Priyangka John Jayaraj, Masitah Ghazali, Abubaker Gaber
Students especially at universities undergo a lot of pressure and stress, and mental health is something that must not be taken lightly, especially at the time of pandemic as we are experiencing now. The need for us to look into the mental health is constantly reminded everywhere. There are a lot of ways to reduce stress such as meditation, getting involved in sports and one of the most practiced methods is by listening to music. Music has been indeed proved to have positive effects on humans and that it aids healing process such as binaural beats and Solfeggio frequency. These frequencies of music have impact towards the brainwave. This study reports on how the design thinking process was used to better identify the most suitable means on integrating mobile Brain-Computer Interface (BCI) as an application to know the impacts of different type of frequencies of music on the human brain to reduce stress. Besides suggesting a generic guideline to develop an application for mobile BCI, this study also provides us insights into the readiness of mobile BCI as an application for common usage.
{"title":"Relax App: Designing Mobile Brain-Computer Interface App to Reduce Stress among Students","authors":"Priyangka John Jayaraj, Masitah Ghazali, Abubaker Gaber","doi":"10.11113/ijic.v11n2.310","DOIUrl":"https://doi.org/10.11113/ijic.v11n2.310","url":null,"abstract":"Students especially at universities undergo a lot of pressure and stress, and mental health is something that must not be taken lightly, especially at the time of pandemic as we are experiencing now. The need for us to look into the mental health is constantly reminded everywhere. There are a lot of ways to reduce stress such as meditation, getting involved in sports and one of the most practiced methods is by listening to music. Music has been indeed proved to have positive effects on humans and that it aids healing process such as binaural beats and Solfeggio frequency. These frequencies of music have impact towards the brainwave. This study reports on how the design thinking process was used to better identify the most suitable means on integrating mobile Brain-Computer Interface (BCI) as an application to know the impacts of different type of frequencies of music on the human brain to reduce stress. Besides suggesting a generic guideline to develop an application for mobile BCI, this study also provides us insights into the readiness of mobile BCI as an application for common usage.","PeriodicalId":50314,"journal":{"name":"International Journal of Innovative Computing Information and Control","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84802357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Current timetable scheduling system in School of Computing(SC), Universiti Teknologi Malaysia(UTM) is done manually which consumes time and human effort. In this project, a Genetic Algorithm (GA) approach is proposed to aid the timetable scheduling process. GA is a heuristic search algorithm which finds the best solution based on current individual characteristics. Using GA and scheduling info such as rooms available and timeslots needed, it is shown that scheduling can be done more efficiently, with less time, effort and errors. As a testbed, a web application is developed to maintain records needed and generate timetables. Introduction of GA helps in generating a timetable automatically based on information such as rooms, subjects, lecturers, student group and timeslot. GA reduces human error and human efforts in the timetable scheduling process.
{"title":"Timetable Scheduling System using Genetic Algorithm for School of Computing (tsuGA)","authors":"Hazinah Kutty Mammi, Lim Ying Ying","doi":"10.11113/ijic.v11n2.342","DOIUrl":"https://doi.org/10.11113/ijic.v11n2.342","url":null,"abstract":"Current timetable scheduling system in School of Computing(SC), Universiti Teknologi Malaysia(UTM) is done manually which consumes time and human effort. In this project, a Genetic Algorithm (GA) approach is proposed to aid the timetable scheduling process. GA is a heuristic search algorithm which finds the best solution based on current individual characteristics. Using GA and scheduling info such as rooms available and timeslots needed, it is shown that scheduling can be done more efficiently, with less time, effort and errors. As a testbed, a web application is developed to maintain records needed and generate timetables. Introduction of GA helps in generating a timetable automatically based on information such as rooms, subjects, lecturers, student group and timeslot. GA reduces human error and human efforts in the timetable scheduling process.","PeriodicalId":50314,"journal":{"name":"International Journal of Innovative Computing Information and Control","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82444380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-01DOI: 10.24507/IJICIC.17.03.1055
Yuto Omae, Yohei Kakimoto, J. Toyotani, Kazuyuki Hara, Y. Gon, Hirotaka Takahashi
As of November 2020, the COVID-19 pandemic continues to rage across the world. One of the measures that has been taken to curb the spread of the virus is blanket stay-at-home orders. Staying at home significantly limits close contact with others and can, thus, decrease the number of new cases. However, if people refrain from going out, this will cause significant economic damage. For this reason, some people think that these orders should be revoked after a short period of time, and people should get out more often. However, if blanket stay-at-home restrictions are lifted before a significant decrease is seen in the number of new cases, the number of infected people is likely to increase within a short period. This will, in turn, hasten the next round of blanket stay-at-home orders and lead to a further reduction in people who can leave their home. Against this backdrop, this study examines below phenomena, through a multi-agent simulation. The early removal strategies of stay-at-home orders for increasing the number of people leaving their homes have the effect of both increasing and decreasing the number of such people. Therefore, we consider the strategies do not lead to a sufficient increase in the overall number of people leaving their homes. To examine these phenomena, we conducted the simulations that consist of six scenarios with the different removal condition of stay-at-home orders. As a result, we could confirm that when more removal conditions of stay-at-home orders were eased, the tendencies of more number of infected people and death people were increasing with some exceptions. In contrast, there were almost no differences among the numbers of people leaving their home of these scenarios. Based on the results, we also examined the possibility of a strategy that covers both infected people and the number of people allowed to leave their homes.
