Biography

Dr. Abdelkader Ouda is an accomplished academic and industry professional with over three decades of experience in computer science, software engineering, and information security. He earned his B.Sc. (Hons) and M.Sc. degrees in Computer Science and Pure Mathematics from Ain Shams University, Cairo, Egypt, in 1986 and 1993, respectively. In 2005, he completed his Ph.D. in Computer Science at the University of Western Ontario, Canada. Currently, Dr. Ouda holds the position of Associate Professor in the Department of Electrical and Computer Engineering at Western University, where he has been teaching and conducting research for more than 20 years. As a professional engineer, he brings a wealth of practical knowledge to his academic role.

Research Focus

Dr. Ouda's research interests lie in the field of information security, with particular emphasis on:

He leads the Information and Computer Networks Security (iCNS) Research Laboratory at Western University, overseeing cutting-edge research in these areas.

Industry Experience

Prior to his academic career, Dr. Ouda spent over 14 years in the software industry, gaining extensive experience in various aspects of software development. His professional background includes:

This rich industrial experience allows Dr. Ouda to bridge the gap between academic theory and real-world practice, providing students with valuable insights into the day-to-day work of software engineers—an aspect that can be challenging to convey in a traditional classroom setting. Dr. Ouda's unique combination of academic expertise and industry knowledge makes him a valuable asset to both the research community and his students at Western University.

Education

Ph.D. Degree
Period:	September 2000 to December 2004
Institution:	University of Western Ontario
Discipline:	Computer Science
Location:	London, Ontario, Canada
Thesis:	Digital Watermarking Techniques For Image Security and Hidden Communications
Supervisor:	Dr. Mahmoud R. El-Sakka
Research Focus:	Digital Watermarking, Steganography and Steganalysis, Image Processing and coding

Master's of Computer Science
Period:	September 1989 to August 1993
Institution:	Ain Shams University
Discipline:	Pure Mathematics and Computer Science
Location:	Cairo, Egypt
Thesis:	On Public-key Encryption
Supervisor:	Dr. Fayed Faeq Ghaleb
Research Focus:	Cryptography, Number Theory

Bachelor's of Computer Science
Period:	September 1982 to May 1986
Institution:	Ain Shams University
Discipline:	Pure Mathematics and Computer Science
Location:	Cairo, Egypt
Grade:	96.80% (with the highest honour)

Experience

Dr. Abdelkader Ouda brings over three decades of extensive experience in academia, software engineering, and project management, demonstrating a strong commitment to advancing education, research, and practical applications in engineering and computing. Currently serving as an Associate Professor in Electrical and Computer Engineering at Western University since 2019, Dr. Ouda is deeply involved in research, teaching, and service. He also designed and administers the CEAMS application, a software system that facilitates outcomes-based assessment and continuous program improvement for Canadian engineering universities, playing a pivotal role in accreditation processes.

Previously, Dr. Ouda held several leadership and advisory roles at Western University. From 2015 to 2021, he served as the Director of the Software Engineering Program, overseeing curriculum development and program management. Concurrently, he acted as an Academic Counselor from 2011 to 2021, advising undergraduate students in software engineering on academic planning and success strategies while maintaining a focus on professional integrity and confidentiality. His tenure as an Assistant Professor from 2006 to 2019 further highlights his dedication to education and research.

Dr. Ouda’s professional experience extends beyond academia into industry-focused software development and project management. As a Project Manager and IT Specialist Advisor at Western University from 2012 to 2018, he led multiple full-stack development projects, including the Self Start Body Smart online physiotherapy clinic and a comprehensive student admission system. These projects utilized cutting-edge web technologies such as Node.js, MongoDB, Angular, and Ember.js, showcasing his expertise in modern software engineering practices. Earlier in his career, he managed industry-sponsored projects like the Fire-Alert operational management system and collaborated with Uniiverse Collaborative Lifestyle Inc. on innovative application extensions.

