Marius Iordache, Cristian Patachia, Oana Badita, Bogdan Rusti, K. Trichias, J. Brenes
{"title":"5G Open Testbeds and Infrastructure extensions for NetApps advanced experiments","authors":"Marius Iordache, Cristian Patachia, Oana Badita, Bogdan Rusti, K. Trichias, J. Brenes","doi":"10.1109/comm54429.2022.9817289","DOIUrl":"https://doi.org/10.1109/comm54429.2022.9817289","url":null,"abstract":"While 5G Non-Stand Alone (NSA) networks are quickly being deployed across multiple nations, providing a first sense of the capabilities of 5G connectivity, the adoption of 5G by various vertical industry sectors and its integration into their day-to-day operations is progressing slowly. This is partially due to the perceived complexity of deploying services over the 5G networks and due to the fact that the vertical stakeholders do not have a clear understanding of the potential and offerings of 5G. To address that, the concept of Network Applications (NetApps) is picking up steam which is set to assist with the deployment of vertical specific services and their seamless integration with 5G networks and vertical specific components. This paper, presents the work of the EU funded project VITAL-5G in deploying 5G Stand Alone (SA) testbeds in three real-life Transport & Logistics facilities across Europe, the necessary 5G network extensions and architectural considerations, their integration with a state-of-the-art experimentation platform and the use of NetApps to enable the seamless deployment of 5G-enabled vertical services.","PeriodicalId":118077,"journal":{"name":"2022 14th International Conference on Communications (COMM)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132913477","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":"Performance Analysis of Transport Layer Congestion on 5G Systems","authors":"Gordana Barb, Cristina Andras, Cornel Balint","doi":"10.1109/comm54429.2022.9817358","DOIUrl":"https://doi.org/10.1109/comm54429.2022.9817358","url":null,"abstract":"The development of 5G networks is still ongoing. 5G networks connect data, applications, transport systems and people in smart networked communication environments. It will require various protocols to support its multiples features. One of these includes the transport protocol, which is designed to provide high-speed data rates up to 400Gbps. In this paper, an analysis of the performance of transport layer congestion on 5G systems using the two types of File Transfer Protocol (FTP) traffic is presented. The performance of the Transmission Control Protocol (TCP) protocol using metrics such as user and cell throughput, round trip time, delay, and Physical Resource Block (PRB) utilization was specifically analyzed. The simulation study shows the differences between File transfer protocol with TCP slow start and File transfer protocol without TCP slow start.","PeriodicalId":118077,"journal":{"name":"2022 14th International Conference on Communications (COMM)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114855707","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":"Two-Stage Spatio- Temporal Vision Transformer for the Detection of Violent Scenes","authors":"M. Constantin, B. Ionescu","doi":"10.1109/comm54429.2022.9817200","DOIUrl":"https://doi.org/10.1109/comm54429.2022.9817200","url":null,"abstract":"The rapid expansion and adoption of CCTV systems brings with itself a series of problems that, if remain unchecked, have the potential of hindering the advantages brought by such systems and reduce the effectiveness of this type of system in security surveillance scenarios. The possibly vast quantities of data associated with a CCTV system that covers a city or problematic areas of that city, venues, events, industrial sites or even smaller security perimeters can over-whelm the human operators and make it hard to distinguish important security events from the rest of the normal data. Therefore, the creation of automated systems that are able to provide operators with accurate alarms when certain events take place is of paramount importance, as this can heavily reduce their workload and improve the efficiency of the system. In this regard, we propose a Two-Stage Vision Transformer-based (2SViT) system for the detection of violent scenes. In this setup, the first stage handles frame-level processing, while the second stage processes temporal information by gathering frame-level features. We train and validate our proposed Transformer architecture on the popular XD- Violence dataset, while testing some size variations for the architecture, and show good results when compared with baseline scores.","PeriodicalId":118077,"journal":{"name":"2022 14th International Conference on Communications (COMM)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131640523","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":"Multi Wideband Stacked Cylindrical-Rectangular DRA for S, C, X, and Ku Applications","authors":"Farah S. Hasan, Saja R. Aldabes, Yanal S. Faouri","doi":"10.1109/comm54429.2022.9817187","DOIUrl":"https://doi.org/10.1109/comm54429.2022.9817187","url":null,"abstract":"This paper proposes a quad-wideband stacked dielectric resonator antenna intended for modern communications. Bandwidth enhancement methods were used to configure antenna characteristics. The DRA consists of several dielectric resonators to form a special shape installed on a grooved ground. Four wide bands were achieved, the first band ranging (3.82 − 4.52) GHz with fractional bandwidth of 16.78 %, the second band covers (5.05–6.77) GHz with fractional bandwidth of 28.9 %, the third band covers (7.76–9.47) GHz with fractional bandwidth 19.8 % and the fourth is ranging (12.66 – 14.98) GHz with fractional bandwidth 16.78 %. Several antenna results are studied for a complete understanding of the proposed antenna behavior.","PeriodicalId":118077,"journal":{"name":"2022 14th International Conference on Communications (COMM)","volume":"25 3-4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116700166","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}
James A. Latshaw, D. Popescu, John A. Snoap, C. Spooner
{"title":"Using Capsule Networks to Classify Digitally Modulated Signals with Raw I/Q Data","authors":"James A. Latshaw, D. Popescu, John A. Snoap, C. Spooner","doi":"10.1109/COMM54429.2022.9817229","DOIUrl":"https://doi.org/10.1109/COMM54429.2022.9817229","url":null,"abstract":"Machine learning has become a powerful tool for solving problems in various engineering and science areas, including the area of communication systems. This paper presents the use of capsule networks for classification of digitally modulated signals using the I/Q signal components. The generalization ability of a trained capsule network to correctly classify the classes of digitally modulated signals that it has been trained to recognize is also studied by using two different datasets that contain similar classes of digitally modulated signals but that have been generated independently. Results indicate that the capsule networks are able to achieve high classification accuracy. However, these networks are susceptible to the datashift problem which will be discussed in this paper.","PeriodicalId":118077,"journal":{"name":"2022 14th International Conference on Communications (COMM)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125105421","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}
Paul Irofti, Andrei Puatracscu, Andrei Iulian Hiji
{"title":"Unsupervised Abnormal Traffic Detection through Topological Flow Analysis","authors":"Paul Irofti, Andrei Puatracscu, Andrei Iulian Hiji","doi":"10.48550/arXiv.2205.07109","DOIUrl":"https://doi.org/10.48550/arXiv.2205.07109","url":null,"abstract":"Cyberthreats are a permanent concern in our modern technological world. In the recent years, sophisticated traffic analysis techniques and anomaly detection (AD) algorithms have been employed to face the more and more subversive adversarial attacks. A malicious intrusion, defined as an invasive action in-tending to illegally exploit private resources, manifests through unusual data traffic and/or abnormal connectivity pattern. Despite the plethora of statistical or signature-based detectors currently provided in the literature, the topological connectivity component of a malicious flow is less exploited. Furthermore, a great proportion of the existing statistical intrusion detectors are based on supervised learning, that relies on labeled data. By viewing network flows as weighted directed interactions between a pair of nodes, in this paper we present a simple method that facilitate the use of connectivity graph features in unsupervised anomaly detection algorithms. We test our methodology on real network traffic datasets and observe several improvements over standard AD.","PeriodicalId":118077,"journal":{"name":"2022 14th International Conference on Communications (COMM)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116467993","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}