Pub Date : 2023-08-31DOI: 10.58346/jisis.2023.i3.007
Udayakumar Dr.R., Anuradha Dr.M., Dr. Yogesh Manohar Gajmal, Elankavi Dr.R.
The mushrooming of IoTs (Internet of Things) and decentralised paradigm in cyber security have attracted a lot of interest from the government, academic, and business sectors in recent years. The use of MLT-assisted techniques in the IoT security arena has attracted a lot of attention in recent years. Many current studies presume that massive training data is readily accessible from IoT devices and transferable to main servers. However, since data is hosted on single servers, security and privacy concerns regarding this data also increase. It is suggested to use decentralised on-device data in OFDL (Optimal Federated Deep Learning) based anomaly detections to proactively identify infiltration in networks for IoTs. The GRUs (Gated Recurrent Units) used in OFDL's training rounds share only learned weights with the main OFDL servers, protecting data integrity on local devices. The model's training costs are reduced by the use of appropriate parameters, which also secures the edge or IoT device. In order to optimise the hyper-parameter environments for the limited OFDL environment, this paper suggests an MSSO (Modified Salp Swarm Optimisation) approach. Additionally, ensembles combine updates from multiple techniques to enhance accuracies. The experimental findings show that this strategy secures user data privacy better than traditional/centralized MLTs and offers the best accuracy rate for attack detection.
{"title":"Anomaly Detection for Internet of Things Security Attacks Based on Recent Optimal Federated Deep Learning Model","authors":"Udayakumar Dr.R., Anuradha Dr.M., Dr. Yogesh Manohar Gajmal, Elankavi Dr.R.","doi":"10.58346/jisis.2023.i3.007","DOIUrl":"https://doi.org/10.58346/jisis.2023.i3.007","url":null,"abstract":"The mushrooming of IoTs (Internet of Things) and decentralised paradigm in cyber security have attracted a lot of interest from the government, academic, and business sectors in recent years. The use of MLT-assisted techniques in the IoT security arena has attracted a lot of attention in recent years. Many current studies presume that massive training data is readily accessible from IoT devices and transferable to main servers. However, since data is hosted on single servers, security and privacy concerns regarding this data also increase. It is suggested to use decentralised on-device data in OFDL (Optimal Federated Deep Learning) based anomaly detections to proactively identify infiltration in networks for IoTs. The GRUs (Gated Recurrent Units) used in OFDL's training rounds share only learned weights with the main OFDL servers, protecting data integrity on local devices. The model's training costs are reduced by the use of appropriate parameters, which also secures the edge or IoT device. In order to optimise the hyper-parameter environments for the limited OFDL environment, this paper suggests an MSSO (Modified Salp Swarm Optimisation) approach. Additionally, ensembles combine updates from multiple techniques to enhance accuracies. The experimental findings show that this strategy secures user data privacy better than traditional/centralized MLTs and offers the best accuracy rate for attack detection.","PeriodicalId":36718,"journal":{"name":"Journal of Internet Services and Information Security","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44788536","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 : 2023-08-31DOI: 10.58346/jisis.2023.i3.003
Basman M. Alnedawi, W. Ibraheem, Z. Al-Abbasi
This article considers the impairments in the application of successive interference cancellation (SIC) at the detection phase of non-orthogonal multiple access (NOMA) users. A practical approach is proposed to model the SIC impairment which takes into account the number of multiplexed users in NOMA’s power domain, in addition to the overall number of shared radio resources. In such case the imperfection of the SIC varies in accordance with the number of users. This strategy is closer to the situation in practice than the case where the SIC is modeled with fixed error factor as in the previous research articles that already considered the matter. A channel estimation approach is also proposed, which depends on the user’s channel gain variations to predict the change in its peers’ channel so as to compensate for the error resulting from SIC imperfection. The outcome of the proposed compensation strategy is promising as the simulation results reflect significant improvement in the achievable rate and energy efficiency.
