Investigation of Applying Machine Learning for Watch-List Filtering in Anti-Money Laundering
Authors : Mohannad Alkhalili; Mahmoud H. Qutqut; Fadi Almasalha
Abstract : Financial institutions must meet international regulations to ensure not to provide services to criminals and terrorists. They also need to continuously monitor financial transactions to detect suspicious activities. Businesses have many operations that monitor and validate their customer's information against sources that either confirm their identities or disprove. Failing to detect unclean transaction(s) will result in harmful consequences on the financial institution responsible for that such as warnings or fines depending on the transaction severity level. The financial institutions use Anti-money laundering (AML) software sanctions screening and Watch-list filtering to monitor every transaction within the financial network to verify that none of the transactions can be used to do business with forbidden people. Lately, the financial industry and academia have agreed that machine learning (ML) may have a significant impact on monitoring money transaction tools to fight money laundering. Several research work and implementations have been done on Know Your Customer (KYC) systems, but there is no work on the watch-list filtering systems because of the compliance risk. Thus, we propose an innovative model to automate the process of checking blocked transactions in the watch-list filtering systems. To the best of our knowledge, this paper is the first research work on automating the watch-list filtering systems. We develop a Machine Learning - Component (ML-Component) that will be integrated with the current watch-list filtering systems. Our proposed ML-Component consists of three phases; monitoring, advising, and taking action. Our model will handle a known critical issue, which is the false positives (i.e., transactions that are blocked by a false alarm). Also, it will minimize the compliance officers' effort, and provide faster processing time. We performed several experiments using different ML algorithms (SVM, DT, and NB) and found that the SVM outperforms other algorithms. Because our dataset is nonlinear, we used the polynomial kernel and achieved higher accuracy for predicting the transactionś decision, and the correlation matrix to show the relationship between the numeric features.
Keywords : "Anti-money laundering, financial transactions monitoring, machine learning (ML), sanctions screening, watch-list filtering.
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Overview of the Current Status of NoSQL Database
Authors : Yasmin Rasheed, Mahmoud H. Qutqut and Fadi Almasalha
Abstract : Nowadays with the accelerated development of the Internet and Cloud computing, the fast growth of technology generates a massive amount of data. Businesses and people generate this data by using web apps, social media, and new technologies. These data, in general, could be structured, semi-structured or unstructured. Because of the different types of data and the big data that is generated, there is a need for a database to be able to store and process these data effectively to enhance the performance when reading and writing. So, there is a need for a new design for the database, and it is not suitable for storing, analyzing and performing data in a relational database for big data. In addition to that, many new challenges faced the traditional relational database; especially in the applications that required large scale and high concurrency such as search engines. In response to that, NoSQL has developed to solve these types of problem. NoSQL database has many advantages that make it gain significant popularity over the last few years and used widely. It read and write the data quickly, expands easily, low cost and many other features. In this paper, we overview the NoSQL database and its characteristics in the field of the Internet of Things (IoT). We also provide two representative use cases of using the NoSQL database in current technologies.
Keywords : NoSQL; database; relational database; IoT
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Hybrid User Action Prediction System for Automated Home using Association Rules and Ontology
Authors : Amneh Shaban 1 ; Fadi Almasalha 1 ; Mahmoud H. Qutqut
Abstract : Nowadays, with the rapid increase of Internet users, the Internet services dominate a primary part of our lifestyle. Moreover, the evolution of the internet of things has introduced new insights into smart platforms and devices that leads to the new vision of ‘smart homes’. The idea of smart homes is not a recent concept; it has been in high interest by both academia and industry to make smart homes a more convenient technology for human's comfort. In this study, the authors propose a new hybrid prediction system based on the frequent pattern (FP)-growth and ontology graphs for home automation systems. Their proposed system simulates the human prediction actions by adding common-sense data by utilizing the advantages of the ontology graph and the FP-growth to find a better solution in predicting home user actions for automated systems. For the evaluation of the proposed system, two ontology graphs are introduced with FP-growth to achieve the best results. Both graphs are tested through multiple weight values with the results of FP-growth. As a result, the best weight distribution selected in this study is (70, 30) for time and location ontology graphs respectively. Their results showed that the proposed prediction system achieved an accuracy of 79% for all weekdays and 81% excluding weekend days.
