Ammar Al-Dallal - Academia.edu (original) (raw)

Papers by Ammar Al-Dallal

Studies in systems, decision and control, 2024

2022 Thirteenth International Conference on Ubiquitous and Future Networks (ICUFN)

2018 4th International Conference on Frontiers of Signal Processing (ICFSP), 2018

Modernization and commercialization of life lead to an unhealthy Lifestyle that results in increa... more Modernization and commercialization of life lead to an unhealthy Lifestyle that results in increasing non-communicable diseases such as heart diseases and diabetes. Non-communicable diseases have direct impact on inaction, inactivity, and idleness of people. Heart diseases and diabetes are two of the most dangerous killers affecting the society. This research aims to produce application software to be used by doctors and other medical practitioners to predict the occurrence or recurrence of non-communicable diseases (NCDs). The predictive data-mining model was applied in this project. Patients records obtained from Bahrain Defense Force Hospital were used to examine the proposed software application. This application was executed and tested by the actual practitioner in the mentioned hospital. The results showed that the prediction system is capable of predicting NCDs’ diseases effectively, efficiently and most importantly, instantly. This application is capable of helping a physician in making proper decisions towards patient health risks.

Increasing the growth rates of websites' number has led to the challenge of assisting Web custome... more Increasing the growth rates of websites' number has led to the challenge of assisting Web customers in finding appropriate details from the Internet using an intelligent search engine. Information retrieval (IR) is an essential and useful strategy for Web users; thus, different strategies and techniques are designed for such purpose. Currently, the focus on the usefulness of Artificial Intelligence (AI) has been improved with IR. One AI area is Evolutionary Computation (EC), which is based on designs of natural selection. A traditional and important strategy in EC is Genetic Algorithm (GA); this paper adopts the GA technique to enhance the retrieval of HTML documents. This improvement is obtained by creating a modern evaluation function and applying a hybrid crossover operator. The proposed evaluation function is based on term proximity, keyword probability within the document, and HTML tag weight query. Experimental results are compared with two well known evaluation function functions applied in IR domain which are Okapi-BM25 and Bayesian interface network model. The results demonstrate a good level of enhancement to the recall and precision. In addition, the documents retrieved by the proposed system were more accurate and relevant to the queries than that retrieved by other models.

Symmetry

The increased adoption of cloud computing resources produces major loopholes in cloud computing f... more The increased adoption of cloud computing resources produces major loopholes in cloud computing for cybersecurity attacks. An intrusion detection system (IDS) is one of the vital defenses against threats and attacks to cloud computing. Current IDSs encounter two challenges, namely, low accuracy and a high false alarm rate. Due to these challenges, additional efforts are required by network experts to respond to abnormal traffic alerts. To improve IDS efficiency in detecting abnormal network traffic, this work develops an IDS using a recurrent neural network based on gated recurrent units (GRUs) and improved long short-term memory (LSTM) through a computing unit to form Cu-LSTMGRU. The proposed system efficiently classifies the network flow instances as benign or malevolent. This system is examined using the most up-to-date dataset CICIDS2018. To further optimize computational complexity, the dataset is optimized through the Pearson correlation feature selection algorithm. The propos...

Symmetry

As cyber-attacks become remarkably sophisticated, effective Intrusion Detection Systems (IDSs) ar... more As cyber-attacks become remarkably sophisticated, effective Intrusion Detection Systems (IDSs) are needed to monitor computer resources and to provide alerts regarding unusual or suspicious behavior. Despite using several machine learning (ML) and data mining methods to achieve high effectiveness, these systems have not proven ideal. Current intrusion detection algorithms suffer from high dimensionality, redundancy, meaningless data, high error rate, false alarm rate, and false-negative rate. This paper proposes a novel Ensemble Learning (EL) algorithm-based network IDS model. The efficient feature selection is attained via a hybrid of Correlation Feature Selection coupled with Forest Panelized Attributes (CFS–FPA). The improved intrusion detection involves exploiting AdaBoosting and bagging ensemble learning algorithms to modify four classifiers: Support Vector Machine, Random Forest, Naïve Bayes, and K-Nearest Neighbor. These four enhanced classifiers have been applied first as Ad...