{"title":"Modelling and Compensation of SIC Imperfection in IRS-NOMA based 5G-System","authors":"Basman M. Alnedawi, W. Ibraheem, Z. Al-Abbasi","doi":"10.58346/jisis.2023.i3.003","DOIUrl":"https://doi.org/10.58346/jisis.2023.i3.003","url":null,"abstract":"This article considers the impairments in the application of successive interference cancellation (SIC) at the detection phase of non-orthogonal multiple access (NOMA) users. A practical approach is proposed to model the SIC impairment which takes into account the number of multiplexed users in NOMA’s power domain, in addition to the overall number of shared radio resources. In such case the imperfection of the SIC varies in accordance with the number of users. This strategy is closer to the situation in practice than the case where the SIC is modeled with fixed error factor as in the previous research articles that already considered the matter. A channel estimation approach is also proposed, which depends on the user’s channel gain variations to predict the change in its peers’ channel so as to compensate for the error resulting from SIC imperfection. The outcome of the proposed compensation strategy is promising as the simulation results reflect significant improvement in the achievable rate and energy efficiency.","PeriodicalId":36718,"journal":{"name":"Journal of Internet Services and Information Security","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42015424","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 : 2023-08-31DOI: 10.58346/jisis.2023.i3.004
B. Blažič, Primoz Cigoj, Andrej Jerman Blažič
This study explores the impact of internet users’ and web owners’ knowledge, measured by the level of digital skills, on the number of insecure websites based on a survey of the internet. The influence of the affordability of internet access to the web space on the vulnerability of a particular European country is also considered. The study introduces a quantifiable index for assessing the insecurity of websites that is incorporated into a newly developed tool that scans websites and identifies the vulnerability in the Web Content Management System (WCMS). The collected vulnerability data and the digital skills are analyzed with statistical methods for finding the interdependences and relationships. Higher levels of digital skills and lower fixed-internet-access costs contribute to a smaller number of insecure websites. The vulnerability of the websites for different economic sectors is explored as well. The paper discusses the differences in the digital development pathways and governmental policies applied in European countries that have been affected by user knowledge and digital skills. The study brings original results and findings, as there are no similar studies addressing the impact of the knowledge of a country’s population on the level of insecurity found in the WCMS, including plug-ins.
{"title":"Web-Service Security and The Digital Skills of Users: An Exploratory Study of Countries in Europe","authors":"B. Blažič, Primoz Cigoj, Andrej Jerman Blažič","doi":"10.58346/jisis.2023.i3.004","DOIUrl":"https://doi.org/10.58346/jisis.2023.i3.004","url":null,"abstract":"This study explores the impact of internet users’ and web owners’ knowledge, measured by the level of digital skills, on the number of insecure websites based on a survey of the internet. The influence of the affordability of internet access to the web space on the vulnerability of a particular European country is also considered. The study introduces a quantifiable index for assessing the insecurity of websites that is incorporated into a newly developed tool that scans websites and identifies the vulnerability in the Web Content Management System (WCMS). The collected vulnerability data and the digital skills are analyzed with statistical methods for finding the interdependences and relationships. Higher levels of digital skills and lower fixed-internet-access costs contribute to a smaller number of insecure websites. The vulnerability of the websites for different economic sectors is explored as well. The paper discusses the differences in the digital development pathways and governmental policies applied in European countries that have been affected by user knowledge and digital skills. The study brings original results and findings, as there are no similar studies addressing the impact of the knowledge of a country’s population on the level of insecurity found in the WCMS, including plug-ins.","PeriodicalId":36718,"journal":{"name":"Journal of Internet Services and Information Security","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45228900","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 : 2023-08-31DOI: 10.58346/jisis.2023.i3.006
A. A. Abdo, Khaznah Alhajri, Assail Alyami, Aljazi Alkhalaf, Bashayer Allail, Esra Alyami, Hind Baaqeel
In recent years, online social networks (OSNs) have become a huge used platform for sharing activities, opinions, and advertisements. Spam content is considered one of the biggest threats in social networks. Spammers exploit OSNs for falsifying content as part of phishing, such as sharing forged advertisements, selling forged products, or sharing sexual words. Therefore, machine learning (ML) and deep learning (DL) techniques are the best methods for detecting phishing attacks and minimize their risk. This paper provides an overview of prior studies of OSNs spam detection modeling based on ML and DL techniques. The research papers are classified into three categories: the features used for prediction, the dataset size corresponding language used, real-time based applications, and machine learning or deep learning techniques. Challenges and opportunities in phishing attacks prediction using ML and DL techniques are also concluded in our study.
