Sentiment analysis is the process of recognizing and categorizing the emotions being expressed in a textual source. Tweets are commonly used to generate a large amount of sentiment data after they are analyzed. These feelings data help to learn about people's thoughts on a various range of topics. People are typically attracted for researching positive and negative reviews, which contain dislikes and likes, shared by the consumers concerning the features of a certain service or product. Therefore, the aspects or features of the product/ service play an important role in opinion mining. Furthermore to enough work being carried out in text mining, feature extraction in opinion mining is presently becoming a hot research field. In this paper, we focus on the study of feature extractors because of their importance in classification performance. The feature extraction is the most critical aspect of opinion classification since classification efficiency can be degraded if features are not properly chosen. A few scientific researchers have addressed the issue of feature extraction. And we found in the literature that almost every article deals with one or two feature extractors. For that, we decided in this paper to cover all the most popular feature extractors which are BOW, N-grams, TF-IDF, Word2vec, GloVe and FastText. In general, this paper will discuss the existing feature extractors in the opinion mining domain. Also, it will present the advantages and the inconveniences of each extractor. Moreover, a comparative study is performed for determining the most efficient combination CNN/extractor in terms of accuracy, precision, recall, and F1 measure.
{"title":"Evaluation of different extractors of features at the level of sentiment analysis","authors":"Fatima Es-Sabery, Khadija Es-Sabery, Hamid Garmani, Junaid Qadir, Abdellatif Hair","doi":"10.36244/icj.2022.2.9","DOIUrl":"https://doi.org/10.36244/icj.2022.2.9","url":null,"abstract":"Sentiment analysis is the process of recognizing and categorizing the emotions being expressed in a textual source. Tweets are commonly used to generate a large amount of sentiment data after they are analyzed. These feelings data help to learn about people's thoughts on a various range of topics. People are typically attracted for researching positive and negative reviews, which contain dislikes and likes, shared by the consumers concerning the features of a certain service or product. Therefore, the aspects or features of the product/ service play an important role in opinion mining. Furthermore to enough work being carried out in text mining, feature extraction in opinion mining is presently becoming a hot research field. In this paper, we focus on the study of feature extractors because of their importance in classification performance. The feature extraction is the most critical aspect of opinion classification since classification efficiency can be degraded if features are not properly chosen. A few scientific researchers have addressed the issue of feature extraction. And we found in the literature that almost every article deals with one or two feature extractors. For that, we decided in this paper to cover all the most popular feature extractors which are BOW, N-grams, TF-IDF, Word2vec, GloVe and FastText. In general, this paper will discuss the existing feature extractors in the opinion mining domain. Also, it will present the advantages and the inconveniences of each extractor. Moreover, a comparative study is performed for determining the most efficient combination CNN/extractor in terms of accuracy, precision, recall, and F1 measure.","PeriodicalId":42504,"journal":{"name":"Infocommunications Journal","volume":"62 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90687913","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}
George Matta, Sebastian Chlup, A. Shaaban, Christoph Schmittner, Andreas Pinzenöhler, Elke Szalai, Markus Tauber
The Internet of Things (IoT) and cloud technologies are increasingly implemented in the form of Cyber-Physical Systems of Systems (CPSoS) for the railway sector. In order to satisfy the security requirements of Cyber-Physical Systems (CPS), domainspecific risk identification assessment procedures have been developed. Threat modelling is one of the most commonly used methods for threat identification for the security analysis of CPSoS and is capable of targeting various domains. This paper reports our experience of using a risk management framework identify the most critical security vulnerabilities in CPSoS in the domain and shows the broader impact this work can have on the domain of safety and security management. Moreover, we emphasize the application of common analytical methods for cyber-security based on international industry standards to identify the most vulnerable assets. These will be applied to a meta-model for automated railway systems in the concept phase to support the development and deployment of these systems. Furthermore, it is the first step to create a secure and standard complaint system by design.