Sensors

In a non-orthogonal multiple access (NOMA) system, the successive interference cancellation (SIC)... more In a non-orthogonal multiple access (NOMA) system, the successive interference cancellation (SIC) procedure is typically employed at the receiver side, where several user’s signals are decoded in a subsequent manner. Fading channels may disperse the transmitted signal and originate dependencies among its samples, which may affect the channel estimation procedure and consequently affect the SIC process and signal detection accuracy. In this work, the impact of Deep Neural Network (DNN) in explicitly estimating the channel coefficients for each user in NOMA cell is investigated in both Rayleigh and Rician fading channels. The proposed approach integrates the Long Short-Term Memory (LSTM) network into the NOMA system where this LSTM network is utilized to predict the channel coefficients. DNN is trained using different channel statistics and then utilized to predict the desired channel parameters that will be exploited by the receiver to retrieve the original data. Furthermore, this wo...

Symmetry, 2021

When adopting cloud computing, cybersecurity needs to be applied to detect and protect against ma... more When adopting cloud computing, cybersecurity needs to be applied to detect and protect against malicious intruders to improve the organization’s capability against cyberattacks. Having network intrusion detection with zero false alarm is a challenge. This is due to the asymmetry between informative features and irrelevant and redundant features of the dataset. In this work, a novel machine learning based hybrid intrusion detection system is proposed. It combined support vector machine (SVM) and genetic algorithm (GA) methodologies with an innovative fitness function developed to evaluate system accuracy. This system was examined using the CICIDS2017 dataset, which contains normal and most up-to-date common attacks. Both algorithms, GA and SVM, were executed in parallel to achieve two optimal objectives simultaneously: obtaining the best subset of features with maximum accuracy. In this scenario, an SVM was employed using different values of hyperparameters of the kernel function, ga...

Advances in Science, Technology and Engineering Systems Journal, 2019

Data mining is recognized as an effective technique for extracting and retrieving valuable inform... more Data mining is recognized as an effective technique for extracting and retrieving valuable information or decision from the vast available data. Because of the nature of the functionality of medical centers and hospitals, their data centers contain a collection of valuable information about their patients. By properly processing these data, different applications can be developed to utilize them. These applications could participate in predicting and diagnosing particular diseases. Two prime diseases realized to impact the overall health of society are heart diseases and diabetes. The presented work intends to develop and test a software application that helps doctors and practitioners predict the emergence of noncommunicable diseases (NCDs) such as diabetes and heart diseases. The application applies the predictive data mining model to the medical records which are collected from the Bahrain Defense Force Hospital (BDFH). The BDFH doctors evaluated the application and executed it on actual patients. The results obtained are accurately matching the expectation of doctors in BDFH. All kinds of risks are categorized appropriately according to the defined categories. As a conclusion, this application can help doctors in making proper decisions toward patient health risks. In addition, data mining is more supportive for the health sector and is essential for exploring the knowledge to be used in the health care sector.

World Journal of Entrepreneurship, Management and Sustainable Development, 2018

Purpose Information security management (ISM) is proving to be an important topic in the modern w... more Purpose Information security management (ISM) is proving to be an important topic in the modern world; in environments that will rely a great deal on digital technologies, such as smart cities, ISM research is of high importance and needs to be well analysed. The paper aims to discuss these issues. Design/methodology/approach This paper indicates the criticality of ISM for smart cities through the literature, then focusses on top organisational factors influencing ISM in smart city organisations, which are embraced and justified from the literature. Findings This paper highlights the need for more research around ISM in the context of smart city organisations, also ISM-related organisational factors that are expected to most influence smart city organisational performance. Research limitations/implications This paper is proposed to influence more research in the area of ISM for smart cities among the research community. Additional research is also expected to further validate and ex...

