Faculty of Computing

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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
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.
A Few-shot custom CNN Model for Retinal Nerve Fibre Layer Thickness Measurement in OCT Images of Epilepsy
(Proc. of International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (, 2024-02-01) Ruqayya Muhammad; Moussa Mahamat Boukar; Steve Adeshina; Senol Dane
This study aims to assess the effectiveness of employing deep learning models for measuring retinal nerve fiber layer (RNFL) thickness in optical coherence tomography (OCT) scans of epilepsy patients. Conventional OCT scan segmentation methods typically rely on supervised learning, demanding substantial data for training and assuming fixed network weights post-training. To mitigate these challenges, we explore the applicability of few-shot learning (FSL) in CNN architectures, allowing dynamic fine-tuning of network weights with minimal additional data. Experimental results demonstrate enhanced segmentation accuracy, with the proposed Few shot Custom CNN achieving a notable 91% accuracy, surpassing both the Custom CNN (86%) and the OCT machine data. This suggests the superiority of the few-shot Custom CNN model in segmentation performance compared to OCT scans.
A framework for Poultry weather control with IoT in sub-Saharan Africa
(15th International Conference on Electronics Computer and Computation (ICECCO 2019), 2019-02-02) Nasiru Afeez; Steve Adeshina; Abdullahi Inci; Moussa Mahamat Boukar
Poultry farming in the sub-Saharan region of Africa is fraught with a lot of challenges among which are high temperature and humidity. In this paper, the authors proposed an Internet of Things (IoT) framework that will help in regulating the various climatic conditions that will help at providing a high yield of poultry products. This framework is aimed at providing proactive and preventive ways to avert or reduce the high mortality rate in a flock of birds as a result of heat stress. IoT which is a connected environment of monitoring sensors with high precision and an accurate decision taken would be presented in managing environmental conditions of poultry house that will gather information, analyze it and effect an action based on the predetermined weather conditions that are suitable for bird’s existence
A Holistic–Based Digital Forensic Readiness Framework For Zenith Bank, Nigeria
(International Conference on Computational and Social Sciences, 2015-08-25) Abdullahi, Adamu Garba; Maheyzah Md Siraj
The advancement of internet has made many business organizations conduct their operation automatically, in effect its open a possibly dangerous unforeseen information security incidents of both illegal and civil nature. Therefore, if any organization does’t arrange themselves for such instances, it’s likely that vital significant digital evidence will be damage. In other word an organization should has a digital forensic readiness framework (DFR). DFR is the capacity of anyassociation to exploit its prospective to use digital evidence whilst minimizing the cost of investigation. Subsequently, in order to prepare organizations for incident responds, the application of digital forensic readiness policies and procedures is important. Contemporary lack of forensic skills is one of the factors that make organizations reluctant to implement digital forensics. This project propose a holistic-based framework of DFR and investigate how it can be applied to Zenith Bank Plc. This paper surveys existing frameworks to identify the best-suited practical components for Zenith Bank’s operational unit
A Hybrid Approach for Reverse Engineering GUI Model from Android Apps for Automated Testing
(Journal of Telecommunication, Electronic and Computer Engineering, 2017-02-02) Ibrahim Anka Salihu
Nowadays, smartphone users are increasingly relying on mobile applications to complete most of their daily tasks. As such, mobile applications are becoming more and more complex. Therefore, software testers can no longer rely on manual testing methods to test mobile applications. Automated model-based testing techniques are recently used to test mobile applications. However, the models generated by existing techniques are of insufficient quality. This paper proposed a hybrid technique for reverse engineering graphical user interface (GUI) model from mobile applications. It performs static analysis of application’s bytecode to extract GUI information followed by a dynamic crawling to systematically explore and reverse engineer a model of the application under test. A case study was performed on real-world mobile apps to evaluate the effectiveness of the technique. The results showed that the proposed technique can generate a model with high coverage of mobile apps behaviour.
A LIGHTWEIGHT AUTHENTICATION TECHNIQUE FOR SECURE COMMUNICATION OF EDGE/FOG DATA-CENTERS
(Readers Insight Publisher, 2020-05-13) Yahuza, Muktar; Idris, Mohd Yamani Idna; Wahab, Ainuddin Wahid Abdul; Abdullahi, Adamu Garba; Musa, Mahadi A.
