Research Articles in Computer Science

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    A Dynamic and Incremental Graphical Grid Authentication Technique for Mobile and Web Applications
    (2024-08-08) Gong Jiaming; Akande Oluwatobi Noah; Chia-Chen Lin; Agarwal Saurabh
    Knowledge-based authentication techniques remain one of the proven ways of maintaining confidentiality, ensuring integrity, and guaranteeing the availability of an information system. They employ what a user knows (Passwords or PINs) to authorize or grant access to an information system. While passwords employ a fixed combination of characters, Personal Identification Numbers (PINs) are majorly numbers. Existing implementations of these authentication techniques involve the repetitive use of static passwords and PINs at every login instance. These have been exposed to various attacks, such as keyloggers, shoulder surfing, brute force, and dictionary attacks. To overcome these attacks, this study presents an authentication technique where users’ PINs are incremented during successive login attempts. Users are expected to choose a preferred incremental factor, which can be any number they can remember, that will be added to the default 6-digit PIN to produce a dynamic PIN that can be used in subsequent login sessions. Furthermore, an additional layer of security that involves the use of a dynamic 4 by 4 graphical grid was integrated into the proposed incremented PIN technique. At every login session, users are presented with a set of 16 possible PINs to choose from. The security analysis of the proposed authentication technique revealed that the proposed technique could resist existing password attacks, thereby enhancing security. A performance testing and usability analysis was also carried out among 1145 individuals who interacted with the web application that uses the incremental authentication technique. The questionnaire items were structured based on the constructs of the Unified Theory of Acceptance and Use of Technology (UTAUT) Model. Statistical analysis of the responses received showed an appreciable level of acceptance in terms of performance expectancy, effort expectancy, social influence, and facilitating conditions. The positive user acceptance results provide reassurance about the practicality and effectiveness of the proposed technique. It is believed that the proposed incremental graphical grid authentication technique will further enhance the security of our growing mobile and web applications
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    A Dynamic Round Triple Data Encryption Standard Cryptographic Technique for Data Security
    (Springer Nature Switzerland AG, 2020-08-08) Akande Oluwatobi Noah; Abikoye Oluwakemi Christiana; Kayode Aderonke Anthonia; Aro Oladele Taye; Ogundokun Oluwaseun Roseline
    Cryptographic techniques have been widely employed to protect sensitive data from unauthorized access and manipulation. Among these cryptographic techniques, Data Encryption Standard (DES) has been widely employed, however, it suffers from key and differential attacks. To overcome these attacks, several DES modifications have been proposed in literatures. Most modifications have focused on enhancing DES encryption key; however, the strength of a cryptographic technique is determined by the encryption key used and the number of encryption rounds. It is a known fact that Advanced Encryption Standard (AES) cryptographic technique with 14 encryption rounds is stronger than AES with 12 rounds while AES with 12 rounds is stronger than AES with 10 rounds. Therefore, this study proposed a DES cryptographic technique whose number of rounds is dynamic. Users are expected to specify the number of encryption and decryption rounds to be employed at run time. Moreover, a predefined number of shifting operations which is left circular shift 2 was chosen for each encryption round. As, a trade-off in complexity, the number of Substitution box (S-box) was also reduced to 4, so that the input to the S-boxes would be arranged in four 12-bit blocks for the X-OR operation and not six 8-bit blocks as in the traditional DES. Finally, three keys were used to encrypt, decrypt and encrypt the plaintext ciphertext as in triple DES. The modified DES yielded a better avalanche effect for rounds greater than 16 though its encryption and decryption time were greater than that of the traditional DES.
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    A novel technique to prevent SQL injection and cross-site scripting attacks using Knuth-Morris-Pratt string match algorithm
    (Springer Open, 2020-08-08) Abikoye Oluwakemi Christiana; Abubakar Abdullahi; Dokoro Ahmed Haruna; Akande Oluwatobi Noah; Kayode Aderonke Anthonia
    Structured Query Language (SQL) injection and cross-site scripting remain a major threat to data-driven web applications. Instances where hackers obtain unrestricted access to back-end database of web applications so as to steal, edit, and destroy confidential data are increasing. Therefore, measures must be put in place to curtail the growing threats of SQL injection and XSS attacks. This study presents a technique for detecting and preventing these threats using Knuth-Morris-Pratt (KMP) string matching algorithm. The algorithm was used to match user’s input string with the stored pattern of the injection string in order to detect any malicious code. The implementation was carried out using PHP scripting language and Apache XAMPP Server. The security level of the technique was measured using different test cases of SQL injection, cross-site scripting (XSS), and encoded injection attacks. Results obtained revealed that the proposed technique was able to successfully detect and prevent the attacks, log the attack entry in the database, block the system using its mac address, and also generate a warning message. Therefore, the proposed technique proved to be more effective in detecting and preventing SQL injection and XSS attacks
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    Comprehensive Evaluation Of Appearance-Based Techniques For Palmprint Features Extraction Using Probabilistic Neural Network, Cosine Measures And Euclidean Distance Classifiers
    (UNIVERSITY OF PITESTI SCIENTIFIC BULLETIN, 2018-08-08) Akande Oluwatobi Noah; Abikoye O. C; Adeyemo I. A; Ogundokun R. O; Aro T. O
    Most biometric systems work by comparing features extracted from a query biometric trait with those extracted from a stored biometric trait. Therefore, to a great extent, the accuracy of any biometric system is dependent on the effectiveness of its features extraction stage. With an intention to establish a suitable appearance based features extraction technique, an independent comparative study of Independent Component Analysis (ICA), Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) algorithms for palmprint features extraction is reported in this article. Euclidean distance, Probabilistic Neural Network (PNN) and cosine measures were used as classifiers. Results obtained revealed that cosine metrics is preferable for ICA features extraction while PNN is preferable for LDA features extraction. Both PNN and Euclidean distance yielded a better recognition rate for PCA. However, ICA yielded the best recognition rate in terms of FAR and FRR followed by LDA then PCA
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    Design and Implementation of a Mobile Students’ Course Registration Platform
    (International Journal of Advanced Technology and Engineering Exploration, 2015-08-08) Adigun Abimbola Adebisi; Akande Oluwatobi Noah; Ajagbe Oluwafemi Adeola
    This paper describes a Mobile Application Based Course Registration Platform (MABCRP) designed and implemented to facilitate the process of students' course registration within a University system. This was designed to serve as an alternative to web based and online course registration system being currently used by most universities. This intends to bring course registration closer to the students who are vastly great users of mobile devices. The developed mobile application will enable students to automatically register expected courses per semester, view all registered courses and also to add or delete registered courses. Result of user evaluation of the developed MABCRP shows that it has a good usability in terms of usefulness and ease of use. The results also indicate that the developed MABCRP is capable to help students register their academic courses more easily without location being a barrier.