KnE Social Sciences, 2019

Most of the healthcare organizations and medical research institutions store their patient’s data... more Most of the healthcare organizations and medical research institutions store their patient’s data digitally for future references and for planning their future treatments. This heterogeneous medical dataset is very difficult to analyze due to its complexity and volume of data, in addition to having missing values and noise which makes this mining a tedious task. Efficient classification of medical dataset is a major data mining problem then and now. Diagnosis, prediction of diseases and the precision of results can be improved if relationships and patterns from these complex medical datasets are extracted efficiently. This paper analyses some of the major classification algorithms such as C4.5 ( J48), SMO, Naïve Bayes, KNN Classification algorithms and Random Forest and the performance of these algorithms are compared using WEKA. Performance evaluation of these algorithms is based on Accuracy, Sensitivity and Specificity and Error rate. The medical data set used in this study are He...

International Journal of Artificial Life Research, Apr 1, 2012

Increasing the growth rates of websites' number has led to the challenge of assisting Web custome... more Increasing the growth rates of websites' number has led to the challenge of assisting Web customers in finding appropriate details from the Internet using an intelligent search engine. Information retrieval (IR) is an essential and useful strategy for Web users; thus, different strategies and techniques are designed for such purpose. Currently, the focus on the usefulness of Artificial Intelligence (AI) has been improved with IR. One AI area is Evolutionary Computation (EC), which is based on designs of natural selection. A traditional and important strategy in EC is Genetic Algorithm (GA); this paper adopts the GA technique to enhance the retrieval of HTML documents. This improvement is obtained by creating a modern evaluation function and applying a hybrid crossover operator. The proposed evaluation function is based on term proximity, keyword probability within the document, and HTML tag weight query. Experimental results are compared with two well known evaluation function functions applied in IR domain which are Okapi-BM25 and Bayesian interface network model. The results demonstrate a good level of enhancement to the recall and precision. In addition, the documents retrieved by the proposed system were more accurate and relevant to the queries than that retrieved by other models.

Proceedings of the 7th International Joint Conference on Computational Intelligence, 2015

This paper proposes a new solution for Traveling Salesman Problem (TSP) using genetic algorithm. ... more This paper proposes a new solution for Traveling Salesman Problem (TSP) using genetic algorithm. A combinational crossover technique is employed in the search for optimal or near-optimal TSP solutions. It is based upon chromosomes that utilise the concept of heritable building blocks. Moreover, generation of a single offspring, rather than two, per pair of parents, allows the system to generate high performance chromosomes. This solution is compared with the well performing Ordered Crossover (OX). Experimental results demonstrate that, due to the well structured crossover technique, has enhanced performance.

2009 Second International Conference on Developments in eSystems Engineering, 2009

... Ammar Al-Dallal School of Information Systems Computing and Mathematics Brunel University, UK... more ... Ammar Al-Dallal School of Information Systems Computing and Mathematics Brunel University, UK Ammar.AlDallal@brunel.ac.uk ... due to its sim-plicity and its capability as a powerful search mechanism can be employed to make several important contributions to the field of IR. ...

International Journal of Applied Metaheuristic Computing, 2013

This paper proposes two IR approaches; the first is IR with GA, which is a GA-based IR approach. ... more This paper proposes two IR approaches; the first is IR with GA, which is a GA-based IR approach. This approach introduces modified GA operators that allow IR with GA to achieve high performance. The second IR model is IR without GA, which is based on traditional IR approach. Both enhance the precision and recall of the web search by improving the document representation where an enhanced inverted index is developed for this purpose. Moreover, these two models use the same proposed evaluation function for measuring the document relativity to the user query. A number of experiments were conducted to compare the performance of the two suggested approaches with existing techniques. The two suggested approaches were then compared experimentally with another two techniques of classical IR namely Okapi-BM25 fitness function and Bayesian inference network model from documents quality of retrieval perspective. The obtained results demonstrate a good level of enhancement to the recall and pre...

Exhibition, 2009

... 1 School of Information Systems Computing and Mathematics,Brunel University,UK Email:Ammar.Al... more ... 1 School of Information Systems Computing and Mathematics,Brunel University,UK Email:Ammar.AlDallal@brunel.ac.uk 2 College of Information ... and its capability as a powerful search mechanisms, can be employed to make several important contribution to the field of IR. ...