{"title":"Risk Management and Standard Compliance for Cyber-Physical Systems of Systems","authors":"George Matta, Sebastian Chlup, A. Shaaban, Christoph Schmittner, Andreas Pinzenöhler, Elke Szalai, Markus Tauber","doi":"10.36244/icj.2021.2.5","DOIUrl":"https://doi.org/10.36244/icj.2021.2.5","url":null,"abstract":"The Internet of Things (IoT) and cloud technologies are increasingly implemented in the form of Cyber-Physical Systems of Systems (CPSoS) for the railway sector. In order to satisfy the security requirements of Cyber-Physical Systems (CPS), domainspecific risk identification assessment procedures have been developed. Threat modelling is one of the most commonly used methods for threat identification for the security analysis of CPSoS and is capable of targeting various domains. This paper reports our experience of using a risk management framework identify the most critical security vulnerabilities in CPSoS in the domain and shows the broader impact this work can have on the domain of safety and security management. Moreover, we emphasize the application of common analytical methods for cyber-security based on international industry standards to identify the most vulnerable assets. These will be applied to a meta-model for automated railway systems in the concept phase to support the development and deployment of these systems. Furthermore, it is the first step to create a secure and standard complaint system by design.","PeriodicalId":42504,"journal":{"name":"Infocommunications Journal","volume":"1 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88317159","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}
Mehran Amini, Hatwagn Miklos F., G. Mikulai, L. Kóczy
Fuzzy cognitive maps (FCM) have been broadly employed to analyze complex and decidedly uncertain systems in modeling, forecasting, decision making, etc. Road traffic flow is also notoriously known as a highly uncertain nonlinear and complex system. Even though applications of FCM in risk analysis have been presented in various engineering fields, this research aims at modeling road traffic flow based on macroscopic characteristics through FCM. Therefore, a simulation of variables involved with road traffic flow carried out through FCM reasoning on historical data collected from the e-toll dataset of Hungarian networks of freeways. The proposed FCM model is developed based on 58 selected freeway segments as the “concepts” of the FCM; moreover, a new inference rule for employing in FCM reasoning process along with its algorithms have been presented. The results illustrate FCM representation and computation of the real segments with their main road traffic-related characteristics that have reached an equilibrium point. Furthermore, a simulation of the road traffic flow by performing the analysis of customized scenarios is presented, through which macroscopic modeling objectives such as predicting future road traffic flow state, route guidance in various scenarios, freeway geometric characteristics indication, and effectual mobility can be evaluated.
{"title":"Developing a macroscopic model based on fuzzy cognitive map for road traffic flow simulation","authors":"Mehran Amini, Hatwagn Miklos F., G. Mikulai, L. Kóczy","doi":"10.36244/icj.2021.3.2","DOIUrl":"https://doi.org/10.36244/icj.2021.3.2","url":null,"abstract":"Fuzzy cognitive maps (FCM) have been broadly employed to analyze complex and decidedly uncertain systems in modeling, forecasting, decision making, etc. Road traffic flow is also notoriously known as a highly uncertain nonlinear and complex system. Even though applications of FCM in risk analysis have been presented in various engineering fields, this research aims at modeling road traffic flow based on macroscopic characteristics through FCM. Therefore, a simulation of variables involved with road traffic flow carried out through FCM reasoning on historical data collected from the e-toll dataset of Hungarian networks of freeways. The proposed FCM model is developed based on 58 selected freeway segments as the “concepts” of the FCM; moreover, a new inference rule for employing in FCM reasoning process along with its algorithms have been presented. The results illustrate FCM representation and computation of the real segments with their main road traffic-related characteristics that have reached an equilibrium point. Furthermore, a simulation of the road traffic flow by performing the analysis of customized scenarios is presented, through which macroscopic modeling objectives such as predicting future road traffic flow state, route guidance in various scenarios, freeway geometric characteristics indication, and effectual mobility can be evaluated.","PeriodicalId":42504,"journal":{"name":"Infocommunications Journal","volume":"64 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90370960","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 research topic presented in this paper belongs to small training data problem in machine learning (especially in deep learning), it intends to help the work of those working in medicine by analyzing pathological X-ray recordings, using only very few images. This scenario is a particularly hot issue nowadays: how could a new disease for which only limited data are available be diagnosed using features of previous diseases? In this problem, so-called few-shot learning, the difficulty of the classification task is to learn the unique feature characteristics associated with the classes. Although there are solutions, but if the images come from different views, they will not handle these views well. We proposed an improved method, so-called Double-View Matching Network (DVMN based on the deep neural network), which solves the few-shot learning problem as well as the different views of the pathological recordings in the images. The main contribution of this is the convolutional neural network for feature extraction and handling the multi-view in image representation. Our method was tested in the classification of images showing unknown COVID-19 symptoms in an environment designed for learning a few samples, with prior meta-learning on images of other diseases only. The results show that DVMN reaches better accuracy on multi-view dataset than simple Matching Network without multi-view handling.
