Omar Barukab

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Macquarie University

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Papers by Omar Barukab

SUKRY: Suricata IDS with Enhanced kNN Algorithm on Raspberry Pi for Classifying IoT Botnet Attacks

Electronics, Feb 27, 2022

This article is an open access article distributed under the terms and conditions of the Creative... more

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SUKRY: Suricata IDS with Enhanced kNN Algorithm on Raspberry Pi for Classifying IoT Botnet Attacks

Electronics

The focus of this research is the application of the k-Nearest Neighbor algorithm in terms of cla... more The focus of this research is the application of the k-Nearest Neighbor algorithm in terms of classifying botnet attacks in the IoT environment. The kNN algorithm has several advantages in classification tasks, such as simplicity, effectiveness, and robustness. However, it does not perform well in handling large datasets such as the Bot-IoT dataset, which represents a huge amount of data about botnet attacks on IoT networks. Therefore, improving the kNN performance in classifying IoT botnet attacks is the main concern in this study by applying several feature selection techniques. The whole research process was conducted in the Rapidminer environment using three prebuilt feature selection techniques, namely, Information Gain, Forward Selection, and Backward Elimination. After comparing accuracy, precision, recall, F1 score and processing time, the combination of the kNN algorithm and the Forward Selection technique (kNN-FS) achieves the best results among others, with the highest le...

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DBP-iDWT: Improving DNA-Binding Proteins Prediction Using Multi-Perspective Evolutionary Profile and Discrete Wavelet Transform

Computational Intelligence and Neuroscience

DNA-binding proteins (DBPs) have crucial biotic activities including DNA replication, recombinati... more DNA-binding proteins (DBPs) have crucial biotic activities including DNA replication, recombination, and transcription. DBPs are highly concerned with chronic diseases and are used in the manufacturing of antibiotics and steroids. A series of predictors were established to identify DBPs. However, researchers are still working to further enhance the identification of DBPs. This research designed a novel predictor to identify DBPs more accurately. The features from the sequences are transformed by F-PSSM (Filtered position-specific scoring matrix), PSSM-DPC (Position specific scoring matrix-dipeptide composition), and R-PSSM (Reduced position-specific scoring matrix). To eliminate the noisy attributes, we extended DWT (discrete wavelet transform) to F-PSSM, PSSM-DPC, and R-PSSM and introduced three novel descriptors, namely, F-PSSM-DWT, PSSM-DPC-DWT, and R-PSSM-DWT. Onward, the training of the four models were performed using LiXGB (Light eXtreme gradient boosting), XGB (eXtreme gradi...

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iAcety–SmRF: Identification of Acetylation Protein by Using Statistical Moments and Random Forest

Membranes, 2022

Acetylation is the most important post-translation modification (PTM) in eukaryotes; it has manif... more Acetylation is the most important post-translation modification (PTM) in eukaryotes; it has manifold effects on the level of protein that transform an acetyl group from an acetyl coenzyme to a specific site on a polypeptide chain. Acetylation sites play many important roles, including regulating membrane protein functions and strongly affecting the membrane interaction of proteins and membrane remodeling. Because of these properties, its correct identification is essential to understand its mechanism in biological systems. As such, some traditional methods, such as mass spectrometry and site-directed mutagenesis, are used, but they are tedious and time-consuming. To overcome such limitations, many computer models are being developed to correctly identify their sequences from non-acetyl sequences, but they have poor efficiency in terms of accuracy, sensitivity, and specificity. This work proposes an efficient and accurate computational model for predicting Acetylation using machine l...

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A Novel Approach to Identify the Categories of Attributes for the Three-Factor Structure in Customer Satisfaction

Complexity, 2020

Evaluation of customer satisfaction is an important area of marketing research in which products ... more Evaluation of customer satisfaction is an important area of marketing research in which products are defined by attributes that can be grouped into different categories depending on their contribution to customer satisfaction. It is important to identify the category of an attribute so that it can be prioritized by a manager. The Kano model is a well-known method to perform this task for an individual customer. However, it requires filling in a form, which is a difficult and time-consuming exercise. Many existing methods require less effort from the customer side to perform data collection and can be used for a group of customers; however, they are not applicable to individuals. In the present study, we develop a data-analytic method that also uses the dataset; however, it can identify the attribute category for an individual customer. The proposed method is based on the probabilistic approach to analyze changes in the customer satisfaction corresponding to variations in attribute v...

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A Survey on Security Patterns and Issues in Cloud Computing Environment

Cloud Computing becomes an attractive proposition because of long-term potential advantage by red... more Cloud Computing becomes an attractive proposition because of long-term potential advantage by reducing the cost of services and thereby gaining more business outcomes. It is capable of transferring facilities by using the internet in a secured manner economically. It has got interested from both industry and academia. The shared utilization characteristics enhance the proficiencies of the hardware resources of cloud computing. By virtue of this feature, a cloud is being used by commercial and specific users to make available their data in form of either application or service. Security concern originates because of the sharing environment in which external administration for the migration of user's assets takes place. A comprehensive review in order to find major gaps and issues related to security comes under cloud computing has been tried to present. The issues belong to security and its possible countermeasure has been found out and present. The increased number of cloud serv...

