http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/104 2026-09-13T12:32:10Z 2026-09-13T12:32:10Z Ojeniyi, J. A. Waziri, V. O. Adebayo, O. S. Uduimoh, A. A. Oladipupo, S. F. Hussaini, Y. Umar, M. Abdullazeez, A. http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31938 2026-07-14T16:29:14Z 2022-01-01T00:00:00Z

Title: Android malware detection: A systematic Literature review Authors: Ojeniyi, J. A.; Waziri, V. O.; Adebayo, O. S.; Uduimoh, A. A.; Oladipupo, S. F.; Hussaini, Y.; Umar, M.; Abdullazeez, A. Abstract: Android malware is growing at alarming rate and spreading rapidly despite on-going mitigating efforts. This brings a necessity to find more effective solutions to detect those malwares and prevent users from any malicious threats. This study uses the PRISMA statement as a reference so to be transparent. This paper uses a SLR to identify where recent studies in Android malware detection have been focused on and offers a broad perspective relating to types of analysis and the dataset sources used in the research area within the range of 2015 to 2020. A total of 58 selected papers met the inclusion criteria based on title of articles, exclusion criteria, reading abstract and content of the selected 58 papers. Different data are extracted from these articles and recorded in an excel sheet for further analysis. Most of the paper discussed about the use of systematic analysis approach to analyze malware using Debrin dataset, Google Play dataset and Virus Share dataset samples. The systematic review carried out would provide information to all researchers and further inform the requirements for future development of enhanced malware analysis and detection methods.

2022-01-01T00:00:00Z Osho, Oluwafemi Yisa, Victor Falade, Polra Victor Osho, Lauretta Oluwafemi Uduimoh, Andrew http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31936 2026-07-14T15:57:28Z 2025-11-08T00:00:00Z

Title: Digital Closeness, Real Dangers: Predictors of Online Sexual Behaviors, Solicitations, and Harassment Among Adolescents in Nigeria Authors: Osho, Oluwafemi; Yisa, Victor; Falade, Polra Victor; Osho, Lauretta Oluwafemi; Uduimoh, Andrew Abstract: The rapid advancement of digital technologies has profoundly transformed societal interactions, particularly among adolescents, whose daily lives and social engagements are increasingly mediated by digital platforms. However, this digital intimacy exposes adolescents to numerous risks. While much of the existing research on adolescents’ online behaviors and associated threats has focused on Western contexts, limited attention has been given to non-Western settings. This study addresses this gap by examining the online interactions and experiences of adolescents in Nigeria, with particular attention to their sexual behaviors and encounters with sexual solicitation and harassment. Survey data were collected from adolescents in eight secondary schools across two local government areas in a North Central state of Nigeria. Findings reveal that a substantial proportion of adolescents engage in sexual conversations with Internet-only contacts and share nude images. Factors such as gender, phone calls, face-to-face meetings, experiences of blackmail, and the frequency of parent-child discussions significantly predicted the likelihood of engaging in sexual conversations or sending nude pictures. Additionally, age, experiences of cyberbullying and harassment, and blackmail emerged as significant predictors of sexual solicitation and harassment. These findings underscore the urgent need for interventions that integrate sexual-risk digital citizenship education, promote parent-adolescent communication, and leverage technological tools to detect grooming behaviors and facilitate the reporting of online exploitation. Description: Digital Closeness, Real Dangers: Predictors of Online Sexual Behaviors, Solicitations, and Harassment Among Adolescents in Nigeria

2025-11-08T00:00:00Z OJENIYI, Joseph Adebayo WAZIRI, Victor Onomza ADEBAYO, Olawale Surajudeen FASHINA, OLADIPUPO S. YUSUF, A. HUSSAINI MDUGU, UMAR ABDULLAHI, ABDULLAZEEZ http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31816 2026-07-10T03:14:28Z 2022-12-01T00:00:00Z

Title: Android Malware Detection: A Systematic Literature Review Authors: OJENIYI, Joseph Adebayo; WAZIRI, Victor Onomza; ADEBAYO, Olawale Surajudeen; FASHINA, OLADIPUPO S.; YUSUF, A. HUSSAINI; MDUGU, UMAR; ABDULLAHI, ABDULLAZEEZ Abstract: Android malware is growing at alarming rate and spreading rapidly despite on-going mitigating efforts. This brings a necessity to find more effective solutions to detect those malwares and prevent users from any malicious threats. This study uses the PRISMA statement as a reference so to be transparent. This paper uses a SLR to identify where recent studies in Android malware detection have been focused on and offers a broad perspective relating to types of analysis and the dataset sources used in the research area within the range of 2015 to 2020. A total of 58 selected papers met the inclusion criteria based on title of articles, exclusion criteria, reading abstract and content of the selected 58 papers. Different data are extracted from these articles and recorded in an excel sheet for further analysis. Most of the paper discussed about the use of systematic analysis approach to analyze malware using Debrin dataset, Google Play dataset and Virus Share dataset samples. The systematic review carried out would provide information to all researchers and further inform the requirements for future development of enhanced malware analysis and detection methods.

2022-12-01T00:00:00Z Osin, O.J Isah, Abdulkadir O. Subairu, Sikiru O. Ahmad, Suleiman Noel, Moses Dogonyaro http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/30914 2026-05-06T19:05:53Z 2025-09-18T00:00:00Z

Title: Artifi cial Intelligence Enabled Ransomware: A Systematic Review Authors: Osin, O.J; Isah, Abdulkadir O.; Subairu, Sikiru O.; Ahmad, Suleiman; Noel, Moses Dogonyaro Abstract: Ransomware has been one of the most severe cyber threats, hobbled operations as well as bottom lines worldwide. Normally, ransomware attacks have been based on the idea of encrypting or blocking the data itself and paying a ransom for it to be released, yet the introduction of AI now also leaves many traditional detection methods out of date. This survey aims to answer three main research questions about how AI-empowered ransomware are growing as a threat: What are these emerging threats, state of-the-art detection methodologies to detect them and what are the related forthcoming research directions? Applying the PRISMA 2020 methodology, the retrieved papers between 2020 and 2025 were systematically reviewed, where only the ones of high quality and focus were included. What’s clear is that AI has turned ransomware from something that was statically built to something that’s now intelligent, work rounding, complex. However, there is hope on the horizon for detecting and defending against such attacks due to the advances in AI-based detection and response systems. In the following, we reflect on remaining challenges identified in the study and the importance of further work to bridge the gap and make AI-based defenses more impactful. Description: N/A

2025-09-18T00:00:00Z