Edge computing has significantly enhanced the capabilities of cloud computing. Edge data-centres are used for storing data of the end-user devices. Secure communication between the legitimate edge data-centres during the load balancing process has attracted industrial and academic researchers. Recently, Puthal et al. have proposed a technique for authenticating edge datacenters to enable secure load balancing. However, the resource-constraint nature of the edge data-centres is ignored. The scheme is characterized by complex computation and memory intensive cryptographic protocol. It is also vulnerable to key escrow attack because the secret key used for encrypting and decrypting of the communicated messages is been created by the trusted cloud datacenter. Additionally, the key sharing phase of their algorithm is complex. Therefore, to address the highlighted challenges, this paper proposed a lightweight key escrow-less authentication algorithm that will ensure secure communication of resource-constrained edge data-centres during the load balancing process. The security capability of the proposed scheme has been formally evaluated using the automatic cryptographic analytical tool ProVerif. The relatively low computation and communication costs of the proposed scheme compared to the benchmark schemes proved that it is lightweight, thus suitable for resource-constrained edge datacenters.
A Machine Learning Led Investigation Predicting the Thermos‑mechanical Properties of Novel Waste‑based Composite in Construction
(Waste and Biomass Valorization, 2024-05-04) Assia Aboubakar Mahamat; Moussa Mahamat Boukar; Ifeyinwa Ijeoma Obianyo; Nurudeen M. Ibrahim
The study explores the potential of machine learning (ML) in predicting the thermal and mechanical properties of earth-based composites reinforced with natural Borassus fruit fiber. The limited availability of large datasets for accurate predictions is a challenge in material science research, which this study addresses. The authors collected data on thermal conductivity, compressive and flexural strength through experiments and employed four ML techniques suitable for small datasets: linear regression (LR), random forest (RF), decision tree regressor (DTR), and gradient boosting (GB). Evaluation metrics were used to assess the performance of the ML techniques. Linear regression emerged as the most efficient, exhibiting significantly lower error values compared to the others (e.g., RMSE of 0.066 for thermal conductivity, 0.119 for compressive strength, and 0.04 for flexural strength), followed by random forest and decision tree. However, gradient boosting showed relatively poor predictive accuracy. This study demonstrates the successful application of ML for predicting the properties of earth-based composites with limited data, which could significantly reduce the cost and time associated with developing new building materials and products. Manufacturers can gain a competitive edge by using ML to streamline material development, leading to lower costs, faster innovation, and the creation of more environmentally friendly building materials for a greener construction sector.
A Multi-Indexes Based Technique for Resolving Collision in a Hash Table
(IJCSNS International Journal of Computer Science and Network Security, 2021-09-20) Saleh Abdullahi; Moussa Mahamat Boukar
The rapid development of various applications in networking system, business, medical, education, and other domains that use basic data access operations such as insert, edit, delete and search makes data structure venerable and crucial in providing an efficient method for day to day operations of those numerous applications. One of the major problems of those applications is achieving constant time to search a key from a collection. A number of different methods which attempt to achieve that have been discovered by researchers over the years with different performance behaviors. This work evaluated these methods, and found out that almost all the existing methods have non-constant time for adding and searching a key. In this work, we designed a multi-indexes hashing algorithm that handles a collision in a hash table T efficiently and achieved constant time O(1) for searching and adding a key. Our method employed two-level of hashing which uses pattern extraction h1(key) and h2(key). The second hash function h2(key) is use for handling collision in T. Here, we eliminated the wasted slots in the search space T which is another problem associated with the existing methods
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
A Performance Study of IPV6 Multicast Routing over a Dual Stack Virtual Local Area Network
(International Journal of Computer Applications, 2016-08-16) ThankGod Sani; A. A. Obiniyi; Ahiaba Solomon
The shortage address space of the Internet Protocol Version 4 (IPv4) was the major factor that gave birth to the development of Internet Protocol Version 6 (IPv6). Initially, when the shortage alarmed, network experts used mechanisms like Classless Inter Domain Routing and Address Translation to remedies and slow down the exhaustion rate, yet the necessity for IPv6 could not be avoided. Finally, IPv6 emerged in 1998. Another issue however emerged as well, the migration to the new protocol. Since the arrival date up till now IPv6 is not the default Internet routing protocol. As result of the slow migration process, IPv6 has been running alongside with IPv4 on infrastructures partly meant for IPv4 in a dual stack network. The later and the former protocols employed multicast routing as integral of part their operations; this implies multicast routing is an integral part of the two protocols. This paper tests the performance IPv6 multicast routing over a dual stack virtual local area network. Graphical Network Simulator 3 was used to configure the network and Microsoft Hyper-V was used as the hypervisor on which the six virtual machines (hosts) reside. Parameters such as throughput, latency variations, data lost and the network over heads were measured. The experiment has shown that IPv6 multicast routing did not performed well running it alongside with IPv4, therefore, after more examination, running IPv6 multicast routing alongside IPv4 multicast in dual Stack network should be discontinued.
