Olawale S. Adebayo

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The recent employment and eventual widespread acceptance of electronic test in examining students and various classes in Nigeria has created a significant impact in the trends of educational history in the country. In this paper, we examined the impacts, associated challenges and security lapses of the existing electronic-examination system with the aim of(More)
The trend and motive of Cyber-attacks have gone beyond traditional damages and challenges to information stealing for political and economic gain. With the recent APT (Advance Persistent Threat), which comprises of Zeroday malware, Polymorphic malware, and Blended threat, the task of protecting vita infrastructures are increasingly becoming difficult. This(More)
The Android operating system is gaining market share on smartphones and tablets due to its market openness and easier accessibility and operability. Therefore, it is increasingly targeted by malware. This research examines several attack vectors on an android smartphone. Techniques are presented for the analysis of such attack vectors in order to identify(More)
— Elections are believed to be the key pillars of democracy and voting is one of the electoral processes that ensure the sustenance of democracy in any civil society. In this paper, we developed an electronic voting system, which will eliminate rigging and manipulation of results to its barest minimum, this problem is mostly associated with the manual(More)
This paper compares the e-Examination system in Nigeria with that of Australia. We consider the experiences of working with commercial firms such as Electronic Testing Company (eTC) and using open-source software. It is important to foster good relationships with accreditation authorities (such as the systems in the two countries and suggests ways of(More)
The rate at which cybercrime is being perpetrated in our society is quietly alarming, the insecurity of internet has exposed the global community and resources to this menace, many nations, organizations and individuals are becoming victims of this on daily basis. Many Individuals have lost their personal information into the hands of hackers, it is now(More)
Several machine learning techniques based on supervised learning have been adopted in the classification of malware. However, only supervised learning techniques have proofed insufficient for malware classification task. This paper presents a classification of android malware using candidate detectors generated from an unsupervised association rule of(More)
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