Rejwan Bin SulaimanUniversity of Bedfordshire · Department of Computer Science and Technology
Rejwan Bin Sulaiman
Doctor of Philosophy
Cyber Security Lecturer
About
67
Publications
117,826
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300
Citations
Introduction
I am a PhD research student at the Department of Computing, University of Bedfordshire. My research focuses on combining machine learning algorithms like ANN, deep learning, and federated learning, analysing the performance of different combinations, and proposing the best that works with real-time collaborated data.
Additional affiliations
February 2020 - present
Education
February 2020 - May 2024
February 2018 - November 2019
January 2014 - January 2018
Wrexham Glyndwr University
Field of study
- Computer Science
Publications
Publications (67)
Brain tumors are among the most fatal and devastating diseases, and they often result in a significant reduction in life expectancy. The devising of treatment plans that can extend the lives of affected individuals hinges on an accurate diagnosis of these tumors. Identifying and analyzing large volumes of magnetic resonance imaging (MRI) data manua...
The rise of fake news has made the need for effective detection methods , including in languages other than English, increasingly important. The study aims to address the challenges of Bangla which is considered a less important language. To this end, a complete dataset containing about 50,000 news items is proposed. Several deep learning models ha...
![Figure 1: Logical function expressions [24]](profile/Rejwan-Bin-Sulaiman/publication/382877812/figure/fig20/AS:11431281286923602@1730158265822/Logical-function-expressions-24_Q320.jpg)
![Figure 2: A simple decision tree [25]](profile/Rejwan-Bin-Sulaiman/publication/382877812/figure/fig21/AS:11431281286894047@1730158265987/A-simple-decision-tree-25_Q320.jpg)
![Figure 3: The k-nearest neighbour sample [26]](profile/Rejwan-Bin-Sulaiman/publication/382877812/figure/fig22/AS:11431281286894048@1730158266125/The-k-nearest-neighbour-sample-26_Q320.jpg)
![Figure 4: Geometric Margin [27] Category & Boosting (Catboost): This...](profile/Rejwan-Bin-Sulaiman/publication/382877812/figure/fig23/AS:11431281286875535@1730158266266/Geometric-Margin-27-Category-Boosting-Catboost-This-framework-is-popular-and-easy_Q320.jpg)
![Figure 5: The Example of SMOTE Formation Sample [28]](profile/Rejwan-Bin-Sulaiman/publication/382877812/figure/fig24/AS:11431281286875536@1730158266403/The-Example-of-SMOTE-Formation-Sample-28_Q320.jpg)
Sound classification is a multifaceted task that necessitates the gathering and processing of vast quantities of data, as well as the construction of machine learning models that can accurately distinguish between various sounds. In our project, we implemented a novel methodology for classifying both musical instruments and environmental sounds, ut...
Sound classification is a multifaceted task that necessitates the gathering and processing of vast quantities of data, as well as the construction of machine learning models that can accurately distinguish between various sounds. In our project, we implemented a novel methodology for classifying both musical instruments and environmental sounds, ut...
![Figure 1: Logical function expressions [24]](profile/Syeda-Alam-8/publication/384678168/figure/fig1/AS:11431281282168101@1728238699650/Logical-function-expressions-24_Q320.jpg)
![Figure 2: A simple decision tree [25]](profile/Syeda-Alam-8/publication/384678168/figure/fig2/AS:11431281282168102@1728238699793/A-simple-decision-tree-25_Q320.jpg)
![Figure 3: The k-nearest neighbour sample [26]](profile/Syeda-Alam-8/publication/384678168/figure/fig3/AS:11431281282188161@1728238699946/The-k-nearest-neighbour-sample-26_Q320.jpg)
![Figure 4: Geometric Margin [27] Category & Boosting (Catboost): This...](profile/Syeda-Alam-8/publication/384678168/figure/fig4/AS:11431281282168103@1728238700081/Geometric-Margin-27-Category-Boosting-Catboost-This-framework-is-popular-and-easy_Q320.jpg)
![Figure 5: The Example of SMOTE Formation Sample [28]](profile/Syeda-Alam-8/publication/384678168/figure/fig5/AS:11431281282188162@1728238700229/The-Example-of-SMOTE-Formation-Sample-28_Q320.jpg)
Nowadays, credit card transactions are exponentially increasing as a form of online payment. That creates technical pressure on the financial institution to incur losses due to credit card fraud. It is no wonder that credit card fraud is making people feel insecure and unsafe about using the services provided by banks. Data mining reasons on offlin...