{"title":"AI-based Spam Detection Techniques for Online Social Networks: Challenges and Opportunities","authors":"A. A. Abdo, Khaznah Alhajri, Assail Alyami, Aljazi Alkhalaf, Bashayer Allail, Esra Alyami, Hind Baaqeel","doi":"10.58346/jisis.2023.i3.006","DOIUrl":"https://doi.org/10.58346/jisis.2023.i3.006","url":null,"abstract":"In recent years, online social networks (OSNs) have become a huge used platform for sharing activities, opinions, and advertisements. Spam content is considered one of the biggest threats in social networks. Spammers exploit OSNs for falsifying content as part of phishing, such as sharing forged advertisements, selling forged products, or sharing sexual words. Therefore, machine learning (ML) and deep learning (DL) techniques are the best methods for detecting phishing attacks and minimize their risk. This paper provides an overview of prior studies of OSNs spam detection modeling based on ML and DL techniques. The research papers are classified into three categories: the features used for prediction, the dataset size corresponding language used, real-time based applications, and machine learning or deep learning techniques. Challenges and opportunities in phishing attacks prediction using ML and DL techniques are also concluded in our study.","PeriodicalId":36718,"journal":{"name":"Journal of Internet Services and Information Security","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49537950","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 : 2023-08-31DOI: 10.58346/jisis.2023.i3.002
Sourav Sinha, Dr. Revathi Sathiya Narayanan
In recent past during the era of consumerism with easy accessibility to social networking world, the consumers usually give comments and opinions on daily usable ingredients, electronic goods and services offered on payments. These comments or opinions are innumerable and huge on each item, hence need the special attention for sentimental value particularly on their text parts. The present study is an attempt to perform sentiment prediction on Amazon Electronic products, gift cards and Kindle dataset. In this paper, the HLESV (Hybrid Lexicon Ensemble based Soft Voting) model is proposed by combining lexicon and ensemble approaches using optimally weighted voting to predict the sentiment, subsequently to evaluate model using various performance metrics like precision, recall, F1-score. This paper computes an additional metric namely subjectivity score along with sentiment score and proposes non-interpretive sentiment class label to evaluate the polarity of the reviews using our proposed HLESV model for sentiment classification. The accuracy score of our proposed HLESV model is evaluated to assess its effectiveness on Amazon consumer product review datasets and observed an increase of 1-6% accuracy over existing state-of-the-art ensemble methodology.
在最近的消费主义时代，社交网络世界很容易进入，消费者通常会对日常可用的食材、电子产品和支付提供的服务发表评论和意见。这些评论或意见在每个项目上都是无数的和巨大的，因此需要特别注意情感价值，特别是在他们的文本部分。本研究试图对亚马逊电子产品、礼品卡和Kindle数据集进行情感预测。本文提出了基于软投票的HLESV (Hybrid Lexicon Ensemble based Soft Voting)模型，该模型将词典和集成方法相结合，使用最优加权投票来预测情感，然后使用精度、召回率、F1-score等各种性能指标来评估模型。本文计算了一个额外的度量，即主观得分和情感得分，并提出了非解释性的情感类别标签，使用我们提出的HLESV模型进行情感分类来评估评论的极性。我们对我们提出的HLESV模型的准确率评分进行了评估，以评估其在亚马逊消费者产品评论数据集上的有效性，并观察到比现有最先进的集成方法提高了1-6%的准确率。
{"title":"A Novel Hybrid Lexicon Ensemble Learning Model for Sentiment Classification of Consumer Reviews","authors":"Sourav Sinha, Dr. Revathi Sathiya Narayanan","doi":"10.58346/jisis.2023.i3.002","DOIUrl":"https://doi.org/10.58346/jisis.2023.i3.002","url":null,"abstract":"In recent past during the era of consumerism with easy accessibility to social networking world, the consumers usually give comments and opinions on daily usable ingredients, electronic goods and services offered on payments. These comments or opinions are innumerable and huge on each item, hence need the special attention for sentimental value particularly on their text parts. The present study is an attempt to perform sentiment prediction on Amazon Electronic products, gift cards and Kindle dataset. In this paper, the HLESV (Hybrid Lexicon Ensemble based Soft Voting) model is proposed by combining lexicon and ensemble approaches using optimally weighted voting to predict the sentiment, subsequently to evaluate model using various performance metrics like precision, recall, F1-score. This paper computes an additional metric namely subjectivity score along with sentiment score and proposes non-interpretive sentiment class label to evaluate the polarity of the reviews using our proposed HLESV model for sentiment classification. The accuracy score of our proposed HLESV model is evaluated to assess its effectiveness on Amazon consumer product review datasets and observed an increase of 1-6% accuracy over existing state-of-the-art ensemble methodology.","PeriodicalId":36718,"journal":{"name":"Journal of Internet Services and Information Security","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41972152","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 : 2023-08-31DOI: 10.58346/jisis.2023.i3.009
Wasin AlKishri, Setyawan Widyarto, Jabar H. Yousif, M. Al-Bahri