{"title":"Double-View Matching Network for Few-Shot Learning to Classify Covid-19 in X-ray images","authors":"G. Szűcs, Marcell Németh","doi":"10.36244/ICJ.2021.1.4","DOIUrl":"https://doi.org/10.36244/ICJ.2021.1.4","url":null,"abstract":"The research topic presented in this paper belongs to small training data problem in machine learning (especially in deep learning), it intends to help the work of those working in medicine by analyzing pathological X-ray recordings, using only very few images. This scenario is a particularly hot issue nowadays: how could a new disease for which only limited data are available be diagnosed using features of previous diseases? In this problem, so-called few-shot learning, the difficulty of the classification task is to learn the unique feature characteristics associated with the classes. Although there are solutions, but if the images come from different views, they will not handle these views well. We proposed an improved method, so-called Double-View Matching Network (DVMN based on the deep neural network), which solves the few-shot learning problem as well as the different views of the pathological recordings in the images. The main contribution of this is the convolutional neural network for feature extraction and handling the multi-view in image representation. Our method was tested in the classification of images showing unknown COVID-19 symptoms in an environment designed for learning a few samples, with prior meta-learning on images of other diseases only. The results show that DVMN reaches better accuracy on multi-view dataset than simple Matching Network without multi-view handling.","PeriodicalId":42504,"journal":{"name":"Infocommunications Journal","volume":"27 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75223963","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}
One of the latest developments today is the 5G, or 5th generation mobile network. In addition to a number of innovations, the new system also includes millimeter-wavelength frequency ranges denoted with FR2, that formerly not applied for these specific purposes. Proper management of the transmitter and receiver antenna beams is required for efficient communication in this frequency range. For future use, the simplest implementation way is electronically shaping the antenna beams by an algorithm to orient the antennas in the best possible direction. The prerequisites for these algorithms are appropriate propagation models, which are currently lacking, and those that publicly available are not accurate enough for practical use.
{"title":"Improved Model for Indoor Propagation Loss in the 5G FR2 Frequency Band","authors":"Árpád László Makara, L. Csurgai-Horváth","doi":"10.36244/ICJ.2021.1.1","DOIUrl":"https://doi.org/10.36244/ICJ.2021.1.1","url":null,"abstract":"One of the latest developments today is the 5G, or 5th generation mobile network. In addition to a number of innovations, the new system also includes millimeter-wavelength frequency ranges denoted with FR2, that formerly not applied for these specific purposes. Proper management of the transmitter and receiver antenna beams is required for efficient communication in this frequency range. For future use, the simplest implementation way is electronically shaping the antenna beams by an algorithm to orient the antennas in the best possible direction. The prerequisites for these algorithms are appropriate propagation models, which are currently lacking, and those that publicly available are not accurate enough for practical use.","PeriodicalId":42504,"journal":{"name":"Infocommunications Journal","volume":"11 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84484062","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}
Silia Maksuti, Mario Zsilak, Markus Tauber, J. Delsing
A system of systems integrates systems that function independently but are networked together for a period of time to achieve a higher goal. These systems evolve over time and have emergent properties. Therefore, even with security controls in place, it is difficult to maintain a required level of security for the system of systems as a whole because uncertainties may arise at runtime. Uncertainties can occur from internal factors, such as malfunctions of a system, or from external factors, such as malicious attacks. Self-adaptation is an approach that allows a system to adapt in the face of such uncertainties without human intervention. This work outlines the progress made towards security mitigation in system of systems using a generic autonomic management system to assist engineers in developing self-adaptive systems. The manuscript describes the proposed system design, its implementation as part of the Eclipse Arrowhead framework, and its functionality in a smart agriculture use case. The system is designed and implemented in such a way that it can be reused and extended for a variety of use cases without requiring major changes.