His international experience includes serving as a Software Project Manager for the Naturalization and Residence Department in Al-Ain City, UAE (1996–1999), where he developed an operational management system integrating client/server architecture across multiple facilities. Prior to this role, he worked as a Software Engineer at UAE University’s Information Technology Services (1988–1995), contributing to various IT projects in roles ranging from programmer to senior software analyst.

Dr. Ouda’s career reflects a rich blend of academic leadership, technical expertise, and industry collaboration. His ability to bridge theoretical research with practical applications has had a lasting impact on both educational institutions and industry partners.

Research

Dr. Abdelkader Ouda’s research spans a diverse array of topics within the fields of cybersecurity, data analytics, machine learning, and advanced computing systems, with a strong focus on innovative solutions for real-world challenges in modern digital environments.

A significant portion of his work addresses security concerns in distributed computing systems. For example, he developed a mutual Authentication and Key Agreement protocol tailored for hybrid edge–fog–cloud architectures enhanced by 5G networks. This protocol improves security while reducing computational and transmission costs compared to existing alternatives. Similarly, he proposed a lightweight wireless meter-bus (wM-Bus) protocol for IoT devices that leverages the Noise Protocol Framework to optimize energy efficiency without compromising security, extending device lifetimes significantly.

In the domain of user authentication, Dr. Ouda has explored novel approaches such as smartphone-integrated biometric systems using gait cycle analysis and reinforcement learning-based continuous authentication systems relying on behavioral biometrics like keystroke dynamics. These systems enhance security by providing real-time or session-long user verification. He also introduced an Autonomous Inquiry-Based Authentication Chatbot that dynamically generates personalized questions based on recent user activity, adding an adaptive layer to multi-factor authentication.

Dr. Ouda’s contributions to data analytics include the development of an Algorithm-Based Data Generation (ADG) Engine to synthesize behavioral datasets in contexts where real-world data are sparse or unavailable. This engine generates realistic normal and abnormal data patterns, facilitating anomaly detection and analytics in secure or specialized environments. Additionally, he conducted a performance benchmark comparing PostgreSQL and MySQL databases, demonstrating PostgreSQL's superior efficiency for continuous authentication systems requiring low latency and robust concurrent processing.

In intra-domain communication security, Dr. Ouda introduced HSM4SSL, a comprehensive solution leveraging hardware security modules (HSMs) to enhance the Secure Socket Layer (SSL) protocol for intra-domain environments. This approach outperformed existing solutions in terms of request handling and latency while providing robust cryptographic operations.

Beyond security-focused research, Dr. Ouda has contributed to advancements in machine translation and big data management. He optimized machine translation models for translating technical patents from English to Japanese, achieving high-quality results through domain-specific preprocessing and fine-tuning techniques. He also conducted a thorough review of data-lake architectures, identifying trends and challenges while distinguishing them from data warehouses.

Overall, Dr. Abdelkader Ouda’s research demonstrates a commitment to addressing pressing technological challenges with innovative methodologies that balance efficiency, security, and practicality across a range of applications in modern computing systems.

Teaching

2

ES 036 - Programming Fundamentals for Engineers

(Fall 2006, 2007)

Designing, implementing and testing computer programs using a modern object-oriented language such as C++ to fulfill given specifications for small problems using sound engineering principles and processes. Awareness of the engineering aspects of the process of constructing a computer program.

6

ES 1036 - Programming Fundamentals for Engineers

(Fall 2019, 2020, 2021, 2022, 2023, 2024)

Designing, implementing and testing computer programs using Java and MATLAB to fulfill given specifications for small problems using sound engineering principles and processes. Awareness of the engineering aspects of the process of constructing a computer program.

