108 10 3575 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Nonthamand, Narin Date A point or period of time associated with an event in the lifecycle of the resource 2023-05-22 Description An account of the resource      The objectives of this study are (1) to explore pre-service teachers’ needs in using educational technology tools for online learning, (2) to develop an online lesson about the use of educational technology tools for pre-service teachers, and (3) to compare the learning achievements before and after taking the lesson. The methodology was divided into three phases. The first phase was a needs assessment concerning the use of educational technology tools in online learning. The samples were 272 undergraduate pre-service teachers at the University of Phayao. The research instrument was a needs analysis questionnaire on the use of educational technology tools in online learning. The collected data was analyzed using Modified Priority Needs Index (PNImodified). In the second phase, an online lesson about the use of educational tools was developed. The research samples were three experts in three different fields, including instructional design, educational technology, and assessment and evaluation. The research instrument used in this phase was a suitability assessment form for the designed online lesson. Document analysis and descriptive statistics were used to analyze the data. In the third phase, the learning achievements before and after completing the lesson were compared. The samples were 112 pre-service teachers at the University of Phayao. The research instrument was a learning achievement test. The data analysis included means, standard deviations, and a t-test. The results were as follows:  Regarding the needs analysis concerning the use of educational technology tools in online learning, the pre-service teachers considered that tools for completing learning tasks were the most crucial element. The data collected from open-ended questions revealed that the most critical problems experienced in online learning were learning tools and poor Internet speed. The results from the suitability test showed that the developed online lesson was overall suitable (M = 2.98, SD = .174).The pre-service teachers’ average post-test score on the achievement test on the use of educational technology tools was higher than the average pre-test score with a statistically significant difference at the .05 level. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/37775 10.3991/ijim.v17i10.37775 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/37775/13209 Rights Information about rights held in and over the resource Copyright (c) 2023 Narin Nonthamand https://creativecommons.org/licenses/by/4.0 Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 17 No. 10 (2023); pp. 30-46 1865-7923 Subject The topic of the resource online course educational technology tools pre-service teachers Title A name given to the resource Development of an Online Learning Lesson in the Educational Technology Equipment Operation Course for Pre-Service Teachers Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource R. Vidhya T. Padmapriya S. Selvakumar R. Mary Victoria M. Anand Date A point or period of time associated with an event in the lifecycle of the resource 2023-02-23 Description An account of the resource The traditional multiple reserves and resounding costs of increase of the corporal volume can be replaced by a distributed file model of divided data employing algorithms, multidimensional integrity, and resilience to complete losses of the storage facilities. The model's created duplicated data enables you to recover some of the split components' lost functionality. A rapid shift in the appraisal and application of knowledge is also required by increasing information and communication technologies. As a result, modern learning methodologies, approaches, and technologies are being developed. This paper describes how to build an automated instructional and analytical complex using semantic information. It has been established what is needed for such an educational and technological complex. Tools built on a semantic network are represented in formal and structural models. Since it was created using a thorough understanding of the topic, the model is intended to facilitate students' perception of the many educational and technical complexities and to enhance the teacher's work. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/37769 10.3991/ijim.v17i04.37769 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/37769/12751 Rights Information about rights held in and over the resource Copyright (c) 2023 R. Vidhya, T. Padmapriya, S. Selvakumar, R. Mary Victoria, M. Anand https://creativecommons.org/licenses/by/4.0 Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 17 No. 04 (2023); pp. 4-20 1865-7923 Subject The topic of the resource educational process semantic network intelligent model security multidimensional parity Title A name given to the resource Multidimensional Parity Algorithms to Escalate the Security of Intelligent Mobile Models in Education Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource G. Baby Saral R. Priya Date A point or period of time associated with an event in the lifecycle of the resource 2023-02-23 Description An account of the resource Mobile Screen spent by teenage who use lot of time on screen experience psychiatric problems such as frustration, fatigue, depression, anxiety, and so on. Matplotlib pyplot with histogram figure is used to evaluate the psychiatric condition data (CSV file). For the purpose of rating the condition data, the standard deviation and mean are determined. For data analysis, there is a correlation matrix that compares every row and column. Gradient Booster, Logistic Regression, Knn algorithm is used to compare the precision of the machine learning process, which merged the characteristics of addictive and non-addictive data to find rating disorders. