{"title":"A Review of Smishing Attaks Mitigation Strategies","authors":"D. Njuguna, J. Kamau, D. Kaburu","doi":"10.24203/ijcit.v11i1.201","DOIUrl":"https://doi.org/10.24203/ijcit.v11i1.201","url":null,"abstract":"Mobile Smishing crime has continued to escalate globally due to technology enhancements and people's growing dependence on smartphones and other technologies. SMS facilitates the distribution of crucial information that is principally important for non-digital savvy users who are typically underprivileged. Smishing, often known as SMS phishing, entails transmitting deceptive text messages to lure someone into revealing individual information or installing malware. The number of incidences of smishing has increased tremendously as the internet and cellphones have spread to even the most remote regions of the globe.","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124181804","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}
{"title":"Classification of Facial Expression Using Principal Component Analysis (PCA) Method and Support Vector Machine (SVM)","authors":"Intan Setiawati, Enny Itje Sela","doi":"10.24203/ijcit.v11i1.205","DOIUrl":"https://doi.org/10.24203/ijcit.v11i1.205","url":null,"abstract":"Classification is a process to assert an object into one of defined categories. This study examines the classification of recognition of student’s facial expression during digital learning –indifferent and serious expression. The dataset used was from a vocational school -SMK Muhammadiyah 2 Bantul. This study used the combination of algorithm: Principal Component Analysis (PCA) and Support Vector Machine (SVM) to increase the accuracy. This study aims at comparing the performance of combination of two algorithm: (PCA to SVM) and (PCA to k-NN). The result states that the combination of PCA-SVM algorithm is higher than the combination of PCA-k-NN algorithm with the average accuracy of 96% and 89%.","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124966224","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}
{"title":"Combining Image Processing Techniques and Mobile Sensor Information for Marker-less Augmented Reality Based Reconstruction","authors":"I. S. Weerakkody, K. Sandaruwan, N. Kodikara","doi":"10.24203/ijcit.v11i1.186","DOIUrl":"https://doi.org/10.24203/ijcit.v11i1.186","url":null,"abstract":"Marker-less Augmented Reality(AR) based recon- struction using mobile devices, is a near impossible task. When considering vision based tracking approaches, it is due to the lack of processing power in mobile devices and when considering mobile sensor based tracking approaches, it is due to the lack of accuracy in mobile Global Positioning System(GPS).\u0000In order to address this problem this research presents a novel approach which combines image processing techniques and mobile sensor information which can be used to perform precise position localization in order to perform augmented reality based reconstruction using mobile devices. The core of this proposed methodology is tightly bound with the image processing technique which is used to identify the object scale in a given image, which is taken from the user’s mobile device. Use of mobile sensor information was to classify the most optimal locations for a given particular user location.\u0000This proposed methodology has been evaluated against the results obtained using 10cm accurate Real-Time Kinematic(RTK) device and against the results obtained using only the Assisted Global Positioning System(A-GPS) chips in mobile devices. Though this proposed methodology require more processing time than A-GPS chips, the accuracy level of this proposed methodology outperforms that of A-GPS chips and the results of the experiments carried out further convince that this proposed methodology facilitates improving the accuracy of position local- ization for augmented reality based reconstruction using mobile devices under certain limitations.","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123550499","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}
{"title":"A Framework for Verification in Contactless Secure Physical Access Control and Authentication Systems","authors":"B. Mwangi","doi":"10.24203/ijcit.v11i1.202","DOIUrl":"https://doi.org/10.24203/ijcit.v11i1.202","url":null,"abstract":"Biometrics is one of the very popular techniques in user identification for accessing institutions and logging into attendance systems. Currently, some of the existing biometric techniques such as the use of fingerprints are unpopular due to COVID-19 challenges. This paper identifies the components of a framework for secure contactless access authentication. The researcher selected 50 journals from Google scholar which were used to analyze the various components used in a secure contactless access authentication framework. The methodology used for research was based on the scientific approach of research methodology that mainly includes data collection from the 50 selected journals, analysis of the data and assessment of results. The following components were identified: database, sensor camera, feature extraction methods, matching and decision algorithm. Out of the considered journals the most used is CASIA database at 40%, CCD Sensor camera with 56%, Gabor feature extraction method at 44%, Hamming distance for matching at 100% and PCA at 100% was used for decision making. These findings will assist the researcher in providing a guide on the best suitable components. Various researchers have proposed an improvement in the current security systems due to integrity and security problems.","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126237896","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}