{"title":"Security and Autonomic Management in System of Systems","authors":"Silia Maksuti, Mario Zsilak, Markus Tauber, J. Delsing","doi":"10.36244/icj.2021.3.7","DOIUrl":"https://doi.org/10.36244/icj.2021.3.7","url":null,"abstract":"A system of systems integrates systems that function independently but are networked together for a period of time to achieve a higher goal. These systems evolve over time and have emergent properties. Therefore, even with security controls in place, it is difficult to maintain a required level of security for the system of systems as a whole because uncertainties may arise at runtime. Uncertainties can occur from internal factors, such as malfunctions of a system, or from external factors, such as malicious attacks. Self-adaptation is an approach that allows a system to adapt in the face of such uncertainties without human intervention. This work outlines the progress made towards security mitigation in system of systems using a generic autonomic management system to assist engineers in developing self-adaptive systems. The manuscript describes the proposed system design, its implementation as part of the Eclipse Arrowhead framework, and its functionality in a smart agriculture use case. The system is designed and implemented in such a way that it can be reused and extended for a variety of use cases without requiring major changes.","PeriodicalId":42504,"journal":{"name":"Infocommunications Journal","volume":"69 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79557968","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}
Árpád László Makara, A. Reichardt, L. Csurgai-Horváth
Computing capacities for numerical modelling are available to an unprecedented extent today. The spread of various artificial intelligence (AI) -based solutions (which in many cases are also resource-intensive operations) is also facilitated by this increase in capacity, which offers several new opportunities in this area. On the one hand, optimization tasks can be done quickly, on the other hand, it is also possible to solve (estimate) problems where we cannot (for some reason) create a model for the initial problem. In our article, we investigate how to apply artificial intelligence-based solutions to electromagnetic field computing tasks as efficiently as possible. The required theoretical summary presents an implemented application: optimization of electrostatic ion engine accelerator electrodes for orbit correction operations. To solve each problem, we used methods from the supervised machine learning toolkit, usually along with LMS (least mean square method) update steps. All inputs required for AI were solved by numerical space calculation (primarily using the finite element method). The data input required to optimize the electrodes of an ion thruster can come from two sources: measurement data or simulation results. Given that the operating environment of a satellite can be modelled in a vacuum chamber, it is a particularly difficult issue to perform the measurement, but even more difficult in the case of optimisation. Therefore, an effective solution to the problem can only be achieved by simulation. The primary goal of this research is to optimise the fuel (in this case, the number of ions) during operation, with the stated aim of maximising the time of operation of the spacecraft.
{"title":"AI-Based Electrode Optimisation for Small Satellite Ion Thrusters","authors":"Árpád László Makara, A. Reichardt, L. Csurgai-Horváth","doi":"10.36244/icj.2021.4.1","DOIUrl":"https://doi.org/10.36244/icj.2021.4.1","url":null,"abstract":"Computing capacities for numerical modelling are available to an unprecedented extent today. The spread of various artificial intelligence (AI) -based solutions (which in many cases are also resource-intensive operations) is also facilitated by this increase in capacity, which offers several new opportunities in this area. On the one hand, optimization tasks can be done quickly, on the other hand, it is also possible to solve (estimate) problems where we cannot (for some reason) create a model for the initial problem. In our article, we investigate how to apply artificial intelligence-based solutions to electromagnetic field computing tasks as efficiently as possible. The required theoretical summary presents an implemented application: optimization of electrostatic ion engine accelerator electrodes for orbit correction operations. To solve each problem, we used methods from the supervised machine learning