15

SE 2203 - Software Design

(Winter 2011, 2012, 2013, 2014, 2015, Fall 2015, 2016, 2017, 2018, Winter 2020, 2021, 2022, 2023, 2024, 2025)

Object Oriented Design (OOD) using the Unified Modeling Language. Importance of the design process in the software life cycle. Review of traditional software design methods leading into fundamental OOD principles and practices. Reusability, use of tool sets and standards are stressed. Brief coverage of user-interface design, real-time and distributed systems, architectural design.

3

SE 2205 - Algorithms & Data Structure for Object-Oriented Design

(Winter 2007, 2008, Winter 2018)

Survey of important computer algorithms and related data structures used in object-oriented software engineering. Design, performance analysis and implementation of such algorithms, stressing their practical use and performance certification of large software applications. Understand how to "seal" designs to guarantee performance goals and insure that all error conditions are caught.

5

SE 3310 - Theoretical Foundations of Software Engineering

(Winter 2007, 2008, 2009, 2010, 2011)

An investigation into the theoretical foundations of Software Engineering including automata theory, computability, analysis of algorithms and the application of formal specification methods to software specification.

7

SE 3313 - Operating Systems for Software Engineering

(Fall 2006, 2007, 2008, 2009, 2010, 2011, 2012)

Theory and construction of operating systems, including real-time and embedded systems aspect from an engineering point of view, stressing performance measurement and metrics. Quality of Service issues leading to certification that an operating system will satisfy hard real-time constraints.

3

SE 314 - Design and Implementation of Computer Networks

(Winter 2007, 2008, 2009)

Design, configuration, and maintenance of switches, LANs, and VLANs leading to a thorough understanding of the real-world internetworking. At the completion of this, the student is well-prepared to write the Cisco CCNA Certification Examination.

12

SE 3314 - Computer Networks Applications

(Winter 2010, 2011, 2012, 2013, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022)

This course examines and introduces advanced concepts in computer network and data communications. Topics include mobile and wireless data communications, multimedia networking, network management, distributed computing and clusters, and peer to peer network applications.

7

SE 3350 - Software Engineering Design I

(Fall 2012, Winter 2013, 2014, 2016, 2017, 2018, 2019)

Design and implementation of a large group project illustrating the design concepts being taught and promoting team interaction in a professional setting.

5

SE 3351 - Software Project and Process Management

(Fall 2006, 2007, 2008, Winter 2010, 2014)

Project Management and Software Process life cycles. Includes detailed analysis of components of each process. Metrics, tools and related standards associated with those components. Integration into a complete software project planning including software effort, scheduling and cost estimation, software quality management, and software risk management.

3

SE 352 - Software Engineering Design Tools

(Winter 2007, 2008, 2009)

System tools (loaders, debuggers, libraries, archivers), survey of programming languages, run-time systems, introduction to parsing (yacc and lex), survey of database technology, Object Oriented languages, special topics.

11

SE 3352 - Software Requirements and Analysis

(Fall 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019)

Requirements includes a feasibility study of the desired systems, elicitations and analysis of user's needs, the creation of a precise description of what the system should and should not do along with any constraints on its operation and implementation, and the validation of this specification by the users.

6

SE 4472 - Information Security

(Fall 2008, 2009, 2010, 2011, 2012, 2013)

This course provides an introduction to the topic of security in the context of computer networks. The goals are to provide students with a foundation allowing them to identify, analyze, and solve network-related security problems in information systems with the emphasis on the engineering aspects of information security.

4

ECE 9610 - Advanced Topics in Information and Communication Security

(Winter 2012, 2013, 2014, 2016)

This course concentrates on the challenges involved in the construction of cryptographic protocols to protect modern computer networks, such as p2p Networks, Service Oriented Network (SON), or Wireless Sensor Network (WSN). Specifically, anonymous p2p protocols and ways for shutting down p2p Botnets will be surveyed and discussed with regard to peer-to-peer networks. For Service Oriented Network, topics in building secure web service-based operations will be addressed. The security goals for wireless communication will be considered in terms of WSN authentication and routing protocols.