{"title":"IMPACT OF REMOVAL STRATEGIES OF STAY-AT-HOME ORDERS ON THE NUMBER OF COVID-19 INFECTORS AND PEOPLE LEAVING THEIR HOMES","authors":"Yuto Omae, Yohei Kakimoto, J. Toyotani, Kazuyuki Hara, Y. Gon, Hirotaka Takahashi","doi":"10.24507/IJICIC.17.03.1055","DOIUrl":"https://doi.org/10.24507/IJICIC.17.03.1055","url":null,"abstract":"As of November 2020, the COVID-19 pandemic continues to rage across the world. One of the measures that has been taken to curb the spread of the virus is blanket stay-at-home orders. Staying at home significantly limits close contact with others and can, thus, decrease the number of new cases. However, if people refrain from going out, this will cause significant economic damage. For this reason, some people think that these orders should be revoked after a short period of time, and people should get out more often. However, if blanket stay-at-home restrictions are lifted before a significant decrease is seen in the number of new cases, the number of infected people is likely to increase within a short period. This will, in turn, hasten the next round of blanket stay-at-home orders and lead to a further reduction in people who can leave their home. Against this backdrop, this study examines below phenomena, through a multi-agent simulation. The early removal strategies of stay-at-home orders for increasing the number of people leaving their homes have the effect of both increasing and decreasing the number of such people. Therefore, we consider the strategies do not lead to a sufficient increase in the overall number of people leaving their homes. To examine these phenomena, we conducted the simulations that consist of six scenarios with the different removal condition of stay-at-home orders. As a result, we could confirm that when more removal conditions of stay-at-home orders were eased, the tendencies of more number of infected people and death people were increasing with some exceptions. In contrast, there were almost no differences among the numbers of people leaving their home of these scenarios. Based on the results, we also examined the possibility of a strategy that covers both infected people and the number of people allowed to leave their homes.","PeriodicalId":50314,"journal":{"name":"International Journal of Innovative Computing Information and Control","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84001672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Noor Azzah Said, S. Seman, Dilla Syadia Ab Latiff, Siti Noorsuriani Ma’o, N. M. Mozie
The wide-ranging features of a smartwatch have driven the rapid growth of the smartwatch market as they pique the users’ interests by offering interactive technology that simultaneously promotes fitness and tracks health. Nevertheless, the factors influencing smartwatch adoption among individuals are yet to be comprehended despite the ever-growing popularity of smartwatch usage. Hence, to understand the possible factors in detail, a research model is proposed to indicate the influential underlying factors relative to smartwatch adoption in the Malaysian populace. This study will examine the four proposed dimensions of perceived benefits, healthology, IT innovation, and smartwatch as luxury products. Online questionnaires will be used to collect the research data, while SPSS will be used to run both preliminary research and descriptive analyses, PLS-SEM will be used to further analyze the model.
