Malware Detection Using Ensemble N-gram Opcode Sequences
Conventional approaches to tackling malware attacks have proven to be futile at detecting never-before-seen (zero-day) malware. Research however has shown that zero-day malicious files are mostly semantic-preserving variants of already existing malware, which are generated via obfuscation methods. In this paper we propose and evaluate a machine learning based malware detection model using ensemble approach. We employ a strategy of ensemble where multiple feature sets generated from different n-gram sizes of opcode sequences are trained using a single classifier. Model predictions on the trained multi feature sets are weighted and combined on average to make a final verdict on whether a binary file is malicious or benign. To obtain optimal weight combination for the ensemble feature sets, we applied a grid search on a set of pre-defined weights in the range 0 to 1. With a balanced dataset of 2000 samples, an ensemble of n-gram opcode sequences of n sizes 1 and 2 with respective weight pair 0.3 and 0.7 yielded the best detection accuracy of 98.1% using random forest (RF) classifier. Ensemble n-gram sizes 2 and 3 obtained 99.7% as best precision using weight 0.5 for both models.
International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 24 (2021); pp. 19-31
International Association of Online Engineering (IAOE), Vienna, Austria
Copyright (c) 2021 Paul Ntim Yeboah, Stephen Kweku Amuquandoh, Haruna Balle Baz Musah
Smart Home Multi-Factor Authentication Using Face Recognition and One-Time Password on Smartphone
Recently, the adoption of smart home technology has been on the rise and becoming a trend for home residents. The development of Internet-of-Things (IoT) technology drives the smart home authentication system with biometric systems such as facial recognition, fingerprint, and voice control techniques. In the context of homeowners, security is always the primary concern. However, conventional home security and the existing smart home security system have some limitations. These techniques use single-factor authentication, which provides limited protection for home security. Therefore, this project proposed a design for smart home multi-factor authentication using facial recognition and a one-time password sent to smartphones for a home security system. Rapid application development was the methodology for conducting this study. A usability evaluation suggested that the proposed smart home multi-factor authentication is acceptable, but some usability issues can be improved in the future.
International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 24 (2021); pp. 32-48
Copyright (c) 2021 Yen Xin Tok, Norliza Katuk, Ahmad Suki Che Mohamed Arif
Development of a Learning Model of Quadric Surfaces With Augmented Reality and Didactic Engineering
Augmented reality (AR) is an emerging technology that has permeated different spheres of life, one of them is education, and specifically the teaching-learning process at different educational levels and objects of study. For this reason, this paper presents the development of a learning model of quadric surfaces mediated by a mobile AR application and based on didactic engineering. The model was applied to a group of environmental engineering students of the Catholic University of Manizales. To obtain information on the use of the application and the learning results obtained, some intervention instruments were developed. The students stated that the use of AR allowed them to better understand the concepts of quadric surfaces, even more so in a time of pandemic by COVID-19, where education was highly measured by ICTs.