Detecting fake faces has become a crucial endeavour within the realm of computer vision. The widespread availability of digital media has facilitated the creation and dissemination of deceptive and misleading content. A prominent strategy for identifying counterfeit faces employs advanced deep-learning methodologies that scrutinise both colour and textural attributes. This investigation is geared towards devising a method for discerning fake faces by leveraging the capabilities of convolutional neural networks (CNNs). These networks are trained to discriminate between authentic and forged images by discerning nuances in their colour characteristics. To achieve this, the MSU MFSD dataset will be harnessed, allowing for exploring colour textures and extracting facial traits across diverse colour channels, including RGB, HSV, and YCbCr.The proposed framework marks a notable stride in the realm of computer vision research, particularly given the prevalent employment of digital media, which has eased the generation and distribution of misleading or deceitful content. Developing dependable systems for identifying counterfeit faces holds immense potential in curtailing the proliferation of false information and upholding the integrity of digital media platforms.
{"title":"Fake Face Detection Based on Colour Textual Analysis Using Deep Convolutional Neural Network","authors":"Wasin AlKishri, Setyawan Widyarto, Jabar H. Yousif, M. Al-Bahri","doi":"10.58346/jisis.2023.i3.009","DOIUrl":"https://doi.org/10.58346/jisis.2023.i3.009","url":null,"abstract":"Detecting fake faces has become a crucial endeavour within the realm of computer vision. The widespread availability of digital media has facilitated the creation and dissemination of deceptive and misleading content. A prominent strategy for identifying counterfeit faces employs advanced deep-learning methodologies that scrutinise both colour and textural attributes. This investigation is geared towards devising a method for discerning fake faces by leveraging the capabilities of convolutional neural networks (CNNs). These networks are trained to discriminate between authentic and forged images by discerning nuances in their colour characteristics. To achieve this, the MSU MFSD dataset will be harnessed, allowing for exploring colour textures and extracting facial traits across diverse colour channels, including RGB, HSV, and YCbCr.The proposed framework marks a notable stride in the realm of computer vision research, particularly given the prevalent employment of digital media, which has eased the generation and distribution of misleading or deceitful content. Developing dependable systems for identifying counterfeit faces holds immense potential in curtailing the proliferation of false information and upholding the integrity of digital media platforms.","PeriodicalId":36718,"journal":{"name":"Journal of Internet Services and Information Security","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41793563","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 : 2023-08-31DOI: 10.58346/jisis.2023.i3.005
Walter Antonio Campos Ugaz, Maria del Rocío Hende Santolaya, Handry Martín Rodas Purizaga, Wesley Amado Salazar Bravo, Jorge Dávila, José Yudberto Vilca Ccolque, Doris Fúster Guillén
The Internet of Everything (IoE) is rapidly growing and utilized in various applications. However, the growing mobile traffic and services pose significant challenges in flexibility, movement, accessibility, and safety. The existing internet architecture and protocol must be improved to address the challenges. The article examines the attributes and prerequisites of forthcoming networking applications while emphasizing the constraints of conventional network architecture and protocols in fulfilling these needs. The research presents a new Hybrid Internet Architecture and Protocol (HIAP), the Self-Evolving and Transformative (SET) architecture. This architecture is designed to provide diverse control works and smart configuration options for different applications and networking conditions. This HIAP framework's primary emphasis lies in transport protocols and mechanisms for peer-to-peer file sharing. This study proposes implementing a deadline-aware multipath transport protocol within the framework of the Internet architecture with seamless support of real-time applications requiring strict adherence to latency demands. The HIAP framework incorporates evolvability, adaptable routing, and in-network cache mechanisms to enhance contentdelivery. To conduct a more comprehensive examination and conceptualize the peer-to-peer file-sharing system, the research created a pragmatic blueprint for setting the file transfer protocol on the HIAP. The study presented the groundwork for an Internet architecture better suited to the changing demands of the IoE and its various applications. This HIAP architecture aims to be more adaptable, efficient, and transformative. The present study involves a comparative analysis between the proposed research and current architecture. The findings provide evidence of the progress made by the suggested research in addressing the challenges related to multipath and safety in future architectural designs.