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/37745 10.3991/ijim.v17i04.37745 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/37745/12771 Rights Information about rights held in and over the resource Copyright (c) 2023 G. Baby Saral, R. Priya https://creativecommons.org/licenses/by/4.0 Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 17 No. 04 (2023); pp. 144-151 1865-7923 Subject The topic of the resource Data Science, Gradien Booster, logistic regression, Pyplot. Title A name given to the resource Mobile Screen Addiction Using Addictive Attribute by Combination of Algorithm-In Addiction Disorder Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Non-refereed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource N. Chitra Safinaz. S K. Bhanu Rekha Date A point or period of time associated with an event in the lifecycle of the resource 2023-02-23 Description An account of the resource The Feature Selection concept is the procedure where in the data is simplified removing the irrelevant features. Divergence method is another strategy of method where in the relation among the attributes and class is measured to understand their contribution to performance. Nowadays the mobile network is  integrated with the other networks like the computer networks transmitting all kinds of data leading to attacks in  networks  known as intrusion in computer networks equally applicable to mobile communications.  So in this paper the intrusion detection method involving the other other mode of communication is considered in mobile interaction network. The proposed algorithm performs feature selection using the divergence evaluation method to reduce the feature set. A 10% KDDCUP99 data set was used for the evaluation of the proposed algorithm, and performance metrics were evaluated using the C4.5 classifier. The metrics TPR, FPR and consistency were compared with the mutual information based DMIFSA, RMIFSA, MMIFSA methods and the proposed method is implemented on Python 3.8 that proved to achieve the high accuracy of 99.94% as compared to other methods and also reduce the redundant features. The consistency in Accuracy is maintained almost from 4 features to 10 features in proposed method as compared to other methods that indicates the stability of the system is achieved. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/37733 10.3991/ijim.v17i04.37733 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/37733/12761 Rights Information about rights held in and over the resource Copyright (c) 2023 N. Chitra, Safinaz. S, K. Bhanu Rekha https://creativecommons.org/licenses/by/4.0 Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 17 No. 04 (2023); pp. 75-88 1865-7923 Subject The topic of the resource Divergence, Feature Selection, C4.5 Classifier, mobile communications, TPR (True Positive Rate), FPR (False positive Rate), Accuracy, stability Title A name given to the resource Divergence Based Feature Selection for Pattern Recognizing of the Performance of Intrusion Detection in Mobile Communications Merged with the Computer Communication Networks Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Ghorab, Ahmed S. Rasheed, Raed S. Hamad, Hatem M. Date A point or period of time associated with an event in the lifecycle of the resource 2023-04-26 Description An account of the resource Vehicle capacities and intelligence are rapidly increasing, which will likely support a wide range of novel and interesting applications. However, these resources are not effectively utilized. To take advantage of these invaluable capabilities in smart vehicles, they can be used in the cloud environment and can be operated through distributed computing platforms in order to benefit from their combined processing power, storage capacity, and memory resources. Vehicular edge computing (VEC) is a promising field that allows computing tasks to be transferred from cloud servers to vehicular edge servers for processing, allowing data and apps to be placed closer to vehicles (users). This paper proposes a framework that combines two modules, the first one for managing microservice caching in vehicle-mounted edge networks, such that we use cluster-based caching technique to deal with the case where similar microservices are frequently requested in VEC. The second one integrates the computational capabilities of the edge servers with the capabilities of vehicles to perform task offloading in a collaborative manner. Our solution addresses the limitations of existing edge computing platforms during peak times by combining microservices caching with computational task offloading to improve overall system performance.   Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/37729 10.3991/ijim.v17i08.37729 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/37729/13063 Rights Information about rights held in and over the resource Copyright (c) 2023 Ahmed S. Ghorab, Hatem Hammad, Raed Rasheed https://creativecommons.org/licenses/by/4.0 Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 17 No. 08 (2023); pp. 78-99 1865-7923 Subject The topic of the resource Mobile Edge Computing (MEC) Task Offloading Microservice Caching Title A name given to the resource Joint Microservices Caching and Task Offloading Framework in VEC Based on Deep Reinforcement Learning Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Abdalilah. G. I. Alhalangy Date A point or period of time associated with an event in the lifecycle of the resource 2023-02-23 Description An account of the resource Group’s communications using Mobile Ad hoc Networks (MANETs) have recently drawn