2022 International Balkan Conference on Communications and Networking (BalkanCom)最新文献_第2页

Markov Model Based Traffic Classification with Multiple Features 基于马尔可夫模型的多特征流量分类

2022 International Balkan Conference on Communications and Networking (BalkanCom) Pub Date : 2022-08-22 DOI: 10.1109/BalkanCom55633.2022.9900541

Oguz Kaan Koksal, R. Temelli, Huseyin Ozkan, O. Gurbuz

{"title":"Markov Model Based Traffic Classification with Multiple Features","authors":"Oguz Kaan Koksal, R. Temelli, Huseyin Ozkan, O. Gurbuz","doi":"10.1109/BalkanCom55633.2022.9900541","DOIUrl":"https://doi.org/10.1109/BalkanCom55633.2022.9900541","url":null,"abstract":"Traffic prioritization has recently become more critical and crucial for home Wi-Fi networks due to the increased number of connected devices and applications. While some of these applications are delay sensitive, some have high throughput requirements. Quality of Service (QoS) in Wi-Fi is achieved via differentiation and prioritization of traffic streams, which can be performed successfully as long as the packets can be classified with high precision. As a solution for this problem, this paper presents a new Discrete Time Markov Chain-based traffic classification algorithm, which exploits a multidimensional feature set, named as k-Nearest Markov Component with 3 Dimensions (kNMC-3D). Considering results obtained on two different datasets with current, most popular multimedia applications from different categories, we present the performance of the proposed algorithm, kNMC-3D in comparison to kNMC, two feature extraction based machine learning techniques, Support Vector Machines (SVM) and Random Forest (RF) and a deep learning approach, Auto Encoder with RF (AE+RF). It is shown that kNMC-3D achieves 84.93% and 90.73% accuracy at the application level, 91.13% and 99.17% accuracy at category level on our dataset and a benchmark dataset, respectively. Outperforming the existing methods that focus mainly on feature extraction, kNMC-3D prevents information loss by making use of sequentiality in the traffic, while it improves kNMC by considering multiple features, number of bits, inter-arrival times and number of packets.","PeriodicalId":114443,"journal":{"name":"2022 International Balkan Conference on Communications and Networking (BalkanCom)","volume":"8 24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114107781","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

Machine Learning Methods for Device Identification Using Wireless Fingerprinting 使用无线指纹识别设备的机器学习方法

2022 International Balkan Conference on Communications and Networking (BalkanCom) Pub Date : 2022-08-22 DOI: 10.1109/BalkanCom55633.2022.9900723

Srdjan Sobot, Vukan Ninkovic, D. Vukobratović, Milan Pavlović, Miloš Radovanović

{"title":"Machine Learning Methods for Device Identification Using Wireless Fingerprinting","authors":"Srdjan Sobot, Vukan Ninkovic, D. Vukobratović, Milan Pavlović, Miloš Radovanović","doi":"10.1109/BalkanCom55633.2022.9900723","DOIUrl":"https://doi.org/10.1109/BalkanCom55633.2022.9900723","url":null,"abstract":"Industrial Internet of Things (IoT) systems increasingly rely on wireless communication standards. In a common industrial scenario, indoor wireless IoT devices communicate with access points to deliver data collected from industrial sensors, robots and factory machines. Due to static or quasi-static locations of IoT devices and access points, historical observations of IoT device channel conditions provide a possibility to precisely identify the device without observing its traditional identifiers (e.g., MAC or IP address). Such device identification methods based on wireless fingerprinting gained increased attention lately as an additional cyber-security mechanism for critical IoT infrastructures. In this paper, we perform a systematic study of a large class of machine learning algorithms for device identification using wireless fingerprints for the most popular cellular and Wi-Fi IoT technologies. We design, implement, deploy, collect relevant data sets, train and test a multitude of machine learning algorithms, as a part of the complete end-to-end solution design for device identification via wireless fingerprinting. The proposed solution is currently being deployed in a real-world industrial IoT environment as part of H2020 project COLLABS.","PeriodicalId":114443,"journal":{"name":"2022 International Balkan Conference on Communications and Networking (BalkanCom)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128984377","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

Deep Reinforcement Learning Applied to Computation Offloading of Vehicular Applications: A Comparison 深度强化学习在车辆应用计算卸载中的应用:比较

2022 International Balkan Conference on Communications and Networking (BalkanCom) Pub Date : 2022-08-22 DOI: 10.1109/BalkanCom55633.2022.9900545

Mieszko Ferens, Diego Hortelano, I. de Miguel, Ramón J. Durán Barroso, J. Aguado, L. Ruiz, N. Merayo, P. Fernández, R. Lorenzo, E. Abril