Publications

Authentication and Key Agreement Protocol in Hybrid Edge–Fog–Cloud Computing Enhanced by 5G Networks

Future Internet, Volume 16, Issue 6 (June 2024)

Abstract: The Internet of Things (IoT) has revolutionized connected devices, with applications in healthcare, data analytics, and smart cities. For time-sensitive applications, 5G wireless networks provide ultra-reliable low-latency communication (URLLC) and fog computing offloads IoT processing. Integrating 5G and fog computing can address cloud computing’s deficiencies, but security challenges remain, especially in Authentication and Key Agreement aspects due to the distributed and dynamic nature of fog computing.

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This study presents an innovative mutual Authentication and Key Agreement protocol that is specifically tailored to meet the security needs of fog computing in the context of the edge–fog–cloud three-tier architecture, enhanced by the incorporation of the 5G network. This study improves security in the edge–fog–cloud context by introducing a stateless authentication mechanism and conducting a comparative analysis of the proposed protocol with well-known alternatives, such as TLS 1.3, 5G-AKA, and various handover protocols. The suggested approach has a total transmission cost of only 1280 bits in the authentication phase, which is approximately 30% lower than other protocols. In addition, the suggested handover protocol only involves two signaling expenses. The computational cost for handover authentication for the edge user is significantly low, measuring 0.243 ms, which is under 10% of the computing costs of other authentication protocols.

Keywords: fog–cloud computing; fog security; authentication protocols; key agreement protocols

A Secure Lightweight Wireless M-Bus Protocol for IoT: Leveraging the Noise Protocol Framework

ICJECE 2024

Abstract—The escalating demand for secure communication in the Internet of Things (IoT), particularly in energy-sensitive devices such as smart meters, highlights a critical challenge: achieving robust security without excessive energy consumption. While various solutions have been proposed to minimize energy use, many fail to address the unique constraints of the IoT devices effectively. This article introduces an innovative approach by proposing a secure, lightweight wireless meter-bus (wM-Bus) protocol, specifically designed for the stringent resource constraints of the IoT environments.

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By incorporating the noise protocol framework (NPF), our protocol significantly reduces computational and power requirements without compromising security integrity. Through a methodical implementation that spanned five distinct phases, including a comparative analysis with the conventional transport layer security (TLS), our findings are compelling. The NPF, particularly with its NX and XX patterns, dramatically surpasses TLS in performance, extending operational lifetimes to approximately 9 and 7.88 years, respectively, in contrast to the 3.81 years offered by TLS. These results not only demonstrate the superior efficiency of the NPF in the IoT settings but also highlight its potential in striking an optimal balance between security and operational longevity.

Index Terms—Advanced metering infrastructure (AMI), cryptography, Internet of Things (IoT), lightweight, noise protocol framework (NPF), protocol, security, smart metering, wireless meter-bus (wM-Bus).

Enhanced Security Access Control Using Statistical-Based Legitimate or Counterfeit Identification System

Computers, Volume 13, Issue 7 (July 2024)

Abstract: With our increasing reliance on technology, there is a growing demand for efficient and seamless access control systems. Smartphone-centric biometric methods offer a diverse range of potential solutions capable of verifying users and providing an additional layer of security to prevent unauthorized access. To ensure the security and accuracy of smartphone-centric biometric identification, it is crucial that the phone reliably identifies its legitimate owner. Once the legitimate holder has been successfully determined, the phone can effortlessly provide real-time identity verification for various applications.

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To achieve this, we introduce a novel smartphone-integrated detection and control system called Identification: Legitimate or Counterfeit (ILC), which utilizes gait cycle analysis. The ILC system employs the smartphone’s accelerometer sensor, along with advanced statistical methods, to detect the user’s gait pattern, enabling real-time identification of the smartphone owner. This approach relies on statistical analysis of measurements obtained from the accelerometer sensor, specifically, peaks extracted from the X-axis data. Subsequently, the derived feature’s probability distribution function (PDF) is computed and compared to the known user’s PDF. The calculated probability verifies the similarity between the distributions, and a decision is made with 92.18% accuracy based on a predetermined verification threshold.