a lot of interest. Information is delivered to a group of receivers simultaneously through a process known as multipath. Therefore, to enable team communication activities, an effective and efficient multipath routing protocol is essential. Enhancing multicast routing has been the subject of numerous initiatives. However, they don't account for scalability. A scalable geographic multicast routing protocol was proposed in this research (SGMRP). This protocol's primary goal is to create a compact, adaptable multipath routing strategy that works regardless of the number of broadcast participants or the magnitude of the network. Using a prediction model and cross-validation techniques, the model performance evaluation tool assesses model effectiveness. The satisfaction with the service was also evaluated using a question. In addition to reducing the number of participating nodes in localization, the proposed method also gets rid of duplicate packets between clusters. The article introduces the framework's fundamental idea, details its transparent implementations, and finishes with a preliminary assessment of the framework based on typical mobile software kinds. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/37675 10.3991/ijim.v17i04.37675 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/37675/12765 Rights Information about rights held in and over the resource Copyright (c) 2023 Abdalilah. G. I. Alhalangy https://creativecommons.org/licenses/by/4.0 Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 17 No. 04 (2023); pp. 101-116 1865-7923 Subject The topic of the resource Scalable Geographic Multicast Routing Protocol (SGMRP); Mobile Ad hoc Networks (MANETs); GPS; localization; multicast routing; Title A name given to the resource SGMRP-Utilizing a Mobile Ad Hoc Network to Develop a Scalable Geographic Multicast Routing Protocol for Localization Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Adil. O. Y. Mohamed Date A point or period of time associated with an event in the lifecycle of the resource 2023-02-23 Description An account of the resource The rate of smartphone purchases is rising daily, and mobile payments are now frequently accepted in various areas. It is essential to transfer money completely safe as well as quick. The encrypted distributed ledgers function provides verified real-time transaction confirmation without the necessity for intermediaries like banks and clearinghouses; blockchain provide quick, secure, decentralized, and inexpensive transaction services. Blockchain technology makes money transfer simpler with transparency and financial data security. Through these capabilities, blockchain has attracted interest from around the world. However, some challenges arise while completing some financial security needs. This work proposes a framework for secure mobile payments based on blockchain technology. The advantages of blockchain are discussed and how blockchain technology provides multi-level authentication to secure mobile based financial transactions. Due to the increased safety and confidentiality of users on mobile payment apps, the suggested system takes into account the need of developing a safe application for the mobile transactions. We have also addressed the security related challenges of blockchain based payment applications and provided potential solutions. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/37671 10.3991/ijim.v17i04.37671 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/37671/12755 Rights Information about rights held in and over the resource Copyright (c) 2023 Adil. O. Y. Mohamed https://creativecommons.org/licenses/by/4.0 Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 17 No. 04 (2023); pp. 37-46 1865-7923 Subject The topic of the resource Mobile Payment; Blockchain; Secure; transaction; fast Title A name given to the resource Intelligent Blockchain-Based Secure Framework for Transaction in Mobile Electronic Payment System Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Rusul H. Al_taie Hawraa abd Al_kadum hassan Date A point or period of time associated with an event in the lifecycle of the resource 2023-02-23 Description An account of the resource These days, We know that mobile phones with camera are very common to  used by most of the people because of their ease of use and carry . So I figured I need for mobile phone images processing. These images are often subjected to a variety of types of distortion, such as noise, poor illumination, and blur due to transmission , image acquisition and mobile movement during capturing scene. This Degradation leads to produce distorted images are not suitable for viewing or application. To overcome this degradation, this paper presents image improvement in mobile phone by distortion removal using Band Reject Filter and DFT to obtain on the best clear image. Periodic noise is sinusoidal of several of certain frequencies and periodic in nature. It looks identical to the bars that the image is covered. The proposed method is subjected to eliminate this noise from a set of images using Band Reject Filter using discrete Fourier transform that attenuate and replace a number of degradation bands. Then, computes the peak signal to noise ratio metric for each band. After that, select the largest value of each band for the purpose the making one clear image. Finally, the bands that carry value large are merged to produce a one image. The final image is converted to the spatial domain using an inverse Fourier transform. The experimental outcomes indicate that the proposed method improves the degraded image by a greater percentage without using the better value for metric and makes image more clear and  informative compare with the input image. