2022 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)最新文献_第7页

Review of Recent Intrusion Detection Systems and Intrusion Prevention Systems in IoT Networks 物联网网络中入侵检测和入侵防御系统研究进展

2022 International Conference on Software, Telecommunications and Computer Networks (SoftCOM) Pub Date : 2022-09-22 DOI: 10.23919/softcom55329.2022.9911401

Z. Chiba, N. Abghour, K. Moussaid, O. Lifandali, R. Kinta

{"title":"Review of Recent Intrusion Detection Systems and Intrusion Prevention Systems in IoT Networks","authors":"Z. Chiba, N. Abghour, K. Moussaid, O. Lifandali, R. Kinta","doi":"10.23919/softcom55329.2022.9911401","DOIUrl":"https://doi.org/10.23919/softcom55329.2022.9911401","url":null,"abstract":"The Internet of Things (IoT) paradigm has gained exponential growth and popularity in recent years. It is a precipitously shifting technology, in which interconnected computing devices and sensors share data and communicate over the Internet, to decipher different problems and deliver new services without human intervention. In fact, IoT is becoming more ubiquitous in our daily lives, connecting physical things to e-services. That is to say; the IoT is the engine that powers home automation, modern health, advanced manufacturing, and smart cities. Thus, IoT holds a lot of promise for enhancing social and corporate life. Despite the rising vogue of IoT equipment, they are weak and vulnerable to many security threats because of the nature of their networks, and inherent hardware limitations that restrict their ability to implement security measures and increase their exposure to vulnerability attacks. Furthermore, the integration and diversification of IoT terminals and applications make IoT more prone to various intrusion attacks. There are many techniques used to preclude IoT from various attacks, Intrusion Detection System (IDS) and Intrusion Preventions System (IPS) are some of them, which can guarantee the security, privacy, and reliability of the IoT. In this paper, we provide a review of several recent and pertinent IDS and IPS proposed for IoT networks, where we highlight the suggested mechanisms and their limitations. This aids to spot the issues that still require to be tackled, well define the mainstream of research direction, and pave the way for novel avenues of research for future researchers.","PeriodicalId":261625,"journal":{"name":"2022 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127002889","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: 1

Predicting Students'Final Exam Grades Based on Learning Material Usage extracted from Moodle Logs 基于Moodle日志中学习材料使用情况预测学生期末考试成绩

2022 International Conference on Software, Telecommunications and Computer Networks (SoftCOM) Pub Date : 2022-09-22 DOI: 10.23919/softcom55329.2022.9911477

Suzana Marija Dunatov, Kristian Kasalo, Anamaria Lovrinčević, Jelena Maljković, Antonela Prnjak

引用次数: 0

Generative Recurrent Network For Design SARS-CoV-2 Main Protease Inhibitor 基于生成递归网络的SARS-CoV-2主蛋白酶抑制剂设计

2022 International Conference on Software, Telecommunications and Computer Networks (SoftCOM) Pub Date : 2022-09-22 DOI: 10.23919/softcom55329.2022.9911377

Adham Khaled, Zeinab Abd El Haliem

引用次数: 0

ATMAS: Airplane Trajectory Missing Alarm System based on Deep Learning 基于深度学习的飞机轨迹丢失报警系统

2022 International Conference on Software, Telecommunications and Computer Networks (SoftCOM) Pub Date : 2022-09-22 DOI: 10.23919/softcom55329.2022.9911358

Qiaoqiao Zhu, Zexin Wu, Jie Nie

引用次数: 0

A Hybrid Deep Learning Technique for Sentiment Analysis in E-Learning Platform with Natural Language Processing 基于自然语言处理的电子学习平台情感分析混合深度学习技术

2022 International Conference on Software, Telecommunications and Computer Networks (SoftCOM) Pub Date : 2022-09-22 DOI: 10.23919/softcom55329.2022.9911232

Jayashree Das, Anupam Das, J. Rosak-Szyrocka

{"title":"A Hybrid Deep Learning Technique for Sentiment Analysis in E-Learning Platform with Natural Language Processing","authors":"Jayashree Das, Anupam Das, J. Rosak-Szyrocka","doi":"10.23919/softcom55329.2022.9911232","DOIUrl":"https://doi.org/10.23919/softcom55329.2022.9911232","url":null,"abstract":"E-learning-based teaching methodologies are increasing now-a-days and also, the online classes are considered as highly popular that ensures the virtual platform for online education from anywhere in the world. The social networks are widely distributed that generates different opinions on various perspectives of life through the messages on the web. This textural information is highly sourced with the data for performing the sentiment analysis and opinion mining that is expressed through the text. This text provides the feelings of the students with the statements that show agreement or disagreement in the comment sections to reveal the negative or positive feelings of the students towards the learning. The major goal of this paper is to design of new sentiment analysis model for e-learning platform with the help of natural language processing techniques. Initially, the standard text data regarding e-learning platform with user reviews are gathered from benchmark resources. The gathered data is forwarded to pre-processing technique, where the unnecessary content is avoided for maximizing the performance of sentiment analysis. Further, word to vector conversion is carried out using glove embedding scheme for getting the relevant data for sentiment analysis. Further, the sentiment classification is carried out by Convolutional Neural Networks (CNN) with Gated Recurrent Unit (GRU). Finally, the sentiments are analyzed through hybrid deep learning in the field of e-learning. The investigation reveals promising results in sentiment analysis tasks.","PeriodicalId":261625,"journal":{"name":"2022 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129545696","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: 3