{"title":"Consumers’ Behavioral Intention Towards Smartwatch Adoption in Malaysia: A Concept Paper","authors":"Noor Azzah Said, S. Seman, Dilla Syadia Ab Latiff, Siti Noorsuriani Ma’o, N. M. Mozie","doi":"10.11113/IJIC.V11N1.281","DOIUrl":"https://doi.org/10.11113/IJIC.V11N1.281","url":null,"abstract":"The wide-ranging features of a smartwatch have driven the rapid growth of the smartwatch market as they pique the users’ interests by offering interactive technology that simultaneously promotes fitness and tracks health. Nevertheless, the factors influencing smartwatch adoption among individuals are yet to be comprehended despite the ever-growing popularity of smartwatch usage. Hence, to understand the possible factors in detail, a research model is proposed to indicate the influential underlying factors relative to smartwatch adoption in the Malaysian populace. This study will examine the four proposed dimensions of perceived benefits, healthology, IT innovation, and smartwatch as luxury products. Online questionnaires will be used to collect the research data, while SPSS will be used to run both preliminary research and descriptive analyses, PLS-SEM will be used to further analyze the model.","PeriodicalId":50314,"journal":{"name":"International Journal of Innovative Computing Information and Control","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77936383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Ahmad, Mohd Razif Mohamad Yunus, Ahmad Khairi Abd. Wahab, N. Ibrahim, I. I. Mohamad
A mangrove vulnerability assessment's goal is to generate recommendations for reducing vulnerability. Mangrove forests, which grow in the intertidal zones and estuary mouths between land and sea, exist in two worlds at once. Mangroves provide crucial stability for preventing shoreline erosion. It helps to maintain land level by sediment accretion while balancing sediment loss by serving as buffers catching materials washed downstream. Climate change, especially the associated increase in sea level, poses a serious threat to mangrove coastal areas, and it is critical to devise strategies to mitigate vulnerability through strategic management planning. Experts are attempting to determine how mangroves have been affected by climate change and rising sea levels. How do we forecast the consequences and effect of rising sea levels on mangroves, and then adjust and mitigate them accordingly? Vulnerability implies the risk of being assaulted or hurt, whether physically or emotionally. Environmental vulnerability is a feature of impact exposure as well as ecological systems' susceptibility and adaptive potential to environmental tensors. Researchers in this study ranked mangrove vulnerability on a scale of 1 to 5, with 1 indicating very low vulnerability and 5 indicating very high vulnerability. The Physical Mangrove Index (PMI), Biological Mangrove Index (BMI), and Threat Mangrove Index (HMI) are the three major groups of the Mangrove Vulnerability Index (MVI)). The study's main objective is to develop an accurate and efficient GIS database system that has been formulated and tested or implemented in three (3) separate areas, namely, Kukup Island, Tanjung Piai, and Sungai Pulai. The study develops a GIS-based Mangrove Vulnerability Index (MVI) Model for a selected ecosystem, and highlights mangrove vulnerability by ranking them from least to most vulnerable using parameters. The study also provides a forecast for the mangrove loss in the next 50 and 100 years, as well as to classify areas where mangroves are most vulnerable.
{"title":"Mapping the Mangrove Vulnerability Index Using Geographical Information System","authors":"F. Ahmad, Mohd Razif Mohamad Yunus, Ahmad Khairi Abd. Wahab, N. Ibrahim, I. I. Mohamad","doi":"10.11113/IJIC.V11N1.309","DOIUrl":"https://doi.org/10.11113/IJIC.V11N1.309","url":null,"abstract":"A mangrove vulnerability assessment's goal is to generate recommendations for reducing vulnerability. Mangrove forests, which grow in the intertidal zones and estuary mouths between land and sea, exist in two worlds at once. Mangroves provide crucial stability for preventing shoreline erosion. It helps to maintain land level by sediment accretion while balancing sediment loss by serving as buffers catching materials washed downstream. Climate change, especially the associated increase in sea level, poses a serious threat to mangrove coastal areas, and it is critical to devise strategies to mitigate vulnerability through strategic management planning. Experts are attempting to determine how mangroves have been affected by climate change and rising sea levels. How do we forecast the consequences and effect of rising sea levels on mangroves, and then adjust and mitigate them accordingly? Vulnerability implies the risk of being assaulted or hurt, whether physically or emotionally. Environmental vulnerability is a feature of impact exposure as well as ecological systems' susceptibility and adaptive potential to environmental tensors. Researchers in this study ranked mangrove vulnerability on a scale of 1 to 5, with 1 indicating very low vulnerability and 5 indicating very high vulnerability. The Physical Mangrove Index (PMI), Biological Mangrove Index (BMI), and Threat Mangrove Index (HMI) are the three major groups of the Mangrove Vulnerability Index (MVI)). The study's main objective is to develop an accurate and efficient GIS database system that has been formulated and tested or implemented in three (3) separate areas, namely, Kukup Island, Tanjung Piai, and Sungai Pulai. The study develops a GIS-based Mangrove Vulnerability Index (MVI) Model for a selected ecosystem, and highlights mangrove vulnerability by ranking them from least to most vulnerable using parameters. The study also provides a forecast for the mangrove loss in the next 50 and 100 years, as well as to classify areas where mangroves are most vulnerable.","PeriodicalId":50314,"journal":{"name":"International Journal of Innovative Computing Information and Control","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80603667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-01DOI: 10.24507/IJICIC.17.01.167