Keywords: access control systems; identity verification; gait cycle analysis; smartphone sensors.

Continuous Authentication in the Digital Age: An Analysis of Reinforcement Learning and Behavioral Biometrics

Computers, Volume 13, Issue 4 (April 2024)

Abstract: This research article delves into the development of a reinforcement learning (RL)-based continuous authentication system utilizing behavioral biometrics for user identification on computing devices. Keystroke dynamics are employed to capture unique behavioral biometric signatures, while a reward-driven RL model is deployed to authenticate users throughout their sessions. The proposed system augments conventional authentication mechanisms, fortifying them with an additional layer of security to create a robust continuous authentication framework compatible with static authentication systems.

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The methodology entails training an RL model to discern atypical user typing patterns and identify potentially suspicious activities. Each user’s historical data are utilized to train an agent, which undergoes preprocessing to generate episodes for learning purposes. The environment involves the retrieval of observations, which are intentionally perturbed to facilitate learning of nonlinear behaviors. The observation vector encompasses both ongoing and summarized features. A binary and minimalist reward function is employed, with principal component analysis (PCA) utilized for encoding ongoing features, and the double deep Q-network (DDQN) algorithm implemented through a fully connected neural network serving as the policy net. Evaluation results showcase training accuracy and equal error rate (EER) ranging from 94.7% to 100% and 0 to 0.0126, respectively, while test accuracy and EER fall within the range of approximately 81.06% to 93.5% and 0.0323 to 0.11, respectively, for all users as encoder features increase in number. These outcomes are achieved through RL’s iterative refinement of rewards via trial and error, leading to enhanced accuracy over time as more data are processed and incorporated into the system.

Keywords: behavioral biometrics; continuous authentication; keystroke dynamics; Markov decision process (MDP); Q-learning; reinforcement learning (RL); static authentication; user authentication; identification.

Smart Chatbot for User Authentication

Electronics, Volume 11, Issue 23 (December-1 2022)

Abstract: Despite being the most widely used authentication mechanism, password-based authentication is not very secure, being easily guessed or brute-forced. To address this, many systems which especially value security adopt Multi-Factor Authentication (MFA), in which multiple different authentication mechanisms are used concurrently. JitHDA (Just-in-time human dynamics based authentication engine) is a new authentication mechanism which can add another option to MFA capabilities. JitHDA observes human behaviour and human dynamics to gather up to date information on the user from which authentication questions can be dynamically generated.

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This paper proposes a system that implements JitHDA, which we call Autonomous Inquiry-based Authentication Chatbot (AIAC). AIAC uses anomalous events gathered from a user’s recent activity to create personalized questions for the user to answer, and is designed to improve its own capabilities over time using neural networks trained on data gathered during authentication sessions. Due to using the user’s recent activity, they will be easy for the authentic user to answer and hard for a fraudulent user to guess, and as the user’s recent history updates between authentication sessions new questions will be dynamically generated to replace old ones. We intend to show in this paper that AIAC is a viable implementation of JitHDA.

Keywords: bmachine learning; authentication; natural language understanding; big data; chatbots.

Algorithm-Based Data Generation (ADG) Engine for Dual-Mode User Behavioral Data Analytics

Information, Volume 15, Issue 3 (March 2024)

Abstract: The increasing significance of data analytics in modern information analysis is underpinned by vast amounts of user data. However, it is only feasible to amass sufficient data for various tasks in specific data-gathering contexts that either have limited security information or are associated with older applications. There are numerous scenarios where a domain is too new, too specialized, too secure, or data are too sparsely available to adequately support data analytics endeavors. In such cases, synthetic data generation becomes necessary to facilitate further analysis.