Keywords : Internet; home automation; ontologies (artificial intelligence); data mining
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A new steganography technique using JPEG images
Authors : Rand A. Watheq, Fadi Almasalha, and Mahmoud H. Qutqut
Abstract : Steganography is a form of a security technique that uses ambiguity to hide a secret message within an ordinary message between senders and receivers. In this paper, we propose a new steganography technique for hiding data in Joint Photographic Experts Group (JPEG) images as it is the most known type of image compression between the lossy type compressions. Our proposed work is based on lossy compression (frequency domain) in images. This type of compression is susceptible to change even for the smallest amount of change which raises the difficulty to find a proper location to embed data. This should be done without affecting the image quality and without allowing anyone to notice the hidden message. From the senders side, first, we divide the image into 8* 8 blocks, then apply a Discrete Cosine Transform (DCT), Quantization, and zigzag processes respectively. Second, the secret message is embedded at the end of each selected zigzag block array using the best method of our experimental results. Third, the rest of the code applies the Run Length Code (RLC), Different Pulse Code Modularity (DPCM) and Huffman encoder to obtain the compressed image that includes the embedded message. From the receiver’s side, we will reverse the previous steps to extract the secret message using an encrypted shared key via a secure channel. Our experimental results show that the best array content size of zigzag computed coefficients are between 1 to 20. This selection allows us to utilize more than half of the image blocks to embed the secret message and the difference between the cover image that holds the secret message and the original cover image is very minimal and hard to detect.
Keywords : "Steganography; hide secret message; JPEG image;lossy compression; frequency domain; zigzag
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Comprehensive Survey of the IoT Open-Source Oss
Authors : Mahmoud H. Qutqut,Aya Al-Sakran,Fadi Almasalha,Hossam S. Hassanein
Abstract : The Internet of things (IoT) has attracted a great deal of research and industry attention recently and is envisaged to support diverse emerging domains including smart cities, health informatics, and smart sensory platforms. Operating system (OS) support for IoT plays a pivotal role in developing scalable and interoperable applications that are reliable and efficient. IoT is implemented by both high-end and low-end devices that require OSs. Recently, the authors have witnessed a diversity of OSs emerging into the IoT environment to facilitate IoT deployments and developments. In this study, they present a comprehensive overview of the common and existing open-source OSs for IoT. Each OS is described in detail based on a set of designing and developmental aspects that they established. These aspects include architecture and kernel, programming model, scheduling, memory management, networking protocols support, simulator support, security, power consumption, and support for multimedia. They present a taxonomy of the current IoT open-source OSs. The objective of this survey is to provide a well-structured guide to developers and researchers to determine the most appropriate OS for each specific IoT devices/applications based on their functional and non-functional requirements. They remark that this is the first such tutorial style paper on IoT OSs.
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Machine Learning Classification Techniques for Heart Disease Prediction: A Review
Authors : Maryam I. Al-Janabi 1 , Mahmoud H. Qutqut 1 2 *, Mohammad Hijjawi 1
Abstract : The most crucial task in the healthcare field is disease diagnosis. If a disease is diagnosed early, many lives can be saved. Machine learning classification techniques can significantly benefit the medical field by providing an accurate and quick diagnosis of diseases. Hence, save time for both doctors and patients. As heart disease is the number one killer in the world today, it becomes one of the most difficult diseases to diagnose. In this paper, we provide a survey of the machine learning classification techniques that have been proposed to help healthcare professionals in diagnosing heart disease. We start by overviewing the machine learning and describing brief definitions of the most commonly used classification techniques to diagnose heart disease. Then, we review representable research works on using machine learning classification techniques in this field. Also, a detailed tabular comparison of the surveyed papers is presented.
Keywords : Heart Disease; Heart Disease Diagnosis; Heart Disease Prediction; Machine Learning; Machine Learning Classification Techniques.
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Software Re-engineering: An Overview
Authors : Manar Majthoub; Mahmoud H. Qutqut; Yousra Odeh
Abstract : The core of software re-engineering is to enhance or change existing software so it can be understood, managed, and reused as new software. When the system's software architecture and platforms become absolute and need to be changed, re-engineering is needed. The importance of software re-engineering lies in its ability to recover and reuse things which are already existing in an outdated system. This will obviously lower the cost of system maintenance and set up the basis for future software development. This paper presents brief overview of software re-engineering and highlights its future path.