万物互联(Internet of Everything, IoE)正在迅速发展并被广泛应用。然而，不断增长的移动流量和服务在灵活性、移动性、可达性和安全性方面提出了重大挑战。必须改进现有的互联网架构和协议，以应对这些挑战。本文研究了即将到来的网络应用程序的属性和先决条件，同时强调了传统网络体系结构和协议在满足这些需求方面的限制。该研究提出了一种新的混合互联网体系结构和协议(HIAP)，即自进化和转换(SET)体系结构。该架构旨在为不同的应用程序和网络条件提供不同的控制工作和智能配置选项。这个HIAP框架的主要重点在于传输协议和对等文件共享机制。本研究提出在互联网架构框架内实现一种截止日期感知的多路径传输协议，无缝支持需要严格遵守延迟要求的实时应用程序。HIAP框架结合了可演化性、自适应路由和网络内缓存机制来增强内容传递。为了对点对点文件共享系统进行更全面的考察和概念化，本研究为在HIAP上设置文件传输协议创建了一个实用的蓝图。该研究为更好地适应物联网及其各种应用不断变化的需求的互联网体系结构提供了基础。这种HIAP体系结构旨在提高适应性、效率和变革性。目前的研究包括对拟议研究和当前建筑之间的比较分析。研究结果表明，在解决未来建筑设计中与多路径和安全相关的挑战方面，建议的研究取得了进展。
{"title":"Hybrid Internet Architecture and Protocol (HIAP): A Self-Evolving and Transformative Framework for Enabling Seamless Real-Time Applications and Secure Peer-to-Peer File Sharing in the Internet of Everything (IoE)","authors":"Walter Antonio Campos Ugaz, Maria del Rocío Hende Santolaya, Handry Martín Rodas Purizaga, Wesley Amado Salazar Bravo, Jorge Dávila, José Yudberto Vilca Ccolque, Doris Fúster Guillén","doi":"10.58346/jisis.2023.i3.005","DOIUrl":"https://doi.org/10.58346/jisis.2023.i3.005","url":null,"abstract":"The Internet of Everything (IoE) is rapidly growing and utilized in various applications. However, the growing mobile traffic and services pose significant challenges in flexibility, movement, accessibility, and safety. The existing internet architecture and protocol must be improved to address the challenges. The article examines the attributes and prerequisites of forthcoming networking applications while emphasizing the constraints of conventional network architecture and protocols in fulfilling these needs. The research presents a new Hybrid Internet Architecture and Protocol (HIAP), the Self-Evolving and Transformative (SET) architecture. This architecture is designed to provide diverse control works and smart configuration options for different applications and networking conditions. This HIAP framework's primary emphasis lies in transport protocols and mechanisms for peer-to-peer file sharing. This study proposes implementing a deadline-aware multipath transport protocol within the framework of the Internet architecture with seamless support of real-time applications requiring strict adherence to latency demands. The HIAP framework incorporates evolvability, adaptable routing, and in-network cache mechanisms to enhance contentdelivery. To conduct a more comprehensive examination and conceptualize the peer-to-peer file-sharing system, the research created a pragmatic blueprint for setting the file transfer protocol on the HIAP. The study presented the groundwork for an Internet architecture better suited to the changing demands of the IoE and its various applications. This HIAP architecture aims to be more adaptable, efficient, and transformative. The present study involves a comparative analysis between the proposed research and current architecture. The findings provide evidence of the progress made by the suggested research in addressing the challenges related to multipath and safety in future architectural designs.","PeriodicalId":36718,"journal":{"name":"Journal of Internet Services and Information Security","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47100246","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 : 2023-08-31DOI: 10.58346/jisis.2023.i3.011
Lolo José Caballero Cifuentes, Luis Alberto Núñez Lira, Yrene Cecilia Uribe Hernández, C. Luy-Montejo, Yaneth Carol Larico Apaza, Jessica Elizabeth Acevedo Flores, Jacinto Joaquín Vértiz Osores