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To address this challenge, we have developed an Algorithm-based Data Generation (ADG) Engine that enables data generation without the need for initial data, relying instead on user behavior patterns, including both normal and abnormal behavior. The ADG Engine uses a structured database system to keep track of users across different types of activity. It then uses all of this information to make the generated data as real as possible. Our efforts are particularly focused on data analytics, achieved by generating abnormalities within the data and allowing users to customize the generation of normal and abnormal data ratios. In situations where obtaining additional data through conventional means would be impractical or impossible, especially in the case of specific characteristics like anomaly percentages, algorithmically generated datasets provide a viable alternative. In this paper, we introduce the ADG Engine, which can create coherent datasets for multiple users engaged in different activities and across various platforms, entirely from scratch. The ADG Engine incorporates normal and abnormal ratios within each data platform through the application of core algorithms for time-based and numeric-based anomaly generation. The resulting abnormal percentage is compared against the expected values and ranges from 0.13 to 0.17 abnormal data instances in each column. Along with the normal/abnormal ratio, the results strongly suggest that the ADG Engine has successfully completed its primary task.

Keywords: data generation; anomaly data; user behavior generation; data analytics.

HSM4SSL: Leveraging HSMs for Enhanced Intra-Domain Security

Future Internet, Volume 16, Issue 5 (May 2024)

Abstract: In a world where digitization is rapidly advancing, the security and privacy of intra-domain communication within organizations are of critical concern. The imperative to secure communication channels among physical systems has led to the deployment of various security approaches aimed at fortifying networking protocols. However, these approaches have typically been designed to secure protocols individually, lacking a holistic perspective on the broader challenge of intra-domain communication security. This omission raises fundamental concerns about the safety and integrity of intra-domain environments, where all communication occurs within a single domain.

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As a result, this paper introduces HSM4SSL, a comprehensive solution designed to address the evolving challenges of secure data transmission in intra-domain environments. By leveraging hardware security modules (HSMs), HSM4SSL aims to utilize the Secure Socket Layer (SSL) protocol within intra-domain environments to ensure data confidentiality, authentication, and integrity. In addition, solutions proposed by academic researchers and in the industry have not addressed the issue in a holistic and integrative manner, as they only apply to specific types of environments or servers and do not utilize all cryptographic operations for robust security. Thus, HSM4SSL bridges this gap by offering a unified and comprehensive solution that includes certificate management, key management practices, and various security services. HSM4SSL comprises three layers to provide a standardized interaction between software applications and HSMs. A performance evaluation was conducted comparing HSM4SSL with a benchmark tool for cryptographic operations. The results indicate that HSM4SSL achieved 33% higher requests per second (RPS) compared to OpenSSL, along with a 13% lower latency rate. Additionally, HSM4SSL efficiently utilizes CPU and network resources, outperforming OpenSSL in various aspects. These findings highlight the effectiveness and reliability of HSM4SSL in providing secure communication within intra-domain environments, thus addressing the pressing need for enhanced security mechanisms.

Keywords: intra-domain; secure socket layer; transport layer security; public-key certificates; hardware security modules.

A Performance Benchmark for the PostgreSQL and MySQL Databases

Future Internet, Volume 16, Issue 10 (October 2024)

Abstract: This study highlights the necessity for efficient database management in continuous authentication systems, which rely on large-scale behavioral biometric data such as keystroke patterns. A benchmarking framework was developed to evaluate the PostgreSQL and MySQL databases, minimizing repetitive coding through configurable functions and variables. The methodology involved experiments assessing select and insert queries under primary and complex conditions, simulating real-world scenarios. Our quantified results show PostgreSQL’s superior performance in select operations.