Studies in systems, decision and control, 2024

2022 Thirteenth International Conference on Ubiquitous and Future Networks (ICUFN)

2018 4th International Conference on Frontiers of Signal Processing (ICFSP), 2018

Modernization and commercialization of life lead to an unhealthy Lifestyle that results in increa... more Modernization and commercialization of life lead to an unhealthy Lifestyle that results in increasing non-communicable diseases such as heart diseases and diabetes. Non-communicable diseases have direct impact on inaction, inactivity, and idleness of people. Heart diseases and diabetes are two of the most dangerous killers affecting the society. This research aims to produce application software to be used by doctors and other medical practitioners to predict the occurrence or recurrence of non-communicable diseases (NCDs). The predictive data-mining model was applied in this project. Patients records obtained from Bahrain Defense Force Hospital were used to examine the proposed software application. This application was executed and tested by the actual practitioner in the mentioned hospital. The results showed that the prediction system is capable of predicting NCDs’ diseases effectively, efficiently and most importantly, instantly. This application is capable of helping a physician in making proper decisions towards patient health risks.

Increasing the growth rates of websites' number has led to the challenge of assisting Web custome... more Increasing the growth rates of websites' number has led to the challenge of assisting Web customers in finding appropriate details from the Internet using an intelligent search engine. Information retrieval (IR) is an essential and useful strategy for Web users; thus, different strategies and techniques are designed for such purpose. Currently, the focus on the usefulness of Artificial Intelligence (AI) has been improved with IR. One AI area is Evolutionary Computation (EC), which is based on designs of natural selection. A traditional and important strategy in EC is Genetic Algorithm (GA); this paper adopts the GA technique to enhance the retrieval of HTML documents. This improvement is obtained by creating a modern evaluation function and applying a hybrid crossover operator. The proposed evaluation function is based on term proximity, keyword probability within the document, and HTML tag weight query. Experimental results are compared with two well known evaluation function functions applied in IR domain which are Okapi-BM25 and Bayesian interface network model. The results demonstrate a good level of enhancement to the recall and precision. In addition, the documents retrieved by the proposed system were more accurate and relevant to the queries than that retrieved by other models.

Symmetry

The increased adoption of cloud computing resources produces major loopholes in cloud computing f... more The increased adoption of cloud computing resources produces major loopholes in cloud computing for cybersecurity attacks. An intrusion detection system (IDS) is one of the vital defenses against threats and attacks to cloud computing. Current IDSs encounter two challenges, namely, low accuracy and a high false alarm rate. Due to these challenges, additional efforts are required by network experts to respond to abnormal traffic alerts. To improve IDS efficiency in detecting abnormal network traffic, this work develops an IDS using a recurrent neural network based on gated recurrent units (GRUs) and improved long short-term memory (LSTM) through a computing unit to form Cu-LSTMGRU. The proposed system efficiently classifies the network flow instances as benign or malevolent. This system is examined using the most up-to-date dataset CICIDS2018. To further optimize computational complexity, the dataset is optimized through the Pearson correlation feature selection algorithm. The propos...

Symmetry

As cyber-attacks become remarkably sophisticated, effective Intrusion Detection Systems (IDSs) ar... more As cyber-attacks become remarkably sophisticated, effective Intrusion Detection Systems (IDSs) are needed to monitor computer resources and to provide alerts regarding unusual or suspicious behavior. Despite using several machine learning (ML) and data mining methods to achieve high effectiveness, these systems have not proven ideal. Current intrusion detection algorithms suffer from high dimensionality, redundancy, meaningless data, high error rate, false alarm rate, and false-negative rate. This paper proposes a novel Ensemble Learning (EL) algorithm-based network IDS model. The efficient feature selection is attained via a hybrid of Correlation Feature Selection coupled with Forest Panelized Attributes (CFS–FPA). The improved intrusion detection involves exploiting AdaBoosting and bagging ensemble learning algorithms to modify four classifiers: Support Vector Machine, Random Forest, Naïve Bayes, and K-Nearest Neighbor. These four enhanced classifiers have been applied first as Ad...