Keywords : Software,Reverse engineering,Aging,Information technology,Documentation,Software algorithms,Computer science
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An Overview of the Internet of Things Closed Source Operating Systems
Authors : Aya Al-Sakran; Mahmoud H. Qutqut; Fadi Almasalha; Hossam S. Hassanein; Mohammad Hijjawi
Abstract : The Internet of Things (IoT) attract a great deal of research and industry attention recently and are envisaged to support diverse emerging domains including intelligent transportation, smart cities, and health informatics. Operating system support for IoT plays a pivotal role in developing interoperable and scalable applications that are efficient and reliable. IoT is implemented by both high-end and low-end devices that require an operating system to run. Recently, we have witnessed a diversity of OSs emerging into IoT environment to facilitate IoT deployments and developments. In this paper, we present an overview of the common and existing closed source OSs for IoT. This paper is written in a tutorial style where each OS is described in details based on a set of designing and development aspects that we established. These aspects include architecture and kernel, memory management, scheduling, power consumption, networking protocols support, security, programming model, and multimedia support. The objective of this survey is to provide a well-structured guide to developers and researchers to determine the most appropriate OS for each specific IoT applications/devices based on their functional and non-functional requirements.
Keywords : Memory management,Protocols,Kernel,Internet of Things,Hardware,Programming
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Video Security in the Internet of Things: An Overview
Authors : Mina A. Hamoudy, Mahmoud H. Qutqut and Fadi Almasalha
Abstract : Internet of Things (IoT) became one of the core networking paradigms nowadays. IoT is already interconnected with millions of things (e.g., sensors, appliances, video cameras, devices); and is expected soon to connect billions of new devices. An important challenge for supporting multimedia applications in the IoT is the security heterogeneity of several technologies, devices, and protocols. In this paper, we overview video streaming in the IoT networks, focusing on the security of video in IoT. We present a comprehensive overview of security issues and challenges in video streaming in IoT in order for a better understanding.
Keywords : Internet of Things; Security; Video Streaming; Video Traffic; IoT Video, Video Security.
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Mobilitty Management in Femtocell Networks
Authors : Mahmoud H. Qutqut, Hossam S. Hassanein
Abstract : Current wireless broadband networks (WBNs) are facing several limitations and considerations, such as poor indoor coverage, explosive growth in data usage, and massive increase in number of WBN subscribers. Various inventions and solutions are used to enhance the coverage and increase the capacity of wireless networks. Femtocells are seen as a key next step in wireless communication today. Femtocells offer excellent indoor voice and data coverage. As well, femtocells can enhance the capacity and offload traffic from macrocells. There are several issues that must be considered though to enable the successful deployment of femtocells. One of the most important issues is mobility management. Since femtocells will be deployed densely, randomly, and by the millions, providing and supporting seamless mobility and handoff procedures is essential. We present a broad study on mobility management in femtocell networks. Current issues of mobility and handoff management are discussed. Several research works are overviewed and classified. Finally, some open and future research directions are discussed.
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Outage Probability Analysis of Mobile Small cells over LTE-A Networks
Authors : Mohamed F. Feteiha; Mahmoud H. Qutqut; Hossam S. Hassanein
Abstract : Cellular operators have concluded that small cell deployments are a very cost-effective and quick solution to meet the ever growing demands on capacity and coverage in cellular networks for indoor and outdoor environments. While traveling in public transit vehicles, cellular subscribers usually experience poor signal reception and low bandwidth. We hence consider deploying small cells onboard (i.e., mobile small cells) such vehicles. This should enhance subscribers' quality of experience (QoE). We consider a Small Base Station (SBS) mounted in a public transit bus (i.e., mobile SBS) to serve onboard users. The mobile SBS aggregates users' traffic to and from the macroBSs. To further extract the underlying rich multipath-Doppler diversities resulting from the fast mobility and the associated selective fading channel, a pre-coded transmission is deployed in the mobile SBS.We examine the achievable gain from enabling aggregation through mobile SBS in terms of the outage probability. We derive a tight-bound closed-form expression for the outage probability in the downlink (DL). Our results indicate that significant gain in outage probability and coverage are achievable.
Keywords : Mobile communication,Vehicles,Scattering,Wireless communication,Relays,Fading,Femtocells
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Dynamic Small Cell Placement Strategies for LTE Heterogeneous Networks
Authors : Mahmoud H. Qutqut; Hatem Abou-zeid; Hossam S. Hassanein; A. M. Rashwan; Fadi M. Al-Turjman
Abstract : Small cell deployments have proven to be a cost-effective solution to meet the ever growing capacity and coverage requirements of mobile networks. While small cells are commonly deployed indoors, more recently outdoor roll-outs have garnered industry interest to complement existing macrocell infrastructure. However, the problem of where and when to deploy these small cells remains a challenge. In this paper, we investigate the small base station (SBS) placement problem in high demand outdoor environments. First, we propose a dynamic placement strategy (DPS) that optimizes SBS deployment for two different network objectives: minimizing data delivery cost, and minimizing macrocell utilization. We formulate each problem as a mixed integer linear program (MILP) that determines the optimal set of deployment locations among the candidate hot-spots to meet each network objective. Then we develop two greedy algorithms, one for each objective, that achieve close to optimal MILP performance. Our simulation results demonstrate that significant delivery cost and MBS utilization reductions are possible by incorporating the proposed deployment strategies.