International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 22 (2021); pp. 142-153
Copyright (c) 2021 Luis Hernando Carmona-Ramírez, Vladimir Henao-Céspedes
E-Module Design Using Kvisoft Flipbook Application Based on Mathematics Creative Thinking Ability for Junior High Schools
Mathematics learning innovations in teaching materials used in schools are still in the form of printed books from the government. In 4.0 era, the use of technology can be used to make teaching materials in the form of e-modules or electronic modules using the Kvisoft Flipbook application. The purpose of this study was to determine the validity, practicality, and student responses to the design of the number pattern e-module based on mathematical creative thinking skills using the kvisoft flipbook application so that it can be used as a learning resource for students both in the classroom learning process and independent learning. The method used in this study is a research and development (R&D) method using the ADDIE model. The data collection technique used is through a validation questionnaire, user practicality questionnaire and student response questionnaire to e-modules. The results of the study show that this e-module is very feasible to use with the results of material expert validation, media expert validation, user practicality, and student responses to e-modules. Based on the results of this study, the design of the e-module using the kvisoft flipbook maker application based on mathematical creative thinking skills is appropriate for use in the learning process for class VIII number pattern material
International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 04 (2022); pp. 116-136
Copyright (c) 2022 setiyani setiyani, stevanus Budi Waluya, Y.L Sukestiyarno and Adi Nurcahyono
Motor Learning Measuring Tools: A Design and Implementation Using Sensor Technology for Preschool Education
Motor learning in preschool education is very important to be a concern because it has an impact on the growth and development of children, and their mental abilities. This study aims to design and implement motor learning measuring tools using sensor technology for preschool education. This measuring instrument is expected to have a good performance in assessing motion in children, such as running, walking, and jumping. This type of research is development research with three stages, namely, phase I needs analysis and designing motor learning measuring tools, phase II, implementation of motor learning measuring tools, and developing motor learning measuring tools, phase III, evaluating of motor learning measuring tools and dissemination. However, this research is only limited to the stage of designing and implementing motor learning measuring tools. This research involved instrumentation experts and Kindergarten students, with a total sample of 65 students, using the purposive sampling technique. The result of this study is a sensor technology-based motor learning measuring instrument that can make an objective, easy and practical assessment. This measuring instrument can measure motor skills in locomotor movements, namely, running, walking, and jumping. Furthermore, the results of the implementation showed an increase in the motor skills of children aged for the better. So it is hoped that this measuring tool can be used by the wider community in an effort to improve preschool education learning.
International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 17 (2021); pp. 177-191
Copyright (c) 2021 Anton Komaini, Hendra Hidayat, . Ganefri, . Alnedral, . Gusril, Deby Tri Mario
DLMA_NEU: Digital Literacy Mobile Application for Children
This paper presents the design and implementation of DLMA_NEU, adigital literacy mobile application for Android that targets children between ages 7 and 18. It is a developmental study aimed at designing a digital literacy mobile application the study conducted in the following three phases: Phase 1. Literature review; mobile application store search, and interviewing experts in children’s digital literacy, Phase 2 Smart phones app development and Phase 3 Accessing the functionality and usability of the app. Thirty students from Near East College and 5 experts were used throughout the research process. The App is the first digital literacy mobile application in Turkish.DLMA_NEUemploys children’s opinions and also adds the interactive option. To use the application, a child is required to register first.And to provide representation, the application currently supports two languages (English and Turkish). The application supports chatting with friends, and educates children (via videos, text, cartoons and jokes) on how to interact online. The application also serves as an avenue for children to report cyber bullying and other online issues as well assimultaneously acquiring informationon internet usage habits. DMLA_NEU is currently at the testing stage by children from TRCN.
International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 08 (2022); pp. 49-64
Copyright (c) 2022 Sezer Kanbul, Umar Mohammed Kani, mohammed mukhtar magaji
Leveraging Sensor Fusion and Sensor-Body Position for Activity Recognition for Wearable Mobile Technologies
Smart devices like smartphones and smartwatches have made this world smarter. These wearable devices are created through complex research methodologies to make them more usable and interactive with its user. Various interactive mobile applications such as augmented reality (AR), virtual reality (VR) or mixed reality (MR) applications solely depend on the in-built sensors of the smart devices. A lot of facilities can be taken from these devices with sensors such as accelerometer and gyroscope. Different physical activities such as walking, jogging, sitting, etc., can be important for analysis like health state prediction and duration of exercise by using those sensors based on artificial intelligence. In this paper, we have implemented machine learning and deep learning algorithms to detect and recognize eight activities namely, walking, jogging, standing, walking upstairs, walking downstairs, sitting, sitting-in-a-car and cycling; with a maximum of 99.3% accuracy. A few activities are almost similar in action, such as sitting and sitting-in-a-car, but difficult to distinguish; which makes it more challenging to predict tasks. In this paper, we have hypothesized that with more sensors (sensor fusion) and data collection points (sensor-body positions) a wide range of activities can be recognized and the recognition accuracies can be increased. Finally, we showed that the combination of all the sensors data of both pocket/waist and wrist can be used to recognize a wide range of activities accurately. The possibility of using the proposed methodologies for futuristic mobile technologies is quite significant. The adaptation of most recent deep learning algorithms such as convolutional neural network (CNN) and bi-directional Long Short Time Memory (Bi-LSTM) demonstrated high credibility of the methods presented as experimentation.