{"title":"Review of Semantic Importance and Role of using Ontologies in Web Information Retrieval Techniques","authors":"Ashraf Ali","doi":"10.24203/ijcit.v11i1.240","DOIUrl":"https://doi.org/10.24203/ijcit.v11i1.240","url":null,"abstract":"The Web contains an enormous amount of information, which is managed to accumulate, researched, and regularly used by many users. The nature of the Web is multilingual and growing very fast with its diverse nature of data including unstructured or semi-structured data such as Websites, texts, journals, and files. Obtaining critical relevant data from such vast data with its diverse nature has been a monotonous and challenging task. Simple key phrase data gathering systems rely heavily on statistics, resulting in a word incompatibility problem related to a specific word's inescapable semantic and situation variants. As a result, there is an urgent need to arrange such colossal data systematically to find out the relevant information that can be quickly analyzed and fulfill the users' needs in the relevant context. Over the years ontologies are widely used in the semantic Web to contain unorganized information systematic and structured manner. Still, they have also significantly enhanced the efficiency of various information recovery approaches. Ontological information gathering systems recover files focused on the semantic relation of the search request and the searchable information. This paper examines contemporary ontology-based information extraction techniques for texts, interactive media, and multilingual data types. Moreover, the study tried to compare and classify the most significant developments utilized in the search and retrieval techniques and their major disadvantages and benefits.","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126288190","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}
{"title":"Pulsar Star Detection: A Comparative Analysis of Classification Algorithms using SMOTE","authors":"Apratim Sadhu","doi":"10.24203/ijcit.v11i1.193","DOIUrl":"https://doi.org/10.24203/ijcit.v11i1.193","url":null,"abstract":"A Pulsar is a highly magnetized rotating compact star whose magnetic poles emit beams of radiation. The application of pulsar stars has a great application in the field of astronomical study. Applications like the existence of gravitational radiation can be indirectly confirmed from the observation of pulsars in a binary neutron star system. Therefore, the identification of pulsars is necessary for the study of gravitational waves and general relativity. Detection of pulsars in the universe can help research in the field of astrophysics. At present, there are millions of pulsar candidates present to be searched. Machine learning techniques can help detect pulsars from such a large number of candidates. The paper discusses nine common classification algorithms for the prediction of pulsar stars and then compares their performances using various classification metrics such as classification accuracy, precision and recall value, ROC score and f-score on both balanced and unbalanced data. SMOTE-technique is used to balance the data for better results. Among the nine algorithms, XGBoosting algorithm achieved the best results. The paper is concluded with prospects of machine learning for pulsar detection in the field of astronomy.","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120956069","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}
{"title":"Development of an Android Mobile App for Real Time Maize Stem Borers Monitoring in Precision Farming","authors":"E. Joseph","doi":"10.24203/ijcit.v10i6.181","DOIUrl":"https://doi.org/10.24203/ijcit.v10i6.181","url":null,"abstract":"Development of an Android mobile app for real time maize stem borers’ monitoring in precision agriculture is presented. In farmland, cultivated maize requires farmers’ constant care and monitoring during the developing stage to avoid sudden attack of insect pests such as stem borers in the field. The maize monitoring process taken by farmers to ensure attack free and healthy growth is very strenuous and time consuming. The sudden invasion of the Spodoptera species (stem borers) to maize farm early 2016 caused huge loss to farmers and imposed food scarcity in the land. These species are hardly distinguished from one another by farmers in the farm because they look alike in appearance. Rural farmers do not know the right insecticides to apply for the effective control of these species. These issues kept on lingering and now have become serious concern to farmers. Hence, this work is to bridge the gap by providing android mobile app that would enable farmers to effectively monitor these species remotely. The mobile app architecture consists of various sections such as captured insects, categories of spodoptera species, insect pest population plots, determination of economic injury level (EIL) and economic threshold (ET), and control measure was successfully designed. The mobile app structure and behavior were also designed using Unified Modeling Language (UML). The maize Stem borers App was developed in android studio using Kotlin programming language. The App is linked to the cloud server where all the captured and recognized species are stored for downloading and farmers’ visualization. The Internet of Things (IoT) hardware was setup in the maize farm which captured these targeted insect pests, processed via Nividia Jetson Nano and sent to the cloud server. The mobile App synchronized successfully with the cloud server and could download stored maize insect pests in the farmer’s Android phone.","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123659090","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}