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In primary tests, PostgreSQL’s execution time for 1 million records ranged from 0.6 ms to 0.8 ms, while MySQL’s ranged from 9 ms to 12 ms, indicating that PostgreSQL is about 13 times faster. For select queries with a where clause, PostgreSQL required 0.09 ms to 0.13 ms compared to MySQL’s 0.9 ms to 1 ms, making it roughly 9 times more efficient. Insert operations were similar, with PostgreSQL at 0.0007 ms to 0.0014 ms and MySQL at 0.0010 ms to 0.0030 ms. In complex experiments with simultaneous operations, PostgreSQL maintained stable performance (0.7 ms to 0.9 ms for select queries during inserts), while MySQL’s performance degraded significantly (7 ms to 13 ms). These findings underscore PostgreSQL’s suitability for environments requiring low data latency and robust concurrent processing capabilities, making it ideal for continuous authentication systems.

Keywords: benchmark; postgreSQL; mySQL; database; biometrics.

An Optimized Approach to Translate Technical Patents from English to Japanese Using Machine Translation Models

Appl. Sci., Volume 13, Issue 12 (June-2 2023)

Abstract: This paper addresses the challenges associated with machine translation of patents from English to Japanese. This translation poses unique difficulties due to their legal nature, distinguishing them from general Japanese-to-English translation. Furthermore, the complexities inherent in the Japanese language add an additional layer of intricacy to the development of effective translation models within this specific domain. Our approach encompasses a range of essential steps, including preprocessing, data preparation, expert feedback acquisition, and linguistic analysis.

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These steps collectively contribute to the enhancement of machine learning model performance. The experimental results, presented in this study, evaluate three prominent alternatives considered for the final step of the transformer model. Through our methodology, which incorporates a modified version of NLP-Model-III, we achieved outstanding performance for the given problem, attaining an impressive BLEU score of 46.8. Furthermore, significant improvements of up to three points on the BLEU score were observed through hyperparameter fine-tuning. This research also involved the development of a novel dataset consisting of meticulously collected patent document data. The findings of this study provide valuable insights and contribute to the advancement of Japanese patent translation methodologies.

Keywords: machine translation; technical patents; natural language processing; translation quality; cross-lingual information retrieval; corpus-based translation; domain adaptation; language model fine-tuning; neural machine translation.

Data Lakes: A Survey of Concepts and Architectures

Computers, Volume 13, Issue 7 (July 2024)

Abstract: This paper presents a comprehensive literature review on the evolution of data-lake technology, with a particular focus on data-lake architectures. By systematically examining the existing body of research, we identify and classify the major types of data-lake architectures that have been proposed and implemented over time. The review highlights key trends in the development of data-lake architectures, identifies the primary challenges faced in their implementation, and discusses future directions for research and practice in this rapidly evolving field.

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We have developed diagrammatic representations to highlight the evolution of various architectures. These diagrams use consistent notations across all architectures to further enhance the comparative analysis of the different architectural components. We also explore the differences between data warehouses and data lakes. Our findings provide valuable insights for researchers and practitioners seeking to understand the current state of data-lake technology and its potential future trajectory.

Keywords: big data; hadoop; data lake; data warehouse; data lakehouse; data management; schema; internet of things.

1. Iman IM Abu Sulayman and Abdelkader Ouda. Data analytics methods for anomaly detection: Evolution and recommendations. In 2018 International Conference on Signal Processing and Information Security (ICSPIS), pages 1–4. IEEE, 2018.


2. Wafaa Anani, Abdelkader Ouda, and Ali Hamou. A survey of wireless communications for IoT echo-systems. In 2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE), pages 1–6. IEEE, 2019.


3. Osama Ali-Ozkan and Abdelkader Ouda. Key-based reversible data masking for business intelligence healthcare analytics platforms. In 2019 International Symposium on Networks, Computers and Communications (ISNCC), pages 1–6. IEEE, 2019.


4. Iman IM Abu Sulayman and Abdelkader Ouda. User modeling via anomaly detection techniques for user authentication. In 2019 IEEE 10th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), pages 0169–0176. IEEE, 2019.


5. Iman IM Abu Sulayman and Abdelkader Ouda. Human trait analysis via machine learning techniques for user authentication. In 2020 International Symposium on Networks, Computers and Communications (ISNCC), pages 1–10. IEEE, 2020.