A Recommended Digital Forensic Readiness Framework For Nigerian Banks
(International Journal of Development Research, 2019-08-28) Abdullahi, Adamu Garba; Aliyu Musa Bade
With the coming of the internet manual method of doing businesses has change dramatically to a computerized way of doing operations, similarly it also possess a threat to information security. Consequently, organizations’ that fells to address or take serious security measures are likely to fall under cyber-attacks, therefore vital information will be damage. To minimize such occurrences in both public and private organization there is a need to have digital forensic framework that they will be used in other to protect sensitive information from being compromise. Digital forensic framework (DFR) helps to exploit the use of evidence and also reducing the cost of investigation. Moreover, to prepare an organization for incident respond DFR policies and procedures are important to be implemented. Therefor this paper has proposed a framework that will be used to minimize attacks to sensitive information by cyber attackers, the framework was designed by surveying the existing frameworks available so as to find the suitable components to be used in Nigerian banking sectors and a qualitative approach was used to seek expert view on the proposed framework, the results shows the components are likely to be used in most financial sector in Nigeria as it covers the major components needed for investigations.
A Review of Fraudulent Practices in Healthcare Insurance and Machine Learning-Based Investigation Approaches
(IEEE, 2023-02-02) Aishat Salau; Nwojo Agwu Nnanna; Moussa Mahamat Boukar
Healthcare insurance fraud is a complex and costly problem that has become a concern globally. Traditional methods of detecting fraudulent claims and requests are time-consuming and often ineffective. Machine learning methods offer potential solutions to this problem by improving fraud investigation and prevention in health insurance systems. This paper presents a comprehensive review of machine learning-based approaches for addressing healthcare insurance fraud, as well as associated challenges and limitations. Despite limitations, our findings suggest that fraud could be effectively tackled by addressing the challenges identified. Areas for further research were also highlighted.
A Review On Security Issues In Wireless Sensor Networks
(International Journal of Recent Academic Research, 2019-08-21) Aliyu Musa Bade; Abdullahi, Adamu Garba
With increasing dependency on technology, Wireless Sensor Networks (WSNs) had gained more and more popularity in the areas of communication, sensing and computing among investors as well as researchers over the years. The proceeds had since been able to simplify complexity in sensing networks, revealing previously unnoticed observable facts. Major research activities being carried out in this field includes deployment, localization, synchronization, architecture, middleware, security, designing less power consuming devices, abstractions and higher level algorithms for sensor specific issues. However, WSN designs still exhibits security issues in their applications that are of concern. This paper explains a synopsis of ongoing research activities, various security problems involved in wireless sensor networks and possible solutions. The paper also reviewed into the various types of successful attacks carried out on these devices to provide future researchers with clues on how to improve their designs
A Static-dynamic Approach for UI Model Generation for Mobile Applications
(IEEE, 2018-02-02) Ibrahim Anka Salihu
Nowadays, smartphone users are increasingly relying on mobile applications to complete most of their daily tasks. To ensure acceptable quality and to meet its specifications, mobile apps need to be tested thoroughly. As testing mobile apps becomes challenging and tedious, test automation can alleviate this process. Model-based testing is an approach for test automation that is popularly used to test mobile applications. In order to benefit from model-based testing, there is a need for technique and tool for automated model generation. Therefore, this paper presents a hybrid approach for automated User Interface (UI) model generation for mobile applications. It performs static analysis of application’s bytecode to extract UI information, followed by a dynamic crawling to systematically explore and reverse engineer a model of the application under test. We then evaluate our approach on several open-source mobile applications. The results showed that our approach can generate a high-quality model from mobile applications.
A Study on Cybersecurity Awareness Among Students in Yobe State University, Nigeria
(Research Trend, 2020-07-18) Abdullahi, Adamu Garba; Maheyzah Md. Siraj; Siti Hajar Othman; M.A. Musa
The emergence of the internet and also the use of various online applications and the exposure to the social platforms that are evolving day by day have positioned students to online risk. Online fraud, cyber-bully, phishing are among those risks students are exposed to in their daily activities. To find a solution to that, cybersecurity awareness can prepare them to protect themself against such risk. This research aims to investigate the students’ awareness of basic knowledge of cybersecurity. A quantitative approach was used for data collection using a set of designed questionnaires, this method was used to investigate the students’ cybersecurity knowledge and observe their behavior toward using the internet, from the survey a total of 201 Computer Science students in the Department of Computer Science at Yobe State University, Nigeria participated in the study. The research has encountered moderate responses from the students as all universities are close at this period due to the COVID 19 pandemic, only students living in urban were able to reach out in the study. The result obtained from the experiment were analyzed and it shows the University students' cybersecurity awareness is at a satisfactory level and more than average of the students are not well aware of how to protect their data. The research contribution is, there is no active cybersecurity awareness program in place, and also females’ students are more likely to be the victim of cyber-attack. Besides that, the survey alsoindicated a high enthusiasm for students to learn more about cybersecurity.