Consumer confidence, business credibility, and economic development are all negatively impacted by the prevalence of counterfeit items in circulation. The potential role of blockchain technology in finding a solution to this issue is explored in this chapter. For product authentication, it employs Ethereum, smart contracts, and QR codes to create a...
The digitisation of healthcare records continues to expand, and the security and privacy of sensitive patient information become increasingly critical. By leveraging AI technologies, such as machine learning and natural language processing, healthcare organisations can implement advanced security measures that enhance healthcare records’ security a...
Consumer confidence, business credibility, and economic development are all negatively impacted by the prevalence of counterfeit items in circulation. The potential role of blockchain technology in finding a solution to this issue is explored in this chapter. For product authentication, it employs Ethereum, smart contracts, and QR codes to create a...
This study explores how employee skill sets in the retail industry are affected by the Fourth Industrial Revolution (4IR). Traditional retail has a strong need to change as technology rapidly alters consumer expectations. The study examines how workers develop new skill sets to remain competitive in the rapidly evolving 4IR market. Workers need to...
The rise of fake news has made the need for effective detection methods, including in languages other than English, increasingly important. The study aims to address the challenges of Bangla which is considered a less important language. To this end, a complete dataset containing about 50,000 news items is proposed. Several deep learning models hav...
Blood cell classification and counting are vital for the diagnosis of various blood-related diseases, such as anemia, leukemia, and thrombocytopenia. The manual process of blood cell classification and counting is time-consuming, prone to errors, and labor-intensive. Therefore, we have proposed a DL based automated system for blood cell classificat...
The blockchain is a revolutionary computing framework that uses a unique data structure to create a record-keeping system that is accessible, communal, and decentralized. It has a wide range of applications in several disciplines. The worldwide implementation of electronic voting systems in public elections is increasing, propelled by the many bene...
Credit card fraud is a significant threat to customers and financial
institutions worldwide, causing billions of dollars in losses each year. Machine
learning algorithms are used to detect fraudulent patterns, but the issue is that the
datasets are imbalanced, and banks cannot share their customers' transaction data
for privacy reasons. The primary...
The issue of credit card fraud poses a significant concern for users of online transactions, necessitating the implementation of effective fraud detection mechanisms. Fraud detection is often done using machine learning algorithms. Practitioners can compare and analyse algorithms to get the best one for their credit card fraud detection scenario. T...
Fake products have become a common term in business, especially in the consumer market. Due to the fake products, companies are going through a lot of financial losses, hampering the brand name, and at the end of the day, every day, they are losing customers. Product counterfeiting is rampant in the modern economy, and it is difficult to detect whe...
Credit card fraud has increased vulnerability effects due to the large usage functions for customers due to innovative technologies and communication patterns. This article presents a review and important analysis of credit card fraud detection and prediction of fraudulent transactions based on cutting-edge research. The study provides a limited in...
Precise prediction and detection of epilepsy, a
common neurological condition marked by sporadic and
repeated seizures, is necessary for efficient management and
patient care. To do accurate and reliable seizure detection,
machine learning (ML) on electroencephalogram (EEG)
recordings is a good choice because of its capacity to provide
insightful i...
One of the most neglected sources of energy loss is streetlights that generate too much light in areas where it is not required. Energy waste has enormous economic and environmental effects. In addition, due to the conventional manual nature of operation, streetlights are frequently seen being turned ‘ON’ during the day and ‘OFF’ in the evening, wh...
From the perspective of any nation, rural areas generally present a comparable
set of problems, such as a lack of proper healthcare, education, living
conditions, wages and market opportunities. Some nations have created and
developed the concept of smart villages during the previous few decades,
which effectively addresses these issues. The landsc...
Biomedical Engineering's Internet of Medical Things (IoMT) is helping to improve the accuracy, dependability, and productivity of electronic equipment in the healthcare business. Real-time sensory data from patients may be delivered and subsequently analyzed through rapid development of wearable IoMT devices, such as neuro-stimulation devices with...