This article examines the use of the SAS tool in the learning of statistics. the type of research was applied with a quasi-experimental design and quantitative approach, the sample was determined by a non-probabilistic method comprising 28 students for both groups; for the collection of information, a pre-test and a post-test were applied, validated with expert judgment and V. Aiken, its reliability with the Spearman Brown coefficient. After the experiment, the results showed higher averages in favor of the experimental group to whom the SAS software was applied in its statistical learning dimensions at a descriptive and inferential level. In order to know the distribution of the data, the Shapiro Wilk numerical method was used, the result of the test gave the certainty to choose the T-Student test for two independent samples at 95% with a level of confidence and 0.05 significance. It is concluded that the SAS software improves the levels of learning of statistics, increases their creativity, they feel more motivated, and there is an interaction favoring more active learning.
{"title":"Influence of SAS Software on the Learning of Statistics at the University Level","authors":"Lolo José Caballero Cifuentes, Luis Alberto Núñez Lira, Yrene Cecilia Uribe Hernández, C. Luy-Montejo, Yaneth Carol Larico Apaza, Jessica Elizabeth Acevedo Flores, Jacinto Joaquín Vértiz Osores","doi":"10.58346/jisis.2023.i3.011","DOIUrl":"https://doi.org/10.58346/jisis.2023.i3.011","url":null,"abstract":"This article examines the use of the SAS tool in the learning of statistics. the type of research was applied with a quasi-experimental design and quantitative approach, the sample was determined by a non-probabilistic method comprising 28 students for both groups; for the collection of information, a pre-test and a post-test were applied, validated with expert judgment and V. Aiken, its reliability with the Spearman Brown coefficient. After the experiment, the results showed higher averages in favor of the experimental group to whom the SAS software was applied in its statistical learning dimensions at a descriptive and inferential level. In order to know the distribution of the data, the Shapiro Wilk numerical method was used, the result of the test gave the certainty to choose the T-Student test for two independent samples at 95% with a level of confidence and 0.05 significance. It is concluded that the SAS software improves the levels of learning of statistics, increases their creativity, they feel more motivated, and there is an interaction favoring more active learning.","PeriodicalId":36718,"journal":{"name":"Journal of Internet Services and Information Security","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49135897","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 : 2023-08-31DOI: 10.58346/jisis.2023.i3.001
Eliana Maritza Barturen Mondragón, María del Pilar Quezada Castro, María del Pilar Castro Arellano, C. Aguila, Guillermo Alexander Quezada Castro
The spread of fake news on Facebook is a reality. This behavior is aimed at affecting reputation and generating distrust towards a certain person or on a specific topic. A bibliometric study of the scientific production in Scopus on Fake News on Facebook in the period 2013-2023 was carried out. The results showed that fake news is promoted in political issues to generate instability and in health issues to generate confusion and panic in the population. It was concluded that citizens must develop critical thinking to question the validity of news sources. Similarly, anonymity and misinformation are a natural part of society.