6. Iman IM Abu Sulayman and Abdelkader Ouda. Designing security user profiles via anomaly detection for user authentication. In 2020 International Symposium on Networks, Computers and Communications (ISNCC), pages 1–6. IEEE, 2020.


7. Peter Voege and Abdelkader Ouda. A study on natural language chatbot-based authentication systems. In 2021 International Symposium on Networks, Computers and Communications (ISNCC), pages 1–4. IEEE, 2021.


8. Iman IM Abu Sulayman, Rongji He, Marlin Manka, Andrew Ning, and Abdelkader Ouda. Lifi/wifi authentication and handover protocols: Survey, evaluation, and recommendation. In 2021 International Symposium on Networks, Computers and Communications (ISNCC), pages 1–6. IEEE, 2021.


9. Wafaa Anani and Abdelkader Ouda. Demystifying wireless technologies for best uses in IoT echo-systems. In 2022 2nd International Conference of Smart Systems and Emerging Technologies (SMARTTECH), pages 238–245. IEEE, 2022.


10. Maimoonah Ahmed, Abdelkader Ouda, and Mohamed Abusharkh. An analysis of the effects of hyperparameters on the performance of simulated autonomous vehicles. In 2022 International Telecommunications Conference (ITC-Egypt), pages 1–5. IEEE, 2022.


11. Peter Voege and Abdelkader Ouda. An innovative multi-factor authentication approach. In 2022 International Symposium on Networks, Computers and Communications (ISNCC), pages 1–6. IEEE, 2022.


12. Priya Bansal and Abdelkader Ouda. Study on integration of fastapi and machine learning for continuous authentication of behavioral biometrics. In 2022 International Symposium on Networks, Computers and Communications (ISNCC), pages 1–6. IEEE, 2022.


13. Sanket Salunke, Abdelkader Ouda, and Jonathan Gagne. Transfer learning for behavioral biometrics-based continuous user authentication. In 2022 International Symposium on Networks, Computers and Communications (ISNCC), pages 1–6. IEEE, 2022.


14. Iman IM Abu Sulayman and Abdelkader Ouda. Real-time data generation and anomaly detection for security user profiles. In 2022 International Symposium on Networks, Computers and Communications (ISNCC), pages 1–6. IEEE, 2022.


15. Wafaa Anani and Abdelkader Ouda. Wireless meter bus: Secure remote metering within the iot smart grid. In 2022 International Symposium on Networks, Computers and Communications (ISNCC), pages 1–6. IEEE, 2022.


16. Sergio A Salinas, Mohamed Ahmed TA Elgalhud, Luke Tambakis, Sanket V Salunke, Kshitija Patel, Hamada Ghenniwa, Abdelkader Ouda, Kenneth McIsaac, Katarina Grolinger, and Ana Luisa Trejos. Comparison of machine learning techniques for activities of daily living classification with electromyographic data. In 2022 International Conference on Rehabilitation Robotics (ICORR), pages 1–6. IEEE, 2022.


17. Yazan Aref and Abdelkader Ouda. Autonomous vehicle cyber-attacks classification framework. In 2023 15th I nternational Conference on COMmunication Systems & NETworkS (COMSNETS), pages 373–377. IEEE, 2023.


18. Sanket Vilas Salunke and Abdelkader Ouda. Ensemble learning to enhance continuous user authentication for real world environments. In 2023 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom), pages 102–108. IEEE, 2023.


19. Iman I. M. Abu Sulayman, Peter Voege, and Abdelkader Ouda. Algorithm-based data generation (adg) engine for dual-mode user behavioral data analytics. Information, 15(3), 2024.


20. Yazan Aref and Abdelkader Ouda. Still computers networking is less secure than it should be, causes and solution. In 2023 International Symposium on Networks, Computers and Communications (ISNCC), pages 1–8. IEEE, 2023.