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/37669 10.3991/ijim.v17i04.37669 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/37669/12769 Rights Information about rights held in and over the resource Copyright (c) 2023 Rusul H. Al_taie, Hawraa abd Al_kadum hassan https://creativecommons.org/licenses/by/4.0 Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 17 No. 04 (2023); pp. 134-143 1865-7923 Subject The topic of the resource Band Reject Filter (BRF) ; Periodic Noise; Image Enhancement; DFT; Mobile Phone images. Title A name given to the resource Enhance Mobile Phone Digital Camera Images Using Band Reject Filter and Discrete Fourier Transform Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Non-refereed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Ahdi Hassan Abdalilah. G. I. Alhalangy Fahad Alzahrani Date A point or period of time associated with an event in the lifecycle of the resource 2023-02-23 Description An account of the resource Fake accounts on online social networks are increasing today with an increase in the number of active social network users. Social media websites allow users to share thoughts, facts, views and re-sharing these into various networks. Social media platforms provide users with enormous valuable information but with this great amount of information in social media, many issues like fake profile, online hacking have also grown. The fake profiles in online social sites create fake news and share unwanted material which contains spam links that affect natural users. The massive issue in social media communication networks is spam and it is necessary to identify fake profiles to stop spam. In this paper, a supervised machine learning algorithm called support vector machine (SVM) is used to identify fake accounts on social media effectively. In order to automatically identify fake online profiles, Random Forest classifier is used with SVM. With this concept, it can be applied online easily to identify millions of accounts that cannot be examined manually. The result of this model is compared with other identification techniques and the results show that the proposed algorithm performs better with high precision and recall. This method efficiently safeguards social media networks from online threats and attacks. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/37645 10.3991/ijim.v17i04.37645 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/37645/12759 Rights Information about rights held in and over the resource Copyright (c) 2023 Ahdi Hassan, Abdalilah. G. I. Alhalangy , Fahad Alzahrani https://creativecommons.org/licenses/by/4.0 Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 17 No. 04 (2023); pp. 64-74 1865-7923 Subject The topic of the resource Social Media, SVM, Random Forest Classifier, Fake profile, Mobile network. Title A name given to the resource Fake Accounts Identification in Mobile Communication Networks Based on Machine Learning Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource International Journal of Interactive Mobile Technologies (iJIM) Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Aljammal, Ashraf H. taamneh , Salah Qawasmeh, Ahmad Bani Salameh, Hani Date A point or period of time associated with an event in the lifecycle of the resource 2023-03-07 Description An account of the resource Nowadays, individuals and organizations are increasingly targeted by phishing attacks, so an accurate phishing detection system is required. Therefore, many phishing detection techniques have been proposed as well as phishing datasets have been collected. In this paper, three datasets have been used to train and test machine learning classifiers. The datasets have been archived by Phish-Tank and UCI Machine Learning Repository. Furthermore, Information Gain algorithm have been used for features reduction and selection purpose. In addition, six machine learning classifiers have been evaluated, namely NaiveBayes, ANN, DecisionStump, KNN, J48 and RandomForest. However, the classifiers have been trained and tested over the three datasets in two stages. The first stage is using all features included in each dataset while the second stage using selected features by IG algorithm. At the first stage RandomForest classifier has shown the best performance over Dataset-1 and Dataset-2, while J48 has shown the best performance over Dataset-3. On the other hand, after features selection, the RandomForest classifier was the superior among the other five classifiers over Dataset-1 and Dataset-2 with accuracy of 98% and 93.66% respectively. While ANN classifier has shown the best performance with accuracy of 88.92% over Dataset-3. Because of the few number of instances as well as features in Dataset-3 comparing to the other two dataset; the performance of the classifiers has been affected. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://online-journals.org/index.php/i-jim/article/view/37575 10.3991/ijim.v17i05.37575 Language A language of the resource eng Publisher An entity responsible for making the resource available International Association of Online Engineering (IAOE), Vienna, Austria Relation A related resource https://online-journals.org/index.php/i-jim/article/view/37575/12813 Rights Information about rights held in and over the resource Copyright (c) 2023 Ashraf Hamdan Aljammal https://creativecommons.org/licenses/by/4.0 Source A related resource from which the described resource is derived International Journal of Interactive Mobile Technologies (iJIM); Vol. 17 No. 05 (2023); pp. 71-83 1865-7923 Subject The topic of the resource Phishing attack, phishing attack detection, Cybersecurity, Machine Learning, Web security Title A name given to the resource Machine Learning Based Phishing Attacks Detection Using Multiple Datasets Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article