This paper of work examines the SolarWinds attack, designed on Orion Platform security incident. It analyses the persistent threats agents and potential technical attack techniques to gain unauthorized access. In 2020 SolarWinds attack indicates an initial breach disclosure on Orion Platform software by malware distribution on IT and government org...
The LockBit 3.0 ransomware variant is arguably the most threatening of malware in recent times. With no regard for a victim's industry, the ransomware has undergone several evolutions to arrive at an adaptable and evasive variant which has been a menace to governments and organisations, recently infiltrating Advanced Computer Software group. Previo...
Heart failure is a life-threatening condition that affects millions of people worldwide. The ability to accurately predict patient survival can aid in early intervention and improve patient outcomes. In this study, we explore the potential of utilizing data pre-processing techniques and the Extra-Tree (ET) feature selection method in conjunction wi...
Epilepsy is a prevalent neurological disorder characterized by recurrent and unpredictable seizures, necessitating accurate prediction for effective management and patient care. Application of machine learning (ML) on electroencephalogram (EEG) recordings, along with its ability to provide valuable insights into brain activity during seizures, is a...
Potatoes are the third-largest food crop globally, but their production frequently encounters difficulties because of aggressive pest infestations. Early classification those potato pests plays an important role in the detection and prevention of their notorious attack. The aim of this study is to investigate the various types and characteristics o...
In certain Asian countries, Jute is one of the primary sources of income and Gross Domestic Product (GDP) for the agricultural sector. Like many other crops, Jute is prone to pest infestations, and its identification is typically made visually in countries like Bangladesh, India, Myanmar, and China. In addition, this method is time-consuming, chall...
Potatoes are the third-largest food crop globally, but their production frequently encounters difficulties because of aggressive pest infestations. Early classification those potato pests plays an important role in the detection and prevention of their notorious attack. The aim of this study is to investigate the various types and characteristics o...
Artificial Intelligence (AI) is an emerging field that seeks to replicate or emulate human-like cognitive abilities using artificial means. As the world changes, the development and application of AI tools and technologies in areas such as agriculture, medicine, healthcare, and education are growing at an unprecedented pace. This chapter presents a...
In certain Asian countries, Jute is one of the primary sources of income and Gross Domestic Product (GDP) for the agricultural sector. Like many other crops, Jute is prone to pest infestations, and its identification is typically made visually in countries like Bangladesh, India, Myanmar, and China. In addition, this method is time-consuming, chall...
Potatoes are the third-largest food crop globally, but their production frequently encounters difficulties because of aggressive pest infestations. The aim of this study is to investigate the various types and characteristics of these pests and propose an efficient PotatoPestNet AI-based automatic potato pest identification system. To accomplish th...
Unmanned aerial vehicles (UAVs) have recently attracted numerous regards from researchers and academics. The UAV is useful in heterogeneous applications such as transportation, disaster monitoring, surveillance, etc. Because UAVs have limited internal energy, clustering can effectively balance energy consumption and load. On the other hand, scene c...
Due to digitalization in everyday life, the need for automatically recognizing handwritten digits is increasing. Handwritten digit recognition is essential for countless applications in various industries. Bengali ranks the fifth largest dialect in the world, with 265 million speakers (native and non-native combined), occupying 4% of the world popu...
Monkeypox is a rare disease that raised concern among medical specialists following the convi-19 pandemic. It's concerning since monkeypox is difficult to diagnose early on because of symptoms that are similar to chickenpox and measles. Furthermore, because this is a rare condition, there is a knowledge gap among healthcare professionals. As a resu...
![Figure 2. Digital Soil Mapping Framework [60]](publication/367389019/figure/fig1/AS:11431281114692032@1674616535878/Digital-Soil-Mapping-Framework-60_Q320.jpg)
From the perspective of any nation, rural areas generally present a comparable set of problems, such as a lack of proper health care, education, living conditions, wages, and market opportunities. Some nations have created and developed the concept of smart villages during the previous few decades, which effectively addresses these issues. The land...
Due to digitalization in everyday life, the need for automatically recognizing handwritten digits is increasing. Handwritten digit recognition is essential for numerous applications in various industries. Bengali ranks the fifth largest language in the world with 265 million speakers (Native and non-native combined) and 4 percent of the world popul...
