Shafii Muhammad Abdulhamid

Work place: Department of Cyber Security, Federal University of Technology, Minna, Nigeria



Research Interests: Computer Science & Information Technology, Information Security, Network Security, Information-Theoretic Security


Shafi’i Muhammad Abdulhamid received his PhD in Computer Science from Universiti Teknologi Malaysia (UTM), MSc in Computer Science from Bayero University Kano (BUK), Nigeria and a Bachelor of Technology in Mathematics/Computer Science from the Federal University of Technology Minna, Nigeria. His current research interests are in Cyber Security, Cloud computing, Soft Computing and BigData. He has published many academic papers in reputable International journals, conference proceedings and book chapters. He has been appointed as an Editorial board member for UPI JCSIT and IJTRD. He has also been appointed as a reviewer of several ISI and Scopus indexed International journals such as JNCA Elsevier, ASOC Elsevier, EIJ Elsevier, JKSU-CIS Elsevier, NCAA Springer, BJST Springer, IJNS, IJST, IJCT, JITE:Research, JITE:IIP, JAIT, IJAER and JCEIT SciTechnol. He is a member of IEEE, International Association of Computer Science and Information Technology (IACSIT), Computer Professionals Registration Council of Nigeria (CPN), International Association of Engineers (IAENG), The Internet Society (ISOC), Cyber Security Experts Association of Nigeria (CSEAN) and Nigerian Computer Society (NCS). Presently he is a lecturer at the Department of Cyber Security Science, Federal University of Technology Minna, Nigeria.

Author Articles
Enhancing Fast Fourier Transform Algorithm for Keystroke Acoustic Emanation Denoising Strategy on Real-Time Scenario

By Suleiman Ahmad John Kolo Alhassan Shafii Muhammad Abdulhamid Suleiman Zubairu

DOI:, Pub. Date: 8 Feb. 2024

The use of virtual keyboards in mobile devices such as smartphones and tablets has become an essential tool for inputting information. The sound of keystrokes has been observed in previous studies to be recorded along with ambient noises, such as those produced by uncontrolled student noise, fans, doors and windows, moving cars, and similar sources. The presence of such noises negatively affects the quality of the keystrokes signal, which in turn affects keystroke analysis. The traditional FFT-based denoising methods are vital but they are often limited by their inability to adapt to the varying characteristics of real-world audio and noises. This paper proposes an enhanced Fast Fourier Transform (FFT) with an adaptive threshold technique that reduces ambient noises. The adaptive threshold technique is developed to identify frequency bins that contain noise and set their sizes to zero or attenuate them to reduce the noise. The paper evaluates the performance of the enhanced FFT with adaptive threshold on keystrokes recorded audio and validates it through extensive experimentation. The results show that the enhanced FFT outperforms the traditional FFT in terms of speed and the amount of noise removed from the recorded audio signal, indicating a significant improvement.

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Comparative Analysis of Classification Algorithms for Email Spam Detection

By Shafii Muhammad Abdulhamid Maryam Shuaib Oluwafemi Osho Idris Ismaila John K. Alhassan

DOI:, Pub. Date: 8 Jan. 2018

The increase in the use of email in every day transactions for a lot of businesses or general communication due to its cost effectiveness and efficiency has made emails vulnerable to attacks including spamming. Spam emails also called junk emails are unsolicited messages that are almost identical and sent to multiple recipients randomly. In this study, a performance analysis is done on some classification algorithms including: Bayesian Logistic Regression, Hidden Na?ve Bayes, Radial Basis Function (RBF) Network, Voted Perceptron, Lazy Bayesian Rule, Logit Boost, Rotation Forest, NNge, Logistic Model Tree, REP Tree, Na?ve Bayes, Multilayer Perceptron, Random Tree and J48. The performance of the algorithms were measured in terms of Accuracy, Precision, Recall, F-Measure, Root Mean Squared Error, Receiver Operator Characteristics Area and Root Relative Squared Error using WEKA data mining tool. To have a balanced view on the classification algorithms’ performance, no feature selection or performance boosting method was employed. The research showed that a number of classification algorithms exist that if properly explored through feature selection means will yield more accurate results for email classification. Rotation Forest is found to be the classifier that gives the best accuracy of 94.2%. Though none of the algorithms did not achieve 100% accuracy in sorting spam emails, Rotation Forest has shown a near degree to achieving most accurate result.

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Controlling Citizen’s Cyber Viewing Using Enhanced Internet Content Filters

By Shafii Muhammad Abdulhamid Fasilat Folagbayo IBRAHIM

DOI:, Pub. Date: 8 Nov. 2013

Information passing through internet is generally unrestricted and uncontrollable and a good web content filter acts very much like a sieve. This paper looks at how citizens’ internet viewing can be controlled using content filters to prevent access to illegal sites and malicious contents in Nigeria. Primary data were obtained by administering 100 questionnaires. The data was analyzed by a software package called Statistical Package for Social Sciences (SPSS). The result of the study shows that 66.4% of the respondents agreed that the internet is been abused and the abuse can be controlled by the use of content filters. The PHP, MySQL and Apache were used to design a content filter program. It was recommended that a lot still need to be done by public organizations, academic institutions, government and its agencies especially the Economic and Financial Crime Commission (EFCC) in Nigeria to control the internet abuse by the under aged and criminals.

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The Design and Development of Real-Time E Voting System in Nigeria with Emphasis on Security and Result Veracity

By Shafii Muhammad Abdulhamid Olawale Surajudeen Adebayo Damian Oshomah Ugiomoh Mohammed Danlami AbdulMalik

DOI:, Pub. Date: 8 Apr. 2013

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 system of voting. The implementation of electronic voting system in Nigeria will boost the integrity of INEC and the result they produce. The programs used to develop this system are PHP, MySQL, Java Query, CSS and HTML. These packages make the Graphic Interface User friendly enough for even those with little or no computer knowledge.

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