International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 17 (2021); pp. 141-155
Copyright (c) 2021 Ashraful Alam, Anik Das, Md. Shahriar Tasjid, Ahmed Al Marouf
The Development of POTENSIA; The Android-Based Psychological Application for Mapping and Assessments of Student Mental Health During the COVID-19 Pandemic
Students experience various essential changes related to their psychological conditions during their education in college. Students' adaptability to the demands of these changes will give birth to new skills for the next stage of psychological development. However, academic stress, social problems, career, and personal-emotional problems can hinder the productivity and development of students in terms of mental health. This issue increased with the new-normal life during the COVID-19 pandemic, which also impacted the education process. For this reason, it is necessary to have a mobile-based online psychological assessment to map the mental health conditions of students during the pandemic. This study aims to develop and validate an Android-based online psychological assessment application to map students' mental health conditions. This study involved ten experts in counseling and software development, five counselors, and 638 users of the POTENSIA application. According to application development needs, data analysis using Aiken's V coefficient test, Confirmatory Factor Analysis (CFA), and Rasch Model Analysis. The results of the study prove that the application is considered valid and practical to use. The effectiveness of the application is considered very good in mapping the mental health conditions of students.
International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 16 (2021); pp. 16-33
Copyright (c) 2021 Zadrian Ardi, Hendra Hidayat, Ifdil Ifdil, Yan Guspriadi, Siti Azizi Fauziyyah
A Review of Virtual Reality Applications in an Educational Domain
The use of virtual reality (VR) applications has grown tremendously in recent years. This paper focuses on the review of existing virtual reality applications in higher educational institutions. The VR applications are still not widely used although it helps students in their learning process and enhances their performance. Moreover, some factors which lead to the limited use of virtual reality are lack of communication, delay in technology development, and weak acquisition of knowledge etc. This paper provides a comprehensive overview of virtual reality applications in educational institutions. The reviewed articles are taken from databases such as Science Direct, Ebscohost, and Scopus. Furthermore, the reviewed eighteen articles are published between 2016 and 2021. The study analyzed the reviewed articles based on different factors such as fields, purpose, targets, methods, citations, factors and limitations. The findings revealed that virtual reality applications can play an important role in the education domain. The reviewed articles highlighted the significant contribution of virtual reality applications in the education domain and their impact on the students' performance. Moreover, the study revealed the important factors used in VR environments such as ease of use, efficiency, interactive environments, effectiveness, and learning environments.
International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 22 (2021); pp. 99-110
Copyright (c) 2021 Ghaliya Alfarsi, Azmi bin Mohd. Yusof, Awanis Romli, Mohd Ezanee Bin Rsuli, Ragad Tawafak
A Problem-Based Learning (PBL) and Teaching Model using a Cloud-Based Constructivist Learning Environment to Enhance Thai Undergraduate Creative Thinking and Digital Media Skills
The objective of this research was to develop a Problem-Based Learning (PBL) Model which used a cloud-based constructivist learning environment to enhance Thai undergraduate creative thinking and digital media skills. Initially using a mixed-methods approach, a five-step model was conceptualized. Thereafter, a panel of five academic experts gave input into the model’s design from which the model was expanded to include six related learning environments. The instrument used in the research was a problem-based assessment form. Data collection was carried out utilizing group chats and analyzed using descriptive statistics including the mean and standard deviation. The results of the study revealed that the initial model contained five steps including (1) problem identification, (2), problem analysis, (3) research, (4) presentations, and (5) summary and evaluation, which is integrated into the model’s additional six learning environment elements. These six learning environments were (1) problem-based, (2) resources, (3) cognitive tools, (4) collaboration, (5) scaffolding, and finally, (6) coaching. When applying the proposed model and related environments, there was a consensus from the experts that the model had excellent suitability and can be used as a model for teaching and learning at the bachelor's degree level.
International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 22 (2021); pp. 68-83