The use of credit cards has become quite common these days as digital banking has become the norm. With this increase, fraud in credit cards also has a huge problem and loss to the banks and customers alike. Normal fraud detection systems, are not able to detect the fraud since fraudsters emerge with new techniques to commit fraud. This creates the...
![Figure 5: Morphological Flow [49]](publication/362171603/figure/fig2/AS:1180479092985857@1658459556390/Morphological-Flow-49_Q320.jpg)
![Figure 6: KNN classification Algorithm [24]](publication/362171603/figure/fig3/AS:1180479092985861@1658459556431/KNN-classification-Algorithm-24_Q320.jpg)
![Figure 7: SVM hyperplane margin [39]](publication/362171603/figure/fig4/AS:1180479092985862@1658459556466/SVM-hyperplane-margin-39_Q320.jpg)
![Figure 8: Non-Linear SVM using kernel [27][33]](publication/362171603/figure/fig5/AS:1180479092985863@1658459556504/Non-Linear-SVM-using-kernel-2733_Q320.jpg)
Providing the best customer experience is one of the primary concerns for the firms that are based online. The advancement of machine learning is revolutionising the company's attitude towards the client through improving the service quality by implementing chatbot solutions, which gives the user instant and satisfactory answers to their enquiries....
Face detection and identification is the most difficult and often used task in Artificial Intelligence systems. The goal of this study is to present and compare the results of several face detection and recognition algorithms used in the system. This system begins with a training image of a human, then continues on to the test image, identifying th...
![Fig. 1 Amount of Master credit card issued worldwide [51]](profile/Vitaly-Schetinin/publication/360408387/figure/fig1/AS:1178720161284098@1658040194750/Amount-of-Master-credit-card-issued-worldwide-51_Q320.jpg)
![Fig. 2 Amount of Visa credit issued worldwide [50]](profile/Vitaly-Schetinin/publication/360408387/figure/fig2/AS:1178720161275904@1658040194786/Amount-of-Visa-credit-issued-worldwide-50_Q320.jpg)
Massive usage of credit cards has caused an escalation of fraud. Usage of credit cards has resulted in the growth of online business advancement and ease of the e-payment system. The use of machine learning (methods) are adapted on a larger scale to detect and prevent fraud. ML algorithms play an essential role in analysing customer data. In this r...
In this paper, we attempt to verify a hypothesis of informational efficiency of financial markets, known as “random walk” introduced by Fama. Such hypotheses could be considered in relation to financial crises. In our study the hypothesis is tested on data taken from Warsaw Stock Exchange in 2007–2009 years. The hypothesis is tested by predictive m...
The honeypots that are available in the market are very flexible tools for participating in security defence. Of course, these are the tool that is meant to be targeted in order to achieve more knowledge about the attacker, their intentions, and the tools they use to gain access or attack. But, now from that specific definition, they have evolved....
Blockchain is one of the emerging technology of 21 st century. It is getting common to the people helping them by providing better financial services without any centralised medium (banks, agencies etc.). Although it has a strong backbone of cryptography which ensures the data protection, however, security vulnerabilities are still the part of this...
The world is getting into the practice of implementing 5G network on a business scale; there is research work that is covering the limits beyond 5G (B5G) and 6G. 6G network with the concept of more efficiency and better performance. The demand for network efficiency was always heightened, which is followed by the quality of service and availability...
Now a day’s network security is one of the biggest concern and threat to the World. IoT is an emerging technology which is getting common day by day and billions of devices are interconnected to a wide network platform which are creating privacy and security concerns. Massive number of devices being used over internet by individuals and corporates...
Many researchers have invested their time, effort, and energy on the research area of “Vehicular-to-everything” which is also known as V2X in term of security and vulnerabilities. For communications like V2X, the European Telecommunications Standards Institute (ETSI) has been engaged in order to formulate quality standards for these types of the me...
