontend interface, backend server, and LLM integration layer. A pre-trained model such as GPT was connected via API to process textual data. The study followed a design and implementation-oriented methodology, including data collection from developer surveys, system development, testing, and evaluation. Performance was assessed using both quantitative and qualitative metrics such as accuracy, coherence, and user feedback. Evaluation results demonstrated that the system effectively automated key qualitative analysis tasks with high accuracy and interpretability. However, challenges such as occasional hallucinations, dependency on third-party APIs, and limited dataset scope were noted. Overall, the findings confirm that LLMs can significantly enhance qualitative research in software engineering by providing faster, more consistent, and context-aware insights. The study concludes that integrating LLMs with human oversight presents a promising approach for future software engineering research anddecision-making

Waste management in Edo State suffers from poor communication, irregular service delivery, and weak accountability due to manual record-keeping and fragmented reporting systems. This study developed a web-based Customer Relationship Management (CRM) platform to improve communication, transparency, and citizen participation in waste management. Using the Waterfall methodology, data were collected through interviews and literature review, guiding the design and implementation of the system with ASP.NET Core MVC, C#, Razor Pages, Tailwind CSS, and Microsoft SQL Server. The platform includes a customer interface for registration, request tracking, real-time chat, and announcements, and a waste manager interface for zone management, complaint resolution, and information sharing. Security measures such as Argon2 password hashing and role-based access control were implemented. Testing confirmed full functionality and reliability. The system enhances service delivery bycentralizing communication, standardizing complaint tracking, and promoting citizenengagement, offering a scalable model for technology-drivenwaste management across Edo State.

Color detection is a task that humans perform effortlessly; however, enabling computers to accurately identify colors remains a challenging problem. In many industries, traditional color recognition systems rely heavily on manual processes and paid labor for color-coding items or datasets, which are often time-consuming, repetitive, and proneto human error. To address these limitations, this project presents a deep learning–based color detection program capable of recognizing multiple colors in real time. The system is implemented using Python, a high-level general-purpose programming language, in conjunction with the Open Source Computer Vision Library (OpenCV). By leveraging deep learning techniques, the proposed solution enhances accuracy and efficiency in automated color recognition tasks. The developed system enables computer devices to detect and classify multiple colors in real time, making it suitable for applications across various industries, including pharmaceutical manufacturing, autonomous vehicle development, and robotics. The adoption of this system can significantly reduce production time, minimize reliance on manual labor, and lower operational costs while improving overall productivity

This project presents the design and development of BenTalk, a centralized digital community platform specifically tailored for academic interaction and knowledge sharing within Nigerian universities, with a prototype implementation for the University of Benin's Faculty of Computing. The study addresses the critical challenge of fragmented academic communication, where
students currently rely on general-purpose social media platforms like WhatsApp, Facebook, and Telegram—platforms fundamentally designed for social interaction rather than structured academic discourse. Through comprehensive literature review and system analysis, the research identifies key limitations of existing communication channels: information fragmentation across multiple platforms, lack of institutional oversight, absence of knowledge preservation mechanisms, erosion of professional boundaries, and algorithm misalignment with educational objectives. These challenges necessitate a purpose-built solution that balances the accessibility of social media with the structure required for effective academic collaboration. The BenTalk platform employs a three-tier architecture consisting of a Python FastAPI backend with PostgreSQL database, a React-based responsive web application, and a native Android mobile application developed using Kotlin and Jetpack Compose. The system implements a hierarchical subspace structure organized by departments (Computer Science, Cyber Security, Data Science, Software Engineering, Information and Communication Technology, Information Technology, and Information Science) and academic levels (100L, 200L, 300L, 400L), aligning with the university's existing organizational framework. Core functionalities include secure user authentication via JWT tokens, threaded discussion forums with nested commenting capabilities, upvote/downvote mechanisms for content quality signaling, full-text search across posts, and real-time updates through WebSocket integration. The platform emphasizes knowledge preservation through permanent, searchable archives that
benefit future student cohorts while maintaining intuitive navigation and mobile-first design principles suited to Nigerian infrastructure constraints. The prototype demonstrates technical feasibility and addresses identified gaps in current
academic communication systems. Testing confirms that the platform successfully provides structured academic discourse spaces, reduces information redundancy, facilitates peer-to-peer learning, and enables optional institutional oversight without compromising student ownership of discussions. The system's modular architecture allows for scalability and adaptation to other faculties and institutions. This research contributes to the growing body of literature on educational technology in African
contexts by demonstrating that locally-developed, context-appropriate solutions can effectively address challenges that generic global platforms cannot. The project provides a blueprint for similar implementations across Nigerian universities and offers practical recommendations for institutional adoption, technical enhancement, and sustainable deployment.

The rapid evolution of digital technologies has transformed e-commerce design standards, leaving many early websites outdated and ineffective. This study focuses on the user- centered redesign of a legacy e-commerce interface, using Arngren.net as a case study. The objective was to evaluate the usability and visual experience of the site and to propose a redesign framework that aligns with modern user experience (UX) and interface design (UI) principles. The research adopted a qualitative case study approach, emphasizing heuristic evaluation and comparative analysis. Using Nielsen’s (2020) ten usability heuristics, Arngren.net was assessed for issues relating to layout consistency, navigation flow, accessibility, and visual hierarchy. Findings revealed significant usability flaws, including poor visual organization, low mobile responsiveness, and non-intuitive navigation. These weaknesses were compared with modern e-commerce platforms such as Amazon, eBay, and Shopify-based stores, which prioritize responsive layouts, accessibility compliance, and streamlined user journeys. Based on these insights, a user-centered redesign framework was proposed, integrating simplicity, responsive design, and user trust as key pillars. The redesigned interface emphasizes clear visual hierarchy, improved navigation menus, accessible content structure, and consistency across devices.

The performance quality of web content is a critical determinant of success for e-commerce platforms, directly influencing user engagement and conversion rates. This is especially critical in Nigeria's mobile-first, bandwidth-constrained digital market, where many local websites struggle to meet global performance standards, leading to prolonged load times and a suboptimal user experience that risks customer loss. This study therefore aimed to investigate the performance of selected Nigerian e-commerce websites and diagnose major performance bottlenecks. To achieve this, the project employed a tool-based approach, conducting a performance investigation using Google PageSpeed Insights and GTmetrix to analyze key pages across three major platforms: Jumia, Konga, and Slot. The findings revealed significant performance disparities; Jumia demonstrated relatively optimized performance, Konga exhibited critical inefficiencies with excessively slow load times, and Slot showed inconsistent results, particularly on mobile. In conclusion, the study establishes that technical performance is an inseparable component of web content quality. It provides actionable recommendations, such as image compression and script optimization, underscoring the strategic need for Nigerian e-commerce platforms to prioritize technical excellence to meet up with global standards, enhance user trust, and ensure sustained growth and competitiveness in the evolving digital marketplace.