2022 2nd International Conference in Information and Computing Research (iCORE)最新文献_第2页

Hybrid Android Malware Detection Model using Machine learning Algorithms 基于机器学习算法的混合Android恶意软件检测模型

2022 2nd International Conference in Information and Computing Research (iCORE) Pub Date : 2022-12-01 DOI: 10.1109/iCORE58172.2022.00032

A. K. Lee Yam, J. M. Ballesta, Joyce Ann H. Lanceta, M. K. Mogol, Rogel M. Labanan

{"title":"Hybrid Android Malware Detection Model using Machine learning Algorithms","authors":"A. K. Lee Yam, J. M. Ballesta, Joyce Ann H. Lanceta, M. K. Mogol, Rogel M. Labanan","doi":"10.1109/iCORE58172.2022.00032","DOIUrl":"https://doi.org/10.1109/iCORE58172.2022.00032","url":null,"abstract":"Malware in general, is a serious threat that affects a wide range of users on an everyday basis. Since Android is the most popular mobile operating system, it became a target for fraudulent and malicious activities caused by malware developers that can result in devastating effects. With that, many Android malware applications continue to come into existence and throughout the years, several solutions have emerged, while Android malware has also smartly improved its capabilities to avoid being detected. Hence, a stronger detection model should be developed by improving the current existing Android malware detection techniques. The study created a multi-class hybrid Android malware detection model which investigates the effectiveness of combining system permissions as the static feature and network traffic features as the dynamic feature whereas K-Nearest Neighbor, Random Forest, and XGBoost as the machine learning classifying algorithms. The said classifiers are compared based on various evaluation metrics such as recall, precision, accuracy, F1-score, and Receiver Operating Characteristics Curve (ROC). All classifiers produced a result higher than 90% in accuracy, precision, recall, specificity, and F1-Score. Meanwhile, it is also revealed that our created model can compete with other models that are existing from the previous works wherein the best model is the Random Forest setup C which has a total of 18 features. The said model got a 98.3% recall, 98.4% precision, 98.3% accuracy, 98.3% F1-Score, and 99.9% ROC-AUC.","PeriodicalId":229986,"journal":{"name":"2022 2nd International Conference in Information and Computing Research (iCORE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133445488","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}

引用次数: 0

Hope, Gratitude, and Optimism may contribute to Student Flourishing during COVID-19 Pandemic 希望、感恩和乐观可能有助于学生在COVID-19大流行期间茁壮成长

2022 2nd International Conference in Information and Computing Research (iCORE) Pub Date : 2022-12-01 DOI: 10.1109/iCORE58172.2022.00061

Rickson John Banares, John Mark Distor, Ian I. Llenares

引用次数: 0

MASA: A Mobile and Web Application Framework for A G2C Integrated Municipal Disaster Risk Reduction and Management System for the Community of Rodriguez, Rizal MASA: Rizal Rodriguez社区G2C综合城市灾害风险减少和管理系统的移动和Web应用框架

2022 2nd International Conference in Information and Computing Research (iCORE) Pub Date : 2022-12-01 DOI: 10.1109/iCORE58172.2022.00057

Mainard Justine D. Anastacio, Gerwin M. Bondoc, Karen D. Mamaradlo, Edward Matthew T. Sanmocte, Neo L. Viray, Emeliza R. Yabut, Frederick E. Dador

引用次数: 0

Message from the Program Chair: iCORE 2022 项目主席寄语:iCORE 2022

2022 2nd International Conference in Information and Computing Research (iCORE) Pub Date : 2022-12-01 DOI: 10.1109/icore58172.2022.00008

Angelique Lacasandile

引用次数: 0

Classifying Solar Glint in an Intertidal Zone 潮间带的太阳闪光分类

2022 2nd International Conference in Information and Computing Research (iCORE) Pub Date : 2022-12-01 DOI: 10.1109/iCORE58172.2022.00068

B. Arellano, P. Astillo, Van Patiluna

引用次数: 0

Collaborators, Sponsors, and Partners: iCORE 2022 合作者，赞助商和合作伙伴:iCORE 2022

2022 2nd International Conference in Information and Computing Research (iCORE) Pub Date : 2022-12-01 DOI: 10.1109/icore58172.2022.00018

引用次数: 0

A Study on the Usability of Text Analysis on Web Artifacts for Digital Forensic Investigation 数字司法调查中网络文物文本分析的可用性研究