{"title":"Examining the Widespread Dissemination of Fake News on Facebook: Political Instability and Health Panic","authors":"Eliana Maritza Barturen Mondragón, María del Pilar Quezada Castro, María del Pilar Castro Arellano, C. Aguila, Guillermo Alexander Quezada Castro","doi":"10.58346/jisis.2023.i3.001","DOIUrl":"https://doi.org/10.58346/jisis.2023.i3.001","url":null,"abstract":"The spread of fake news on Facebook is a reality. This behavior is aimed at affecting reputation and generating distrust towards a certain person or on a specific topic. A bibliometric study of the scientific production in Scopus on Fake News on Facebook in the period 2013-2023 was carried out. The results showed that fake news is promoted in political issues to generate instability and in health issues to generate confusion and panic in the population. It was concluded that citizens must develop critical thinking to question the validity of news sources. Similarly, anonymity and misinformation are a natural part of society.","PeriodicalId":36718,"journal":{"name":"Journal of Internet Services and Information Security","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48757495","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 : 2023-08-31DOI: 10.58346/jisis.2023.i3.008
Jhimmy Alberth Quisocala Herrera, Fernando Antonio Flores Limo, Abel Alejandro Tasayco-Jala, Isabel Menacho Vargas, Wilfredo Barrientos Farias, Zoila Mercedes Collantes Inga, Eber L. Herrera Palacios
Internet security is of paramount importance due to the pervasive nature of the network in modern society. As the globe grows increasingly interconnected, issues like data breaches, unauthorized access, and service disruptions become more common. Safeguarding private data, ensuring uninterrupted communication, and protecting vital services are all essential to establishing confidence and stability in the online world. Internet security is a complex problem to solve due to the interconnected nature of the Internet's Architecture and Protocols (IAP). Due to the wide variety of devices and platforms that can access the Internet, cybercriminals can breach a complex ecosystem. Constant monitoring and flexibility are required due to the rapid development of new attack methods and vulnerabilities. The difficulty lies in balancing implementing new security measures and minimizing disruptions to the user experience, which calls for adaptive and novel approaches. In this paper, the Behavioural Biometric Block Chain-Enhanced Authentication layer (BBB-EAL) framework recommends a static authentication mechanism for end-users and edge servers. This authentication creates a secure and encrypted link between parties. Access tokens are produced via a smart contract, removing the requirement for a trusted third party. This work emphasizes the importance of architecture design and sequence diagrams in representing participant interactions and information sharing. Additionally, it examines the construction of the Machine Learning (ML) model used to recognize KMT dynamics. Simulations indicate that the recommended design improves user authentication in an IAP-enabled environment. The findings demonstrate the ability to evaluate confidence in real time, achieve minimal authentication time, and utilize resources efficiently.
{"title":"Security Issues in Internet Architecture and Protocols Based on Behavioural Biometric Block Chain-Enhanced Authentication Layer","authors":"Jhimmy Alberth Quisocala Herrera, Fernando Antonio Flores Limo, Abel Alejandro Tasayco-Jala, Isabel Menacho Vargas, Wilfredo Barrientos Farias, Zoila Mercedes Collantes Inga, Eber L. Herrera Palacios","doi":"10.58346/jisis.2023.i3.008","DOIUrl":"https://doi.org/10.58346/jisis.2023.i3.008","url":null,"abstract":"Internet security is of paramount importance due to the pervasive nature of the network in modern society. As the globe grows increasingly interconnected, issues like data breaches, unauthorized access, and service disruptions become more common. Safeguarding private data, ensuring uninterrupted communication, and protecting vital services are all essential to establishing confidence and stability in the online world. Internet security is a complex problem to solve due to the interconnected nature of the Internet's Architecture and Protocols (IAP). Due to the wide variety of devices and platforms that can access the Internet, cybercriminals can breach a complex ecosystem. Constant monitoring and flexibility are required due to the rapid development of new attack methods and vulnerabilities. The difficulty lies in balancing implementing new security measures and minimizing disruptions to the user experience, which calls for adaptive and novel approaches. In this paper, the Behavioural Biometric Block Chain-Enhanced Authentication layer (BBB-EAL) framework recommends a static authentication mechanism for end-users and edge servers. This authentication creates a secure and encrypted link between parties. Access tokens are produced via a smart contract, removing the requirement for a trusted third party. This work emphasizes the importance of architecture design and sequence diagrams in representing participant interactions and information sharing. Additionally, it examines the construction of the Machine Learning (ML) model used to recognize KMT dynamics. Simulations indicate that the recommended design improves user authentication in an IAP-enabled environment. The findings demonstrate the ability to evaluate confidence in real time, achieve minimal authentication time, and utilize resources efficiently.","PeriodicalId":36718,"journal":{"name":"Journal of Internet Services and Information Security","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47216240","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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