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    Electronic Medical Information Encryption Using Modified Blowfish Algorithm
    (Springer Nature Switzerland, 2019-08-08) Akande Oluwatobi Noah; Abikoye Christiana Oluwakemi; Adebiyi Marion Olubunm; Kayode Anthonia Aderonke; Adegun Adekanmi Adeyinka; Ogundokun Roseline Oluwaseun
    Security and privacy of patients’ information remains a major issue of concern among health practitioners. Therefore, measures must be put in place to ensure that unauthorized individual do not have access to this information. However, the adoption of digital alternative of retrieving and documenting medical information has further opened it up to more attacks. This article presents a modified blowfish algorithm for securing textual and graphical medical information. The F-function used in generating round sub-keys was strengthened so as to produce a strong key that could resist differential attacks. Number of Pixel Change Rate (NPCR) and Unified Average Changing Intensity (UACI) of 98.85% and 33.65% revealed that the modified algorithm is sensitive to changes in its key and also resistive to differential attacks. Furthermore, the modified algorithm demonstrated a better encryption and decryption time than the existing blowfish algorithm.
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    Ethnicity and Biometric Uniqueness
    (2023-08-08) John Daugman; Cathryn Downing; Akande Oluwatobi Noah; Abikoye Oluwakemi Christiana
    We conducted more than 1.3 million comparisons of iris patterns encoded from images collected at two Nigerian universities, which constitute the newly available African Human Iris (AFHIRIS) database. The purpose was to discover whether ethnic differences in iris structure and appearance such as the textural feature size, as contrasted with an all-Chinese image database or an American database in which only 1.53% were of African-American heritage, made a material difference for iris discrimination. We measured a reduction in entropy for the AFHIRIS database due to the coarser iris features created by the thick anterior layer of melanocytes, and we found stochastic parameters that accurately model the relevant empirical distributions. Quantile-Quantile analysis revealed that a very small change in operational decision thresholds for the African database would compensate for the reduced entropy and generate the same performance in terms of resistance to False Matches. We conclude that despite demographic difference, individuality can be robustly discerned by comparison of iris patterns in this West African population
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    Remote Sensing Image Classification for Land Cover Mapping in Developing Countries
    (IJCSNS International Journal of Computer Science and Network Security, 2022-02-05) Nwojo Agwu Nnanna; Moussa Mahamat Boukar
    Convolutional Neural networks (CNNs) are a category of deep learning networks that have proven very effective in computer vision tasks such as image classification. Notwithstanding, not much has been seen in its use for remote sensing image classification in developing countries. This is majorly due to the scarcity of training data. Recently, transfer learning technique has successfully been used to develop state-of-the art models for remote sensing (RS) image classification tasks using training and testing data from well-known RS data repositories. However, the ability of such model to classify RS test data from a different dataset has not been sufficiently investigated. In this paper, we propose a deep CNN model that can classify RS test data from a dataset different from the training dataset. To achieve our objective, we first, re-trained a ResNet-50 model using EuroSAT, a large-scale RS dataset to develop a base model then we integrated Augmentation and Ensemble learning to improve its generalization ability. We further experimented on the ability of this model to classify a novel dataset (Nig_Images). The final classification results shows that our model achieves a 96% and 80% accuracy on EuroSAT and Nig_Images test data respectively. Adequate knowledge and usage of this framework is expected to encourage research and the usage of deep CNNs for land cover mapping in cases of lack of training data as obtainable in developing countries.
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    Developing a Digital Interactive Course Material on Automated Management System (AMS) Moodle for Partial Differential Equations (PDEs) Course
    (IEEE, 2019-02-02) Moussa Mahamat Boukar
    Many physical, engineering problems from some areas like fluid mechanics, heat transfer, rigid body dynamics and elasticity are modelled by Partial Differential Equations (PDEs). That’s why, PDEs course is the main course in the higher educations. The aim of this work is to develop an interactive digital course material for some kind of PDEs. A digital question bank is developed using Wildcard technology on the automated management system Moodle.
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    An Error Analysis Algorithm for Approximate Solution of Linear Fredholm-Stieltjes Integral Equations with Generalized Trapezium Method
    (IEEE, 2017-02-02) Moussa Mahamat Boukar
    Integral equations and their solutions are very important for various areas like physics, engineering, biology and other. Fredholm-Stieltjes integral equations are some of the integral equations. Sometimes it is possible to find exact solutions for some of the integral equations.The main purpose of this paper is to propose an error analysis algorithm for approximate solution of linear Fredholm-Stieltjes integral equations of second kind with Generalized Trapezium Method. Firstly, the theory of error analysis is given. Then the implementation of algorithm is done with Maple software and examples are given with graphics.