2022 2nd International Conference in Information and Computing Research (iCORE) Pub Date : 2022-12-01 DOI: 10.1109/iCORE58172.2022.00030

Rogel M. Labanan, Nympha Delaila S. Muñoz

{"title":"A Study on the Usability of Text Analysis on Web Artifacts for Digital Forensic Investigation","authors":"Rogel M. Labanan, Nympha Delaila S. Muñoz","doi":"10.1109/iCORE58172.2022.00030","DOIUrl":"https://doi.org/10.1109/iCORE58172.2022.00030","url":null,"abstract":"Digital forensic investigation is not new in the field of forensic science which faced several challenges over the past decades. Due to the complexity of performing investigative inquiry on a large amount of data on digital evidence, the choice of appropriate forensic tools, skills, and expertise poses issues and challenges in digital forensic investigation. In this study, an effective approach to performing investigative inquiry based on web browser artifacts was pursued by utilizing text analysis to identify the user's characteristics. Information extraction was performed from a publicly available dataset by extracting, analyzing web browser artifacts, and performing in-house data labeling. Data labeling of the processed web artifacts was conducted and evaluated by an expert volunteer for investigative purposes to achieve the goal of persona characteristic identification of a computer user. Thus, helping investigators interpret textual-based evidence fast even though with a notable amount of data being analyzed versus when human-based analysis is manually performed in the pursuit of solving crimes committed using the internet.","PeriodicalId":229986,"journal":{"name":"2022 2nd International Conference in Information and Computing Research (iCORE)","volume":"152 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116540756","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}

引用次数: 0

CONTRAST: An animated short film about rescue against black hat hackers 对比:一部关于营救黑帽黑客的动画短片

2022 2nd International Conference in Information and Computing Research (iCORE) Pub Date : 2022-12-01 DOI: 10.1109/iCORE58172.2022.00028

Ely James Bala, Adrian Fernando Costales, Jasper Kent Yñota, Marilou N. Jamis, Eliseo Q. Ramirez

引用次数: 0

Program Flow 程序流

2022 2nd International Conference in Information and Computing Research (iCORE) Pub Date : 2022-12-01 DOI: 10.1007/978-1-4302-1136-5_4

B. Bischof

引用次数: 0

Evaluation of the Effect of Varying Digital Elevation Model (DEM) Resolutions on Hydrologic Model Performance of a Tropical Watershed 不同数字高程模型(DEM)分辨率对热带流域水文模型性能影响的评价

2022 2nd International Conference in Information and Computing Research (iCORE) Pub Date : 2022-12-01 DOI: 10.1109/iCORE58172.2022.00050

F. Santos, Francis Tevar, Khrizelle Angelique Sablan, Eugenia Lagmay

{"title":"Evaluation of the Effect of Varying Digital Elevation Model (DEM) Resolutions on Hydrologic Model Performance of a Tropical Watershed","authors":"F. Santos, Francis Tevar, Khrizelle Angelique Sablan, Eugenia Lagmay","doi":"10.1109/iCORE58172.2022.00050","DOIUrl":"https://doi.org/10.1109/iCORE58172.2022.00050","url":null,"abstract":"Remote sensing has been used in the industry to understand present and future scenarios and promote better management practices of different systems. Hydrologic modeling as a tool can be used to represent and predict watershed behavior considering the different changes in an area due to continuous developments such as urbanization and population growth. However, the accuracy and performance of hydrologic models largely depends on the quality of input that will be used, thus the need to establish the relationship between input data and model performance is very important in coming up with decision-support information that will be beneficial in the management of such systems. This study aimed to evaluate the effect of varying Digital Elevation Model (DEM) resolutions on the hydrologic model performance of a tropical watershed in terms of statistical parameters namely the Nash-Sutcliffe Efficiency (NSE) and Percent Bias (PBIAS). A hydrologic model of the Davao River Basin was set up using HEC-HMS and was calibrated and validated before comparing the effects of varying DEM resolutions. Results reveal that as the DEM resolution gets larger, it leads to lower model performance due to less fine resolutions of elevation detail, flow directions, and flow accumulations that define streams and drainage lines. These findings can help hydrology modelers in choosing inputs from remote sensing to improve model performance and increase the reliability of their models that can serve as baseline information for policy making for better watershed management.","PeriodicalId":229986,"journal":{"name":"2022 2nd International Conference in Information and Computing Research (iCORE)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128787032","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}

引用次数: 0