NetApps Approach for Accelerating Vertical Adoption of 5G Networks: A UAV Case 加速垂直5G网络采用的NetApps方法:以无人机为例

2022 International Conference on Software, Telecommunications and Computer Networks (SoftCOM) Pub Date : 2022-09-22 DOI: 10.23919/softcom55329.2022.9911276

Ignacio Martinez-Alpiste, Gelayol Golcarenarenji, D. Klonidis, J. A. Calero, Q. Wang

引用次数: 0

Design and Implementation of a Software Vulnerabilities and Application Research Tool 软件漏洞与应用研究工具的设计与实现

2022 International Conference on Software, Telecommunications and Computer Networks (SoftCOM) Pub Date : 2022-09-22 DOI: 10.23919/softcom55329.2022.9911314

E. Benetti, A. Zucchelli, G. Mazzini

引用次数: 1

Vehicle Distance Estimation Based on Stereo Camera System with Implementation on a Real ADAS Board 基于立体摄像系统的车辆距离估计及其在实际ADAS板上的实现

2022 International Conference on Software, Telecommunications and Computer Networks (SoftCOM) Pub Date : 2022-09-22 DOI: 10.23919/softcom55329.2022.9911360

Marko Miljković, M. Vranješ, David Mijic, M. Dukic

{"title":"Vehicle Distance Estimation Based on Stereo Camera System with Implementation on a Real ADAS Board","authors":"Marko Miljković, M. Vranješ, David Mijic, M. Dukic","doi":"10.23919/softcom55329.2022.9911360","DOIUrl":"https://doi.org/10.23919/softcom55329.2022.9911360","url":null,"abstract":"In Advanced Driver-Assistance Systems (ADAS) one of the main tasks is to determine the distance of the objects in the vehicle's surroundings. This paper presents a solution that determines the distance of a detected vehicle using a stereo image pair, which is implemented on a real ADAS embedded platform (ADAS board). To improve the performance of the solution, after disparity map calculation, the presented solution implements Fast Global Smoothing (FGS) filter with guidance over the disparity map, which smooths disparity map surfaces that represent the same object of the scene, while preserving its edges. This solution is tested in a real environment using the real ADAS board and specific automotive cameras. Distinct vehicles located at different distances from the cameras are used in tests. The results show the proposed solution can provide high-performance results when implemented on a real ADAS platform while processing 7 frames per second for videos with a resolution of 1280×360 pixels. Furthermore, it is possible to conclude that despite the somewhat slower execution of the solution using the FGS filter with guidance, it makes sense to use it because, with still acceptable execution frequency, it provides a much better distance estimation, which is extremely important for ADAS.","PeriodicalId":261625,"journal":{"name":"2022 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123656258","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: 1

SWAP: Secure Warning Messages Authentication and Propagation in Internet of Vehicles 车联网中安全警告信息的认证与传播

2022 International Conference on Software, Telecommunications and Computer Networks (SoftCOM) Pub Date : 2022-09-22 DOI: 10.23919/softcom55329.2022.9911337

Alessandro Brighente, M. Conti, Harsha Vasudev

{"title":"SWAP: Secure Warning Messages Authentication and Propagation in Internet of Vehicles","authors":"Alessandro Brighente, M. Conti, Harsha Vasudev","doi":"10.23919/softcom55329.2022.9911337","DOIUrl":"https://doi.org/10.23919/softcom55329.2022.9911337","url":null,"abstract":"The sensing and communication capabilities of the Internet of Vehicles (IoV) allow for the design of safer Intelligent Transportation Systems (ITS), with capabilities for reduced crashes and drivers' injuries. To this aim, entities in the IoV can autonomously exchange Warning Messages (WMs) on the road status to help drivers, passengers, and vehicles to take immediate actions and reduce road accidents. WMs authentication, timely propagation, and integrity is a fundamental requirement, as the injection of false WMs or their delay by a malicious user can lead to accidents or traffic congestion. The currently available WMs authentication and propagation schemes focus on the security properties, without however accounting for the scalability issues related to the large number of entities connected in the IoV. In this paper, we propose Secure Warning Message Authentication and Propagation (SWAP), an authentication protocol specifically designed for WM propagation in the Internet of Vehicles (IoV). We introduce the Warning Message Authority (WMA), a novel entity responsible for secure WMs handling. Thanks to the WMA, WMs are managed by dedicated resources that allow for the timely delivery of safety-critical information, avoiding delays due to network congestion at the Trusted Authority (TA). We prove the security of SWAP by using the Random Oracle Model (ROM) and via security analysis. Compared to state of the art authentication schemes, SWAP reduces the number of communication bits by 100 bits, and provides a ten-fold decrease of the computation time.","PeriodicalId":261625,"journal":{"name":"2022 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127223233","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

Telecom Fraud Detection with Machine Learning on Imbalanced Dataset 基于不平衡数据集的机器学习电信欺诈检测

2022 International Conference on Software, Telecommunications and Computer Networks (SoftCOM) Pub Date : 2022-09-22 DOI: 10.23919/softcom55329.2022.9911518

Ivan Krasić, S. Celar

引用次数: 2