{"title":"Hybrid Cluster based Collaborative Filtering using Firefly and Agglomerative Hierarchical Clustering","authors":"Spoorthy G., Sanjeevi Sriram G","doi":"10.24203/ijcit.v10i6.170","DOIUrl":"https://doi.org/10.24203/ijcit.v10i6.170","url":null,"abstract":"Recommendation Systems finds the user preferences based on the purchase history of an individual using data mining and machine learning techniques. To reduce the time taken for computation Recommendation systems generally use a pre-processing technique which in turn helps to increase high low performance and over comes over-fitting of data. In this paper, we propose a hybrid collaborative filtering algorithm using firefly and agglomerative hierarchical clustering technique with priority queue and Principle Component Analysis (PCA). We applied our hybrid algorithm on movielens dataset and used Pearson Correlation to obtain Top N recommendations. Experimental results show that the our algorithm delivers accurate and reliable recommendations showing high performance when compared with existing algorithms.","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"238 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121306637","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}
Vusumuzi Malele, Mulumba Banza Gracia, Lebogang Maaka, S. Ndlovu
{"title":"Software-Defined Networking in Cloud Computing","authors":"Vusumuzi Malele, Mulumba Banza Gracia, Lebogang Maaka, S. Ndlovu","doi":"10.24203/ijcit.v10i6.172","DOIUrl":"https://doi.org/10.24203/ijcit.v10i6.172","url":null,"abstract":"Through network programmability, we may simplify network management and bring innovation, cloud computing introduced some of its network concepts. One of the most prominent cloud models for minimizing maintenance obligations and simplifying network infrastructure administration is the SDN (Software Defined Network) architecture. SDN stands out because it provides separation of the control plane and programmability for developing network applications. As a result, SDN is expected to enable more efficient configuration, higher performance, and increased flexibility to support new network architectures. This article is aimed to demonstrates the importance of the SDN and the major role it plays in the organization and how SDNs can be profitable to many organizations that remain in the archaic or a traditional cloud environment and how SDN can restructure the cloud architecture with more security enhancement and also to investigate SDN related issues and challenges to provide insight into the obstacles that this revolutionary network paradigm will face in the future, from both a protocol and architecture standpoint. In this study, systematic literature was conducted and descriptive was used to analyze data. When it comes to SDN, the following challenges and issues stand out: All of these phrases are used to characterize the properties of a system: scalability, high availability, reliability, elasticity, security, performance, resilience, and dependability.","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131078694","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}
{"title":"Technique of Semantic Unambiguity for a Concept Selection of Terms in Focused Contexts with Reinforcement Learning Integration","authors":"Churee Teechawut, Khananat Jaroenchai","doi":"10.24203/ijcit.v10i6.147","DOIUrl":"https://doi.org/10.24203/ijcit.v10i6.147","url":null,"abstract":"Nowadays, there have been many developments of learning processes for computers to understand the meaning of words and their semantic similarities in order for the computers to better communicate, interact and exchange information with humans. Semantic learning development is a major issue because computers cannot comprehend the suitable meaning of words in the concerning concept. As a result, this research is proposing and exploring the efficiency of the technique of semantic unambiguity in order to clarify the Term Concepts in the focused contexts. From the case study with 22 contexts, 62 term, and 475 synsets, it was shown that Reinforcement Learning could accurately select the suitable term concepts for the focused contexts, with Precision = 0.7756, Recall = 0.7756 and F-Measure = 0.7735. Therefore, it can be concluded that the Technique of Semantic Unambiguity for a Concept Selection of Terms in Focused Contexts has high accuracy when applying the Reinforcement Learning.","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133411718","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}