toolkit, usually along with LMS (least mean square method) update steps. All inputs required for AI were solved by numerical space calculation (primarily using the finite element method). The data input required to optimize the electrodes of an ion thruster can come from two sources: measurement data or simulation results. Given that the operating environment of a satellite can be modelled in a vacuum chamber, it is a particularly difficult issue to perform the measurement, but even more difficult in the case of optimisation. Therefore, an effective solution to the problem can only be achieved by simulation. The primary goal of this research is to optimise the fuel (in this case, the number of ions) during operation, with the stated aim of maximising the time of operation of the spacecraft.","PeriodicalId":42504,"journal":{"name":"Infocommunications Journal","volume":"258 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83504985","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}
Ádám Marosits, Zsolt Tabi, Zsófia Kallus, Péter Vaderna, I. Gódor, Z. Zimborás
Quantum Annealing provides a heuristic method leveraging quantum mechanics for solving Quadratic Unconstrained Binary Optimization problems. Existing Quantum Annealing processing units are readily available via cloud platform access for a wide range of use cases. In particular, a novel device, the D-Wave Advantage has been recently released. In this paper, we study the applicability of Maximum Likelihood (ML) Channel Decoder problems for MIMO scenarios in centralized RAN. The main challenge for exact optimization of ML decoders with ever-increasing demand for higher data rates is the exponential increase of the solution space with problem sizes. Since current 5G solutions can only use approximate methodologies, Kim et al. [1] leveraged Quantum Annealing for large MIMO problems with phase shift keying and quadrature amplitude modulation scenarios. Here, we extend upon their work and present embedding limits for both more complex modulation and higher receiver / transmitter numbers using the Pegasus P16 topology of the D-Wave Advantage system.
{"title":"Exploring Embeddings for MIMO Channel Decoding on Quantum Annealers","authors":"Ádám Marosits, Zsolt Tabi, Zsófia Kallus, Péter Vaderna, I. Gódor, Z. Zimborás","doi":"10.36244/ICJ.2021.1.2","DOIUrl":"https://doi.org/10.36244/ICJ.2021.1.2","url":null,"abstract":"Quantum Annealing provides a heuristic method leveraging quantum mechanics for solving Quadratic Unconstrained Binary Optimization problems. Existing Quantum Annealing processing units are readily available via cloud platform access for a wide range of use cases. In particular, a novel device, the D-Wave Advantage has been recently released. In this paper, we study the applicability of Maximum Likelihood (ML) Channel Decoder problems for MIMO scenarios in centralized RAN. The main challenge for exact optimization of ML decoders with ever-increasing demand for higher data rates is the exponential increase of the solution space with problem sizes. Since current 5G solutions can only use approximate methodologies, Kim et al. [1] leveraged Quantum Annealing for large MIMO problems with phase shift keying and quadrature amplitude modulation scenarios. Here, we extend upon their work and present embedding limits for both more complex modulation and higher receiver / transmitter numbers using the Pegasus P16 topology of the D-Wave Advantage system.","PeriodicalId":42504,"journal":{"name":"Infocommunications Journal","volume":"30 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80146916","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}
This paper focuses on one of the most prominent IPv6 transition technologies named 464XLAT. The aim is to analyze the security threats that this technology might face. After carrying out the threat analysis using STRIDE method that stands for Spoofing, Tampering, Repudiation, Information Disclosure and Elevation of Privilege, and using DFD (Data-Flow Diagram) as a core for the analysis, we summarized the security vulnerabilities and attack points possibilities within this infrastructure. We have also built a testbed for 464XLAT topology using several virtual machines, which were created using Debian image. We used our testbed to perform DoS (Denial of Service) attack against the PLAT (provider-side translator) and monitor PLAT’s performance and the number of packets being translated under attack by different number of clients using the hping3 command.