C. Kang
{"title":"A DEVICE-LIFE MODEL FOR RELIABILITY DEMONSTRATION TEST FOR A PRODUCT MADE UP OF A LARGE ARRAY OF ELECTRONIC DEVICES","authors":"C. Kang","doi":"10.24507/IJICIC.17.01.167","DOIUrl":"https://doi.org/10.24507/IJICIC.17.01.167","url":null,"abstract":"","PeriodicalId":50314,"journal":{"name":"International Journal of Innovative Computing Information and Control","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80422484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.24507/ijicic.17.05.1513
Mauritsius T. Wirianto
The advancement of technology opens opportunities for implementation that benefits the social and economic aspects of human life. Given the latest achievement in face recognition technology that surpasses human ability to identify a face, the research explores the application of this scientific discovery in the Indonesian context during the current pandemic situation. Toward the effort to achieve this goal, the study develops an Indonesia Labelled Face in the Wild (ILFW) that collects face images of famous Indonesian people from the Internet in various poses, expressions, lighting/illumination, and fashion attribute. In response to the recent COVID-19 pandemic situation, the study also augmented a face mask to a portion of collected face images. Using DCNN, RetinaFace as the face detection model, and Arcface loss function, and adopting CRISP DM, the research contributes by providing a method to develop a face dataset with 1,200 identities, and face recognition model with 92 percent accuracy and be able to recognize Indonesian people with a face mask. The researchers also recommend use cases for realtime face recognition in the business organization. It uses CCTV to perform automatic attendance, security surveillance, and employee location tracking and exhibits deployment consideration. Future research could increase the accuracy of face recognition model by adding more identities to the face dataset.
{"title":"THE DEVELOPMENT OF FACE RECOGNITION MODEL IN INDONESIA PANDEMIC CONTEXT BASED ON DCNN AND ARCFACE LOSS FUNCTION","authors":"Mauritsius T. Wirianto","doi":"10.24507/ijicic.17.05.1513","DOIUrl":"https://doi.org/10.24507/ijicic.17.05.1513","url":null,"abstract":"The advancement of technology opens opportunities for implementation that benefits the social and economic aspects of human life. Given the latest achievement in face recognition technology that surpasses human ability to identify a face, the research explores the application of this scientific discovery in the Indonesian context during the current pandemic situation. Toward the effort to achieve this goal, the study develops an Indonesia Labelled Face in the Wild (ILFW) that collects face images of famous Indonesian people from the Internet in various poses, expressions, lighting/illumination, and fashion attribute. In response to the recent COVID-19 pandemic situation, the study also augmented a face mask to a portion of collected face images. Using DCNN, RetinaFace as the face detection model, and Arcface loss function, and adopting CRISP DM, the research contributes by providing a method to develop a face dataset with 1,200 identities, and face recognition model with 92 percent accuracy and be able to recognize Indonesian people with a face mask. The researchers also recommend use cases for realtime face recognition in the business organization. It uses CCTV to perform automatic attendance, security surveillance, and employee location tracking and exhibits deployment consideration. Future research could increase the accuracy of face recognition model by adding more identities to the face dataset.","PeriodicalId":50314,"journal":{"name":"International Journal of Innovative Computing Information and Control","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87271986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.24507/IJICIC.17.04.1191
Yues Tadrik Hafiyan, Afiahayati, Ryna Dwi Yanuaryska, Edgar Anarossi, V. Sutanto, J. Triyanto, Y. Sakakibara
DNA is the information carrier in cells that are susceptible to damage, either naturally or due to external influences. Comet assays are often used by experts to determine the level of damage. However, the comet assays gathered with swab technique (Buccal Mucosa for example) often produced a higher noise level compared to ones that are cell-cultured, thus, making the analysis process more difficult. In this research, we proposed a novel way to assess the degree of damage from Buccal Mucosa comet assays using a hybrid of Convolutional Neural Network (CNN) and Extreme Learning Machine (ELM). The CNN was used to capture and extract spatial relation from every comet, while the ELM was used as a classifier that can minimize the risk of vanishing gradient. Our hybrid CNN-ELM model scored 96.96% for accuracy, while the VGG16-ELM scored 88.4% and ResNet50-ELM 76.8%.