Sensors

In a non-orthogonal multiple access (NOMA) system, the successive interference cancellation (SIC)... more In a non-orthogonal multiple access (NOMA) system, the successive interference cancellation (SIC) procedure is typically employed at the receiver side, where several user’s signals are decoded in a subsequent manner. Fading channels may disperse the transmitted signal and originate dependencies among its samples, which may affect the channel estimation procedure and consequently affect the SIC process and signal detection accuracy. In this work, the impact of Deep Neural Network (DNN) in explicitly estimating the channel coefficients for each user in NOMA cell is investigated in both Rayleigh and Rician fading channels. The proposed approach integrates the Long Short-Term Memory (LSTM) network into the NOMA system where this LSTM network is utilized to predict the channel coefficients. DNN is trained using different channel statistics and then utilized to predict the desired channel parameters that will be exploited by the receiver to retrieve the original data. Furthermore, this wo...

Symmetry, 2021

When adopting cloud computing, cybersecurity needs to be applied to detect and protect against ma... more When adopting cloud computing, cybersecurity needs to be applied to detect and protect against malicious intruders to improve the organization’s capability against cyberattacks. Having network intrusion detection with zero false alarm is a challenge. This is due to the asymmetry between informative features and irrelevant and redundant features of the dataset. In this work, a novel machine learning based hybrid intrusion detection system is proposed. It combined support vector machine (SVM) and genetic algorithm (GA) methodologies with an innovative fitness function developed to evaluate system accuracy. This system was examined using the CICIDS2017 dataset, which contains normal and most up-to-date common attacks. Both algorithms, GA and SVM, were executed in parallel to achieve two optimal objectives simultaneously: obtaining the best subset of features with maximum accuracy. In this scenario, an SVM was employed using different values of hyperparameters of the kernel function, ga...

Advances in Science, Technology and Engineering Systems Journal, 2019

Data mining is recognized as an effective technique for extracting and retrieving valuable inform... more Data mining is recognized as an effective technique for extracting and retrieving valuable information or decision from the vast available data. Because of the nature of the functionality of medical centers and hospitals, their data centers contain a collection of valuable information about their patients. By properly processing these data, different applications can be developed to utilize them. These applications could participate in predicting and diagnosing particular diseases. Two prime diseases realized to impact the overall health of society are heart diseases and diabetes. The presented work intends to develop and test a software application that helps doctors and practitioners predict the emergence of noncommunicable diseases (NCDs) such as diabetes and heart diseases. The application applies the predictive data mining model to the medical records which are collected from the Bahrain Defense Force Hospital (BDFH). The BDFH doctors evaluated the application and executed it on actual patients. The results obtained are accurately matching the expectation of doctors in BDFH. All kinds of risks are categorized appropriately according to the defined categories. As a conclusion, this application can help doctors in making proper decisions toward patient health risks. In addition, data mining is more supportive for the health sector and is essential for exploring the knowledge to be used in the health care sector.

World Journal of Entrepreneurship, Management and Sustainable Development, 2018

Purpose Information security management (ISM) is proving to be an important topic in the modern w... more Purpose Information security management (ISM) is proving to be an important topic in the modern world; in environments that will rely a great deal on digital technologies, such as smart cities, ISM research is of high importance and needs to be well analysed. The paper aims to discuss these issues. Design/methodology/approach This paper indicates the criticality of ISM for smart cities through the literature, then focusses on top organisational factors influencing ISM in smart city organisations, which are embraced and justified from the literature. Findings This paper highlights the need for more research around ISM in the context of smart city organisations, also ISM-related organisational factors that are expected to most influence smart city organisational performance. Research limitations/implications This paper is proposed to influence more research in the area of ISM for smart cities among the research community. Additional research is also expected to further validate and ex...