![Figure 5: Morphological Flow [49]](profile/Rejwan-Bin-Sulaiman/publication/340226275/figure/fig2/AS:873646004375555@1585304847483/Morphological-Flow-49_Q320.jpg)
![Figure 6: KNN classification Algorithm [24]](profile/Rejwan-Bin-Sulaiman/publication/340226275/figure/fig3/AS:873646004375556@1585304847520/KNN-classification-Algorithm-24_Q320.jpg)
![Figure 7: SVM hyperplane margin [39]](profile/Rejwan-Bin-Sulaiman/publication/340226275/figure/fig4/AS:873646004383745@1585304847545/SVM-hyperplane-margin-39_Q320.jpg)
![Figure 8: Non-Linear SVM using kernel [27][33]](profile/Rejwan-Bin-Sulaiman/publication/340226275/figure/fig5/AS:873646004383748@1585304847734/Non-Linear-SVM-using-kernel-2733_Q320.jpg)
Providing the best customer experience is one of the primary concerns for the firms that are based online. The advancement of machine learning is revolutionising the company’s attitude towards the client through improving the service quality by implementing chatbot solutions, which gives the user instant and satisfactory answers to their enquiries....
Many researchers have invested their time, effort, and energy on the research area of “Vehicular-to-everything” which is also known as V2X in term of security and vulnerabilities. For communications like V2X, the European Telecommunications Standards Institute (ETSI) has been engaged in order to formulate quality standards for these types of the me...
The honeypots that are available in the market are very flexible tools for participating in security defence. Of course, these are the tool that is meant to be targeted in order to achieve more knowledge about the attacker, their intentions, and the tools they use to gain access or attack. But, now from that specific definition, they have evolved....
Voice Controlled Wireless Home Automation Based on internet/ Bluetooth/ wi-fi is a project that is integrated system with mobile phone (application) to give the facility to the elderly and the disable people, so that they can easily control home utilities fully Based on their phone through voice command. The device is built in such a way that it wi...
This paper will cover the conversion of normal conventional cars into the autonomous car (Driverless car), problems associated with it, objectives, requirements and the expected outcome of this step. It will also cover the standards and give the critical comparison between conventional and driverless cars. This AI based car will cause a huge change...
The Blockchain is an ingenious and remarkable invention. This technology created the backbone of a new type of
internet. It was originally designed for the digital currency, Bitcoin, in which you can send digital money to anyone, even a
stranger. Originally, it transmits bitcoin. It is considered a revolutionary technology. Blockchain helps in crea...
The paper is prepared for exploring the communication as well as
the interaction between two species- humans and robots. The
variables like sex, emotion, lust and sex have already been taken
in terms of completing the study. The innovation of the technology
and its continued impact on future trends and society will
be vividly discussed. Robotics Ar...
A city situated in an urban area that aces in different sectors of the economy, people, governing, strength in human capital, the strong infrastructure of ICT, is said to be a smart city. This smart city term is fairly a recent approach to manage the difficulties of the city life that can mark up the efficiency, minimize the expenses and develops t...
![Figure 2: Anti-tamper operation of the blockchain[10]](profile/Rejwan-Bin-Sulaiman/publication/326758484/figure/fig1/AS:671865395744774@1537196601731/Anti-tamper-operation-of-the-blockchain10_Q320.jpg)
![Figure 3: Confidentiality in the blockchain[14]](profile/Rejwan-Bin-Sulaiman/publication/326758484/figure/fig2/AS:671865395757081@1537196601778/Confidentiality-in-the-blockchain14_Q320.jpg)
Blockchain is one of the emerging technology of 21st century. It is getting common to the people helping them by providing better financial services without any centralised medium (banks, agencies etc.). Although it has a strong backbone of cryptography which ensures the data protection, however, security vulnerabilities are still the part of this...
Questions
Questions (3)
I am working with the Credit card dataset. I am aware of the fact that the Banks and financial institutions do not share the dataset with third-party companies or researchers.
I just need to know the name of the columns that are used in the header of a transaction.
How can I get those data?
Will I try to contact security personals in the banks?
I am new in data Science area, more concisely in machine learning. working with imbalanced credit card data to detect frauds.
I can use matplotlib and some other python tools to get visual graphs and diagrams. But I am curious, what are other tools that are been used in the industry.
Because of GDPR and confidentiality issues, no bank will expose the user's data to third-party researchers, and hence we cannot train our model for real-time fraud detection with real data (What I mean by real data is, that the data has not been modified | changed by any mean). All researchers have worked on a common data set, which is 7 years old, and that might not have all the Features that potentially changed over time. So, I want to use the federate learning Algorithm to train the model with real dataset to follow GDPR law and access to information while preserving the privacy of users.