{"title":"A hybrid convolutional neural network-extreme learning machine with augmented dataset for dna damage classification using comet assay from buccal mucosa sample","authors":"Yues Tadrik Hafiyan, Afiahayati, Ryna Dwi Yanuaryska, Edgar Anarossi, V. Sutanto, J. Triyanto, Y. Sakakibara","doi":"10.24507/IJICIC.17.04.1191","DOIUrl":"https://doi.org/10.24507/IJICIC.17.04.1191","url":null,"abstract":"DNA is the information carrier in cells that are susceptible to damage, either naturally or due to external influences. Comet assays are often used by experts to determine the level of damage. However, the comet assays gathered with swab technique (Buccal Mucosa for example) often produced a higher noise level compared to ones that are cell-cultured, thus, making the analysis process more difficult. In this research, we proposed a novel way to assess the degree of damage from Buccal Mucosa comet assays using a hybrid of Convolutional Neural Network (CNN) and Extreme Learning Machine (ELM). The CNN was used to capture and extract spatial relation from every comet, while the ELM was used as a classifier that can minimize the risk of vanishing gradient. Our hybrid CNN-ELM model scored 96.96% for accuracy, while the VGG16-ELM scored 88.4% and ResNet50-ELM 76.8%.","PeriodicalId":50314,"journal":{"name":"International Journal of Innovative Computing Information and Control","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78416448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The quality or state of being secure is the crucial concern of our daily life usage of any network. However, with the rapid breakthrough in network technology, attacks are becoming more trailblazing than defenses. It is a daunting task to design an effective and reliable intrusion detection system (IDS), while maintaining minimal complexity. The concept of machine learning is considered an important method used in intrusion detection systems to detect irregular network traffic activities. The use of machine learning is the current trend in developing IDS in order to mitigate false positives (FP) and False Negatives (FN) in the anomalous IDS. This paper targets to present a holistic approach to intrusion detection system and the popular machine learning techniques applied on IDS systems, bearing In mind the need to help research scholars in this continuous burgeoning field of Intrusion detection (ID).
{"title":"A Review on Network Intrusion Detection System Using Machine Learning","authors":"B. Kagara, M. Md. Siraj","doi":"10.11113/ijic.v10n1.252","DOIUrl":"https://doi.org/10.11113/ijic.v10n1.252","url":null,"abstract":"The quality or state of being secure is the crucial concern of our daily life usage of any network. However, with the rapid breakthrough in network technology, attacks are becoming more trailblazing than defenses. It is a daunting task to design an effective and reliable intrusion detection system (IDS), while maintaining minimal complexity. The concept of machine learning is considered an important method used in intrusion detection systems to detect irregular network traffic activities. The use of machine learning is the current trend in developing IDS in order to mitigate false positives (FP) and False Negatives (FN) in the anomalous IDS. This paper targets to present a holistic approach to intrusion detection system and the popular machine learning techniques applied on IDS systems, bearing In mind the need to help research scholars in this continuous burgeoning field of Intrusion detection (ID).","PeriodicalId":50314,"journal":{"name":"International Journal of Innovative Computing Information and Control","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2020-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83068992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.1007/978-981-15-5959-4
Chaojie Yang, Yan Pei, Jia-Wei Chang Editors, B. K. Panigrahi
{"title":"Innovative Computing: IC 2020","authors":"Chaojie Yang, Yan Pei, Jia-Wei Chang Editors, B. K. Panigrahi","doi":"10.1007/978-981-15-5959-4","DOIUrl":"https://doi.org/10.1007/978-981-15-5959-4","url":null,"abstract":"","PeriodicalId":50314,"journal":{"name":"International Journal of Innovative Computing Information and Control","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83984284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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