Keywords : Macrocell networks,Scattering,Greedy algorithms,Throughput,Educational institutions,Base stations
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Pairwise Error Probability Evaluation of Cooperative Mobile Femtocells
Authors : Mohamed F. Feteiha; Mahmoud H. Qutqut; Hossam S. Hassanein
Abstract : Cellular subscribers while travelling in public transportation vehicles, such as streetcars and buses, often experience poor signal reception and low bandwidth when using their cellular devises onboard. Small cell deployment of, for example, femtocells is considered as one of the most promising solutions for cellular operators to enhance coverage and meet the increasing need for capacity and QoS support expected by cellular subscribers. We consider a mobile Femto Base Station (mobFBS) installed in the public transportation vehicle, with an external antenna installed on the roof, to offer enhanced coverage and improved capacity onboard. We investigate the performance gains of a communication scheme in downlink LTE-A networks with mobFBSs. Users are assumed to be travelling using a public transportation vehicle, and the transmission between macroBS and users occurs through a mobFBS. The associated wireless links for this type of fast mobility are characterized by a doubly-selective fading channel. This causes performance degradation in terms of increased error probability. By taking advantage of the more powerful central processing mobFBS, we make use of a precoded technique to overcome the performance degradation that results from the wireless fading channel. We investigate the performance gain in terms of pairwise error probability (PEP) via a derived closed-form expression. Our analytical and simulation results indicate that significant diversity gains are achievable and error rates are tremendously reduced.
Keywords : Femtocells,Wireless communication,Vehicles,Macrocell networks,Fading
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HOF: A History-based Offloading Framework for LTE Networks using Mobile Small cells and Wi-Fi
Authors : Mahmoud H. Qutqut; Fadi M. Al-Turjman; Hossam S. Hassanein
Abstract : Small cell deployments are seen as a promising solution for mobile operators due to their potential to improve coverage and increase capacity for indoor areas in a cost-efficient way. Meanwhile, other deployment scenarios are also being sought, such as in public transportation vehicles including buses and streetcars. In this paper, we propose a novel History-based Offloading Framework (HOF) to relieve overburdened macro networks from data traffic generated by mobile users in public transportation vehicles by utilizing small cells and Wi-Fi networks. A small base station (SBS) is installed onboard the vehicle; called a mobile SBS (mobSBS). Mobile users communicate with the mobSBS instead of the distant Macro base station (macroBS). In order to have efficient offloading in terms of bandwidth utilization, mobile data users are prioritized according to different pre-set classes. Our framework takes into account the mobile user's priority and service history to alleviate the effects of non-incessant Wi-Fi availability in order to maximize the offloaded macrocell data traffic. Extensive simulation results have shown that our proposed framework is highly effective in terms of the average offloaded macroBSs data traffic and the total count of offloaded users from the macroBSs.
Keywords : IEEE 802.11 Standards,Mobile computing,Vehicles,Macrocell networks,History,Bandwidth
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MFW: Mobile Femtocells utilizing WiFi, A Data Offloading Framework for Cellular Networks using Mobile Femtocells
Authors : Mahmoud H. Qutqut; Fadi M. Al-Turjman; Hossam S. Hassanein
Abstract : The ever growing data traffic generated by users in cellular networks is becoming more challenging and straining for cellular operators. Thus, developing efficient mechanisms that enable cellular operators to offload data traffic from their networks in a cost-effective manner is essential. To this end, we propose a generic framework (MFW) that exploits femtocells and WiFi networks. The framework allows cellular operators to offload part of the traffic load generated by mobile users in public transportation systems, viz.; buses, streetcars. Regular Femto Base Stations (FBSs) are installed in these vehicles to offer cellular coverage for mobile devices, called the mobile FBS (mobFBS). The mobFBS utilizes ubiquitous WiFi access points as a backhaul to route the traffic to the cellular operator's network through WiFi instead of the loaded macrocells. Mobile data users are categorized in our framework in different prioritized classes in order to efficiently allocate the mobFBS bandwidth to the maximum number of users. Efficiency is considered in terms of bandwidth utilization, enhancing capacity and managing grouped data traffic in vehicles. We elaborate on the performance of MFW via numerical experiments, emulating practical applications, viz. “Skype” and “YouTube”, and demonstrate the efficiency of our framework in terms of data traffic offloading.
Keywords : IEEE 802.11 Standards,Femtocells,Mobile computing,Vehicles,Macrocell networks,Bandwidth
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