本文重点介绍了目前最突出的IPv6转换技术之一——464XLAT。目的是分析该技术可能面临的安全威胁。在使用STRIDE方法(Spoofing, tampening, Repudiation, Information Disclosure and Elevation of Privilege)进行威胁分析后，我们以DFD (Data-Flow Diagram)为分析核心，总结了该基础架构中的安全漏洞和攻击点可能性。我们还使用几个虚拟机为464XLAT拓扑构建了一个测试平台，这些虚拟机是使用Debian映像创建的。我们使用我们的测试平台对PLAT(提供端转换器)执行DoS(拒绝服务)攻击，并使用hping3命令监控PLAT的性能和在不同数量的客户端攻击下被翻译的数据包数量。
{"title":"Identification of the Possible Security Issues of the 464XLAT IPv6 Transition Technology","authors":"A. Al-Azzawi, G. Lencse","doi":"10.36244/icj.2021.4.2","DOIUrl":"https://doi.org/10.36244/icj.2021.4.2","url":null,"abstract":"This paper focuses on one of the most prominent IPv6 transition technologies named 464XLAT. The aim is to analyze the security threats that this technology might face. After carrying out the threat analysis using STRIDE method that stands for Spoofing, Tampering, Repudiation, Information Disclosure and Elevation of Privilege, and using DFD (Data-Flow Diagram) as a core for the analysis, we summarized the security vulnerabilities and attack points possibilities within this infrastructure. We have also built a testbed for 464XLAT topology using several virtual machines, which were created using Debian image. We used our testbed to perform DoS (Denial of Service) attack against the PLAT (provider-side translator) and monitor PLAT’s performance and the number of packets being translated under attack by different number of clients using the hping3 command.","PeriodicalId":42504,"journal":{"name":"Infocommunications Journal","volume":"15 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78415679","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}
Our design for a novel UWB monopole antenna structure with reconfigurable band notch characteristics based on PIN diodes is presented in this paper. The proposed antenna is comprised of a modified circular patch and a partial ground plane. The band-notch characteristics are achieved by etching a slot on the partial ground plane and inserting three PIN diodes into the slots for adjusting the operating antenna bands. The reconfigurability is achieved by adding three PIN diodes to obtain eight states with UWB, dual and triple operating bands which can be obtained by changing the PIN state from ON to OFF, and vice versa. The proposed design shows a simple biasing process to switch the frequency bands with insignificant gain variation and low radiation efficiency reduction. The reconfigurability of the frequency is accomplished by adjusting the effective slot length through modifying the PIN diodes states at the desired operating bands. The desired operating frequency bands can be obtained by switching the diodes. A systematic parametric study based on a numerical analysis is invoked to verify and refine the proposed performance. The proposed antenna is fabricated on FR-4 substrate with dimensions of 50×60×1 mm3. The proposed antenna performance was tested experimentally and compared to the simulated results from CSTMW based on FIT. Experimental results were in concordance with simulated results. We found that the proposed antenna design had simple geometry and it was easy to control the frequency bands to suit the applications of WiMAX and WiFi systems.
{"title":"A Novel UWB Monopole Antenna with Reconfigurable Band Notch Characteristics Based on PIN Diodes","authors":"Yahieal Alnaiemy, L. Nagy","doi":"10.36244/icj.2021.3.4","DOIUrl":"https://doi.org/10.36244/icj.2021.3.4","url":null,"abstract":"Our design for a novel UWB monopole antenna structure with reconfigurable band notch characteristics based on PIN diodes is presented in this paper. The proposed antenna is comprised of a modified circular patch and a partial ground plane. The band-notch characteristics are achieved by etching a slot on the partial ground plane and inserting three PIN diodes into the slots for adjusting the operating antenna bands. The reconfigurability is achieved by adding three PIN diodes to obtain eight states with UWB, dual and triple operating bands which can be obtained by changing the PIN state from ON to OFF, and vice versa. The proposed design shows a simple biasing process to switch the frequency bands with insignificant gain variation and low radiation efficiency reduction. The reconfigurability of the frequency is accomplished by adjusting the effective slot length through modifying the PIN diodes states at the desired operating bands. The desired operating frequency bands can be obtained by switching the diodes. A systematic parametric study based on a numerical analysis is invoked to verify and refine the proposed performance. The proposed antenna is fabricated on FR-4 substrate with dimensions of 50×60×1 mm3. The proposed antenna performance was tested experimentally and compared to the simulated results from CSTMW based on FIT. Experimental results were in concordance with simulated results. We found that the proposed antenna design had simple geometry and it was easy to control the frequency bands to suit the applications of WiMAX and WiFi systems.","PeriodicalId":42504,"journal":{"name":"Infocommunications Journal","volume":"13 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79070230","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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