KnE Social Sciences, 2019

Most of the healthcare organizations and medical research institutions store their patient’s data... more Most of the healthcare organizations and medical research institutions store their patient’s data digitally for future references and for planning their future treatments. This heterogeneous medical dataset is very difficult to analyze due to its complexity and volume of data, in addition to having missing values and noise which makes this mining a tedious task. Efficient classification of medical dataset is a major data mining problem then and now. Diagnosis, prediction of diseases and the precision of results can be improved if relationships and patterns from these complex medical datasets are extracted efficiently. This paper analyses some of the major classification algorithms such as C4.5 ( J48), SMO, Naïve Bayes, KNN Classification algorithms and Random Forest and the performance of these algorithms are compared using WEKA. Performance evaluation of these algorithms is based on Accuracy, Sensitivity and Specificity and Error rate. The medical data set used in this study are He...

International Journal of Artificial Life Research, Apr 1, 2012

Increasing the growth rates of websites' number has led to the challenge of assisting Web custome... more Increasing the growth rates of websites' number has led to the challenge of assisting Web customers in finding appropriate details from the Internet using an intelligent search engine. Information retrieval (IR) is an essential and useful strategy for Web users; thus, different strategies and techniques are designed for such purpose. Currently, the focus on the usefulness of Artificial Intelligence (AI) has been improved with IR. One AI area is Evolutionary Computation (EC), which is based on designs of natural selection. A traditional and important strategy in EC is Genetic Algorithm (GA); this paper adopts the GA technique to enhance the retrieval of HTML documents. This improvement is obtained by creating a modern evaluation function and applying a hybrid crossover operator. The proposed evaluation function is based on term proximity, keyword probability within the document, and HTML tag weight query. Experimental results are compared with two well known evaluation function functions applied in IR domain which are Okapi-BM25 and Bayesian interface network model. The results demonstrate a good level of enhancement to the recall and precision. In addition, the documents retrieved by the proposed system were more accurate and relevant to the queries than that retrieved by other models.

Proceedings of the 7th International Joint Conference on Computational Intelligence, 2015

This paper proposes a new solution for Traveling Salesman Problem (TSP) using genetic algorithm. ... more This paper proposes a new solution for Traveling Salesman Problem (TSP) using genetic algorithm. A combinational crossover technique is employed in the search for optimal or near-optimal TSP solutions. It is based upon chromosomes that utilise the concept of heritable building blocks. Moreover, generation of a single offspring, rather than two, per pair of parents, allows the system to generate high performance chromosomes. This solution is compared with the well performing Ordered Crossover (OX). Experimental results demonstrate that, due to the well structured crossover technique, has enhanced performance.

2009 Second International Conference on Developments in eSystems Engineering, 2009

... Ammar Al-Dallal School of Information Systems Computing and Mathematics Brunel University, UK... more ... Ammar Al-Dallal School of Information Systems Computing and Mathematics Brunel University, UK Ammar.AlDallal@brunel.ac.uk ... due to its sim-plicity and its capability as a powerful search mechanism can be employed to make several important contributions to the field of IR. ...

International Journal of Applied Metaheuristic Computing, 2013

This paper proposes two IR approaches; the first is IR with GA, which is a GA-based IR approach. ... more This paper proposes two IR approaches; the first is IR with GA, which is a GA-based IR approach. This approach introduces modified GA operators that allow IR with GA to achieve high performance. The second IR model is IR without GA, which is based on traditional IR approach. Both enhance the precision and recall of the web search by improving the document representation where an enhanced inverted index is developed for this purpose. Moreover, these two models use the same proposed evaluation function for measuring the document relativity to the user query. A number of experiments were conducted to compare the performance of the two suggested approaches with existing techniques. The two suggested approaches were then compared experimentally with another two techniques of classical IR namely Okapi-BM25 fitness function and Bayesian inference network model from documents quality of retrieval perspective. The obtained results demonstrate a good level of enhancement to the recall and pre...

Exhibition, 2009

... 1 School of Information Systems Computing and Mathematics,Brunel University,UK Email:Ammar.Al... more ... 1 School of Information Systems Computing and Mathematics,Brunel University,UK Email:Ammar.AlDallal@brunel.ac.uk 2 College of Information ... and its capability as a powerful search mechanisms, can be employed to make several important contribution to the field of IR. ...