A User Readiness Model of Social Media for Learning among Polytechnic Students in Nigeria
(Path of Science, 2019-06-30) Ibrahim Anka Salihu
The adoption of Internet resources for learning continues to grow in the world today. Despite the abundant benefit of utilizing social media due to the growth of web 2.0, an internet resource for communication and interaction, its use has not been fully embraced as a teaching tool in Nigeria. Social media is becoming a prominent communication tool and found to be facilitating teaching and learning activities among students. However, the user readiness of social media in learning by the students has been challenging. Despite the wide acceptance of social media (such as Facebook, Twitter, and WhatsApp, e.t.c.) amongst Nigerian polytechnic students, they do not utilize it for academic pursuit. This study examined the Use of Social Media among students in Nigerian Polytechnics. The main objective of this study is to find out the user readiness’ factors that influence the use of social media by the students in Nigerian Polytechnic. The evaluation results show that social media is an indispensable Internet platform among Nigerian Polytechnic students.
Advancing Preauthorization Task in Healthcare: An Application of Deep Active Incremental Learning for Medical Text Classification
(Engineering, Technology & Applied Science Research, 2023-09-29) Nnanna Agwu Nwojo; Moussa Mahamat Boukar
This study presents a novel approach to medical text classification using a deep active incremental learning model, aiming to improve the automation of the preauthorization process in medical health insurance. By automating decision-making for request approval or denial through text classification techniques, the primary focus is on real-time prediction, utilization of limited labeled data, and continuous model improvement. The proposed approach combines a Bidirectional Long Short-Term Memory (Bi-LSTM) neural network with active learning, using uncertainty sampling to facilitate expert-based sample selection and online learning for continuous updates. The proposed model demonstrates improved predictive accuracy over a baseline Long Short-Term Memory (LSTM) model. Through active learning iterations, the proposed model achieved a 4% improvement in balanced accuracy over 100 iterations, underscoring its efficiency in continuous refinement using limited labeled data.
Age Estimation from Facial Images Using Custom Convolutional Neural Network (CNN)
(International Conference on Frontiers in Academic Research, 2023-02-23) Gilbert George; Steve Adeshina; Moussa Mahamat Boukar
Given that aging is influenced by a variety of factors, including gender, ethnicity, environment, and others, automatic age assessment of facial images is a difficult challenge in computer vision and image analysis. Additionally, a significant amount of data and a laborious training phase are needed to estimate age from facial photos with near accuracy. In this study, we present a custom convolutional neural network-based age estimator that can almost precisely predict age from facial photos. We use the UTK facial image dataset using about 17475 images. We train the model to group the facial images into three groups which are; Child, Teenager and Adult. Compared to similar efforts, our method uses less training data while maintaining a high accuracy of 95%.
AMOGA: A Static-Dynamic Model Generation Strategy for Mobile Apps Testing
(IEEE, 2019-01-31) Ibrahim Anka Salihu
In the past few years, mobile devices have been increasingly replacing traditional computers, as their capabilities, such as CPU computation, memory, RAM size, and many more, are being enhanced almost to the level of conventional computers. These capabilities are being exploited by mobile apps developers to produce apps that offer more functionalities and optimized performance. To ensure acceptable quality and to meet their specifications (e.g., design), mobile apps need to be tested thoroughly. As the testing process is often tedious, test automation can be the key to alleviating such laborious activities. In the context of the Android-based mobile apps, researchers and practitioners have proposed many approaches to automate the testing process mainly on the creation of the test suite. Although useful, most existing approaches rely on reverse engineering a model of the application under test for test case creation. Often, such approaches exhibit a lack of comprehensiveness, as the application model does not capture the dynamic behavior of the applications extensively due to the incompleteness of reverse engineering approaches. To address this issue, this paper proposes AMOGA, a strategy that uses a hybrid, static-dynamic approach for generating a user interface model from mobile apps for model-based testing. AMOGA implements a novel crawling technique that uses the event list of UI element associated with each event to dynamically exercise the events ordering at the run time to explore the applications’ behavior. An experimental evaluation was performed to assess the effectiveness of our strategy by measuring the code coverage and the fault detection capability through the use of mutation testing concept. The results of the experimental assessment showed that AMOGA represents an alternative approach for model-based testing of mobile apps by generating comprehensive models to improve the coverage of the applications. The strategy proved its effectiveness by achieving high code coverage and mutation score for different applications