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Performance analysis of 40 Gb/s free space optics transmission based on orbital angular momentum multiplexed beams

Alexandria Engineering Journal, 2021

DBP-GAPred: An intelligent method for prediction of DNA-binding proteins types by enhanced evolutionary profile features with ensemble learning

Journal of Bioinformatics and Computational Biology, 2021

DNA-binding proteins (DBPs) perform an influential role in diverse biological activities like DNA... more DNA-binding proteins (DBPs) perform an influential role in diverse biological activities like DNA replication, slicing, repair, and transcription. Some DBPs are indispensable for understanding many types of human cancers (i.e. lung, breast, and liver cancer) and chronic diseases (i.e. AIDS/HIV, asthma), while other kinds are involved in antibiotics, steroids, and anti-inflammatory drugs designing. These crucial processes are closely related to DBPs types. DBPs are categorized into single-stranded DNA-binding proteins (ssDBPs) and double-stranded DNA-binding proteins (dsDBPs). Few computational predictors have been reported for discriminating ssDBPs and dsDBPs. However, due to the limitations of the existing methods, an intelligent computational system is still highly desirable. In this work, features from protein sequences are discovered by extending the notion of dipeptide composition (DPC), evolutionary difference formula (EDF), and K-separated bigram (KSB) into the position-speci...

Majorization Results for Certain Subfamilies of Analytic Functions

Journal of Function Spaces, 2021

Let h 1 z and h 2 z be two nonvanishing holomorphic functions in the open unit disc with h 1 0 = ... more Let h 1 z and h 2 z be two nonvanishing holomorphic functions in the open unit disc with h 1 0 = h 2 0 = 1 . For some holomorphic function q z , we consider the class consisting of normalized holomorphic functions f whose ratios f z / z q z and q z are subordinate to h 1 z and h 2 z , respectively. The majorization results are obtained for this class when h 1 z is chosen either h 1 z = cos z or h 1 z = 1 + sin z or h 1 z = 1 + z and h 2 z = 1 + sin z .

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iSulfoTyr-PseAAC: Identify Tyrosine Sulfation Sites by Incorporating Statistical Moments via Chou’s 5-steps Rule and Pseudo Components

Current Genomics, 2019

Background:The amino acid residues, in protein, undergo post-translation modification (PTM) durin... more Background:The amino acid residues, in protein, undergo post-translation modification (PTM) during protein synthesis, a process of chemical and physical change in an amino acid that in turn alters behavioral properties of proteins. Tyrosine sulfation is a ubiquitous posttranslational modification which is known to be associated with regulation of various biological functions and pathological processes. Thus its identification is necessary to understand its mechanism. Experimental determination through site-directed mutagenesis and high throughput mass spectrometry is a costly and time taking process, thus, the reliable computational model is required for identification of sulfotyrosine sites.Methodology:In this paper, we present a computational model for the prediction of the sulfotyrosine sites named iSulfoTyr-PseAAC in which feature vectors are constructed using statistical moments of protein amino acid sequences and various position/composition relative features. These features a...

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Android malware classification based on ANFIS with fuzzy c-means clustering using significant application permissions

TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES, 2017

Mobile phones have become an essential part of our lives because we depend on them to perform man... more Mobile phones have become an essential part of our lives because we depend on them to perform many tasks, and they contain personal and important information. The continuous growth in the number of Android mobile applications resulted in an increase in the number of malware applications, which are real threats and can cause great losses. There is an urgent need for efficient and effective Android malware detection techniques. In this paper, we present an adaptive neuro-fuzzy inference system with fuzzy c-means clustering (FCM-ANFIS) for Android malware classification. The proposed approach utilizes the FCM clustering method to determine the optimum number of clusters and cluster centers, which improves the classification accuracy of the ANFIS. The most significant permissions used in the Android application selected by the information gain algorithm are used as input to the proposed approach (FCM-ANFIS) to classify applications as either malware or benign applications. The experimental results show that the proposed approach (FCM-ANFIS) achieves the highest classification accuracy of 91%, with lowest false positive and false negative rates of 0.5% and 0.4%, respectively.

