http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/83 SICT 2026-09-29T03:58:37Z http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31990 Title: ARTIFICIAL INTELLIGENCE – POWERED CYBER WARFARE: RESOURCES, METHODS, WEAPONISATION, FORENSICS, THREAT INTELLIGENCE AND DEFENSES: A SYSTEMATIC REVIEW Authors: Joseph, Christiana; Ojeniyi, Joseph; Noel, Moses; Ahmad, Suleiman; Olusanjo, Fasola; Anyaora, Peter Abstract: Artificial Intelligence (AI) is gradually changing how cyber warfare works, creating new opportunities but also posing threats. This systematic literature review analyses how AI is used in different areas, focusing on resources, methods, weaponisation, forensics, threat intelligence, defenses and research directions. This study uses PRISMA-ScR methodology to analyse relevant publications published between 2018 and 2025. The findings indicate that AI technologies are increasingly being utilised for reconnaissance, automated cyberattacks, and enhanced threat detection. It also increases defensive measures by implementing intelligent systems that ensure faster response and mitigation. However, the increased reliance on AI raises serious concerns about ethical concerns, algorithmic bias, data privacy issues, and the high risk of autonomous weaponisation. The study highlights the need to improve AI-based defense systems and forensic methods to keep up with changing cyber threats. The paper ends by recommending more research in AI, stronger cybersecurity systems, and greater international cooperation to ensure AI is used responsibly in cyber warfare. 2025-09-16T00:00:00Z http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31989 Title: Enhanced Convolutional Neural Network Model Using Bidirectional Encoder Representations from Transformers and Long Short-Term Memory for Hate Speech Detection Authors: Okechukwu, Chukwuemeka; Nwodo, Chinweoke; Anyaora, Peter; Gungbias, Hosea; Subairu, Sikiru; Ojeniyi, Joseph Abstract: Hate speech has become a prevalent and concerning issue in this digital age as a result of the adoption of social media as a means of communication, social interaction, and driving social discussion. This trend has opened a novel front in cybercrime, cyberbullying, privacy violations, and exposure of the people component of information security to violence, subsequently violating the governance and internal security of nations. The detection and mitigation of hate speech on online platforms have gained significant attention due to the growing influence of social media and the internet as communication channels and the adoption of the same as a means of propagating hate and hate crimes. This thesis offers a model for the more accurate detection of hate speech on an online platform using Bidirectional Encoder Representations from Transformers (BERT) to enhance the feature selection layer of Convolutional Neural Networks (CNN) and a hybrid of CNN and Long-Short-Term Memory (LSTM) to detect hate speech. The proposed BERT-CNN-LSTM model achieved an accuracy of 96.1%, which is an increase of over 0.45% from 95.63% in the benchmark paper, thereby contributing a novel and more accurate tool that, when adapted into the security policies of organisations and governments, will help safeguard the rights and privacy of users, thereby protecting them from both physical and psychological harm resulting from hate propagation over the internet. 2024-04-22T00:00:00Z http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31988 Title: Systematic Literature Review on Android Malware Detection Authors: Anyaora, Peter; Adebayo, Olawale; Ismalia, Idris; Ojeniyi, Joseph; Olalere, Morufu Abstract: Users of Android-powered smartphones and tablets have multiplied dramatically. Thanks to Android third-party apps, the essential applications, such as banking and healthcare, are accessible on Android smartphones. There are new threats to be taken into account about harmful programs when these applications are utilized and embraced more broadly. This research performs a systematic literature review using the prima framework and Kitchenham statement to apply on android malware detection and analysis of different methodology of publishing research that have been used for android malware detection for the last past five years. Using the keyword” Android malware detection” the research had seen over 610 published articles on” Android Malware detection”. It was narrowed down to 142 published research papers due to it between the year 2018 to 2022 that was looked at, sixty-five articles (65) were finally selected for investigation after inclusion and exclusion. One of the research key findings is the performance of Machine Learning (ML) algorithms which were relatively higher than others. 2023-03-21T00:00:00Z http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31972 Title: Adoption of Artificial Intelligence in University Libraries in Nigeria. “Strategies and Challenges”: A Review. Authors: Joshua, A. Ikani; Babalola, G. A.; Salami, R. O. Abstract: Artificial Intelligence (AI) has become a potential transformative technology that can revolutionize library services and engage users, facilitate access, and optimize library functions. The main aim of this review is to assess how artificial intelligence technologies are being adopted in Nigerian university libraries, exploring both the enabling strategies and challenges faced during this process. Objectives are to: identify artificial intelligence tools currently in use in university libraries in Nigeria and their service applications, examine strategic approaches to implementing artificial intelligence, highlight challenges hindering effective adoption and integration of artificial intelligence and propose recommendations that may help to enhance adoption artificial intelligence and its sustainability in university libraries in Nigeria. The study reviewed current literature globally on infrastructural, organizational, and human capacity that enable artificial intelligence adoption and underscores gaps, barriers, and prospects in the adoption curve. Findings shows that ChatGPT is a major AI tool utilized by librarians in Nigeria on a person bases but it has not been embedded in library services due to technology insufficiency, policy vacuum, lack of staff capabilities, as well as financial limitations. The paper ends with strategic suggestions on how to better prepare libraries for artificial intelligence integration to support sustainable transformation of library service. Description: PAGE 320-325 2025-10-06T00:00:00Z