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Autonomous framework simulation tools for real-time multimedia streaming over wireless ad-hoc networks

SIMULATION, 2019

Real-time video communication has become one of the most significant applications extensively use... more Real-time video communication has become one of the most significant applications extensively used by homogeneous/heterogeneous wireless network technologies, such as Wi-Fi, the Internet of things, the wireless sensor network (WSN), 5G, etc. This leads to enhanced deployment of multimedia streaming applications over wireless network technologies. In order to accomplish the optimal performance of real-time multimedia streaming applications over the homogeneous/heterogeneous wireless network, it is therefore necessary to develop a simulation tool-set that effectively measures the quality of service (QoS) for different multimedia streaming applications over transport layer protocols. This paper proposes an autonomous simulation tool (AST) that is entirely independent from the source code of transport layer protocols. Furthermore, the AST is integrated into NS-2 to evaluate the QoS of real-time video streaming over numerous transport layer protocols and it uses new QoS measurement tools...

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iHyd-PseAAC (EPSV): Identifying Hydroxylation Sites in Proteins by Extracting Enhanced Position and Sequence Variant Feature via Chou's 5- Step Rule and General Pseudo Amino Acid Composition

Current Genomics, 2019

Background:In various biological processes and cell functions, Post Translational Modifications (... more Background:In various biological processes and cell functions, Post Translational Modifications (PTMs) bear critical significance. Hydroxylation of proline residue is one kind of PTM, which occurs following protein synthesis. The experimental determination of hydroxyproline sites in an uncharacterized protein sequence requires extensive, time-consuming and expensive tests.Methods:With the torrential slide of protein sequences produced in the post-genomic age, certain remarkable computational strategies are desired to overwhelm the issue. Keeping in view the composition and sequence order effect within polypeptide chains, an innovative in-silico predictor via a mathematical model is proposed.Results:Later, it was stringently verified using self-consistency, cross-validation and jackknife tests on benchmark datasets. It was established after a rigorous jackknife test that the new predictor values are superior to the values predicted by previous methodologies.Conclusion:This new mathem...

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Semantic data mapping technology to solve semantic data problem on heterogeneity aspect

International Journal of Advances in Intelligent Informatics, 2017

The diversity of applications developed with different programming languages, application/data ar... more The diversity of applications developed with different programming languages, application/data architectures, database systems and representation of data/information leads to heterogeneity issues. One of the problem challenges in the problem of heterogeneity is about heterogeneity data in term of semantic aspect. The semantic aspect is about data that has the same name with different meaning or data that has a different name with the same meaning. The semantic data mapping process is the best solution in the current days to solve semantic data problem. There are many semantic data mapping technologies that have been used in recent years. This research aims to compare and analyze existing semantic data mapping technology using five criteria’s. After comparative and analytical process, this research provides recommendations of appropriate semantic data mapping technology based on several criteria’s. Furthermore, at the end of this research we apply the recommended semantic data mappin...

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Map Calculation of the Shapley-Shubik Voting Powers: An Example of the European Economic Community

International Journal of Mathematical, Engineering and Management Sciences, 2017

The paper utilizes the Karnaugh map in a pedagogical calculation of the Shapley-Shubik index of v... more The paper utilizes the Karnaugh map in a pedagogical calculation of the Shapley-Shubik index of voting power, which is perhaps the most prominent such index for managerial, political, and engineering voting systems. The Karnaugh map has features that allow it to readily implement this calculation, namely: (a) it can conveniently represent pseudo-switching functions of the form g= B_2^n →R, (b) it can immediately detect the number of orderings in going from one of its configurations (cells) to another, and (c) it visually identifies a pair of configurations that is critical w. r. t. a certain voter, which are a primitive winning coalition of which this voter is a member and a corresponding primitive losing coalition that results when this voter defects. The paper offers a detailed description of these three features and of the associated calculations using the celebrated system of the European Economic Community as a running example.

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SVM significant role selection method for improving semantic text plagiarism detection

International Journal of ADVANCED AND APPLIED SCIENCES, 2017

This research introduces an approach for the prediction and detection of plagiarized text based o... more This research introduces an approach for the prediction and detection of plagiarized text based on Semantic Role Labelling (SRL) and Support Vector Machine (SVM). The introduced method evaluates and analyses text based on semantic position for each term within the text. It additionally detects the source semantic sense in considering the connections between its terms using the Semantic Role Labeling (SRL). SRL presents noteworthy remuneration while creating roles from a text semantically. Selecting for every role created by the SVM method keeping in mind the end goal to foresee significant roles is a noteworthy part of the proposed system. The imperative roles that will vote by the SVM strategy will be chosen in the comparability computation process. The proposed strategy assessed utilizing the PAN-PC-10 dataset. The outcomes proved that the introduced strategy enhanced the execution as far as the assessment measures contrasted and other plagiarism detection methods.

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Restriction Inhibition Assay: A Qualitative and Quantitative Method to Screen Sequence Specific DNA Binder from Herbal Plants

Tropical Journal of Pharmaceutical Research, 2014

Purpose: To employ restriction inhibition assay (RIA) to screen phytochemical-rich fractions (PRF... more Purpose: To employ restriction inhibition assay (RIA) to screen phytochemical-rich fractions (PRFs) with high affinity for EcoRI and HindIII restriction sequences and correlate their interaction to an anticancer activity. Methods: pBR322 linear plasmid DNA was used as a template to screen the sequence-selective inhibition of aqueous extracts of Cinnamomum zeylanicum and Picrorhiza kurroa, respectively. The template was further incubated with different concentrations of PRFs prior to digestion with restriction endonucleases HindIII and EcoRI. The Expressed Sequence Tags (ESTs) and Sequence Tag Sites (STS) of oncogenes were screened for the presence of EcoRI and HindIII restriction sequences to associate an anticancer property to PRF. Results: The inhibitory concentrations of Cinnamomum zeylanicum aqueous extract against HindIII and EcoRI endonucleases were approximately 2.5 and 5 µg/µl, respectively. No binding was observed for Picrorhiza kurroa at both HindIII and EcoRI restriction sites. The saponin-rich fractions of Cinnamomum zeylanicum showed significant (p < 0.001) inhibition as compared to control at concentrations of 0.28±1.45 µg/µl for EcoRI and 0.11±2.68 µg/µl for HindIII endonucleases. Both EcoRI and HindIII restriction sites were found repeatedly in the STS and ESTs of BRCA2, the early onset oncogene. Conclusion: The inhibition of endonucleases by phytochemical-rich fractions provides direct evidence of the use of RIA for screening as well as demonstrating the binding specificity of these PRFs. The presence of 5'-AAGCTT-3' & 5'-GAATTC-3' in the ESTs of BRAC2 provides an insight into the use of screened components as leads in the search for novel anticancer compounds.

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Android Malware Classification Using Optimized Ensemble Learning Based on Genetic Algorithms

Sustainability

The continuous increase in Android malware applications (apps) represents a significant danger to... more The continuous increase in Android malware applications (apps) represents a significant danger to the privacy and security of users’ information. Therefore, effective and efficient Android malware app-classification techniques are needed. This paper presents a method for Android malware classification using optimized ensemble learning based on genetic algorithms. The suggested method is divided into two steps. First, a base learner is used to handle various machine learning algorithms, including support vector machine (SVM), logistic regression (LR), gradient boosting (GB), decision tree (DT), and AdaBoost (ADA) classifiers. Second, a meta learner RF-GA, utilizing genetic algorithm (GA) to optimize the parameters of a random forest (RF) algorithm, is employed to classify the prediction probabilities from the base learner. The genetic algorithm is used to optimize the parameter settings in the RF algorithm in order to obtain the highest Android malware classification accuracy. The ef...

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Intelligent Hybrid Approach for Android Malware Detection based on Permissions and API Calls

International Journal of Advanced Computer Science and Applications

Android malware is rapidly becoming a potential threat to users. The number of Android malware is... more Android malware is rapidly becoming a potential threat to users. The number of Android malware is growing exponentially; they become significantly sophisticated and cause potential financial and information losses for users. Hence, there is a need for effective and efficient techniques to detect the Android malware applications. This paper proposes an intelligent hybrid approach for Android malware detection using the permissions and API calls in the Android application. The proposed approach consists of two steps. The first step involves finding the most significant permissions and Application Programming Interfaces (API) calls that leads to efficient discrimination between the malware and good ware applications. For this purpose, two features selection algorithms, Information Gain (IG) and Pearson CorrCoef (PC) are employed to rank the individual permissions and API's calls based on their importance for classification. In the second step, the proposed new hybrid approach for Android malware detection based on the combination of the Adaptive neural fuzzy Inference System (ANFIS) with the Particle Swarm Optimization (PSO), is employed to differentiate between the malware and goodware Android applications (apps). The PSO is intelligently utilized to optimize the ANFIS parameters by tuning its membership functions to generate reliable and more precise fuzzy rules for Android apps classification. Using a dataset consists of 250 goodware and 250 malware apps collected from different recourse, the conducted experiments show that the suggested method for Android malware detection is effective and achieved an accuracy of 89%.

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Reducing Flooding of Zone Routing Protocol in Mobile Ad-Hoc Networks

VAWKUM Transactions on Computer Sciences, 2016

SUKRY: Suricata IDS with Enhanced kNN Algorithm on Raspberry Pi for Classifying IoT Botnet Attacks

Electronics, Feb 27, 2022

This article is an open access article distributed under the terms and conditions of the Creative... more

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SUKRY: Suricata IDS with Enhanced kNN Algorithm on Raspberry Pi for Classifying IoT Botnet Attacks

Electronics

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DBP-iDWT: Improving DNA-Binding Proteins Prediction Using Multi-Perspective Evolutionary Profile and Discrete Wavelet Transform

Computational Intelligence and Neuroscience