{"title":"Deep Reinforcement Learning Applied to Computation Offloading of Vehicular Applications: A Comparison","authors":"Mieszko Ferens, Diego Hortelano, I. de Miguel, Ramón J. Durán Barroso, J. Aguado, L. Ruiz, N. Merayo, P. Fernández, R. Lorenzo, E. Abril","doi":"10.1109/BalkanCom55633.2022.9900545","DOIUrl":"https://doi.org/10.1109/BalkanCom55633.2022.9900545","url":null,"abstract":"An observable trend in recent years is the increasing demand for more complex services designed to be used with portable or automotive embedded devices. The problem is that these devices may lack the computational resources necessary to comply with service requirements. To solve it, cloud and edge computing, and in particular, the recent multi-access edge computing (MEC) paradigm, have been proposed. By offloading the processing of computational tasks from devices or vehicles to an external network, a larger amount of computational resources, placed in different locations, becomes accessible. However, this in turn creates the issue of deciding where each task should be executed. In this paper, we model the problem of computation offloading of vehicular applications to solve it using deep reinforcement learning (DRL) and evaluate the performance of different DRL algorithms and heuristics, showing the advantages of the former methods. Moreover, the impact of two scheduling techniques in computing nodes and two reward strategies in the DRL methods are also analyzed and discussed.","PeriodicalId":114443,"journal":{"name":"2022 International Balkan Conference on Communications and Networking (BalkanCom)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128828331","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

Calibrated Probabilistic QoT Regression for Unestablished Lightpaths in Optical Networks 光网络中未建立光路的校正概率QoT回归

2022 International Balkan Conference on Communications and Networking (BalkanCom) Pub Date : 2022-08-22 DOI: 10.1109/BalkanCom55633.2022.9900791

Nicola Di Cicco, Memedhe Ibrahimi, C. Rottondi, M. Tornatore

{"title":"Calibrated Probabilistic QoT Regression for Unestablished Lightpaths in Optical Networks","authors":"Nicola Di Cicco, Memedhe Ibrahimi, C. Rottondi, M. Tornatore","doi":"10.1109/BalkanCom55633.2022.9900791","DOIUrl":"https://doi.org/10.1109/BalkanCom55633.2022.9900791","url":null,"abstract":"Quality-of-Transmission (QoT) regression of unestablished lightpaths is a fundamental problem in Machine Learning applied to optical networks. Even though this problem is well-investigated in current literature, many state-of-the-art approaches either predict point-estimates of the QoT or make simplifying assumptions about the QoT distribution. Because of this, during lightpath deployment, an operator might take either overly-aggressive or overly-conservative decisions due to biased predictions. In this paper, we leverage state-of-the-art Gradient Boosting Decision Tree (GBDT) models and recent advances in uncertainty calibration to perform QoT probabilistic regression for unestablished lightpaths. Calibration of a regression model allows for an accurate modeling of the QoT Cumulative Distribution Function (CDF) without any prior assumption on the QoT distribution. In our illustrative experimental results, we show that our calibrated GBDT model’s predictions provide accurate confidence interval estimates, even when only few samples per lightpath configuration are available at training time.","PeriodicalId":114443,"journal":{"name":"2022 International Balkan Conference on Communications and Networking (BalkanCom)","volume":"152 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114638601","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

High-Mobility Wireless Channel Measurements at 5.9 GHz in an Urban Environment 城市环境下5.9 GHz高移动性无线信道测量

2022 International Balkan Conference on Communications and Networking (BalkanCom) Pub Date : 2022-08-22 DOI: 10.1109/BalkanCom55633.2022.9900633

Faruk Pasic, Stefan Pratschner, R. Langwieser, C. Mecklenbräuker

引用次数: 5

An Architecture of MySQL Storage Engines to Increase the Resource Utilization 提高资源利用率的MySQL存储引擎架构

2022 International Balkan Conference on Communications and Networking (BalkanCom) Pub Date : 2022-08-22 DOI: 10.1109/BalkanCom55633.2022.9900616

J. Janjua, T. A. Khan, Sidra Zulfiqar, Muhammad Usman

引用次数: 2

Experimental Implementation of Index Modulation for Molecular Communication 分子通信索引调制的实验实现

2022 International Balkan Conference on Communications and Networking (BalkanCom) Pub Date : 2022-08-22 DOI: 10.1109/BalkanCom55633.2022.9900864

Gokce Duzyol, Kerem Avcı, Zeliha Cansu Canbek Ozdil, A. E. Pusane, T. Tuğcu

{"title":"Experimental Implementation of Index Modulation for Molecular Communication","authors":"Gokce Duzyol, Kerem Avcı, Zeliha Cansu Canbek Ozdil, A. E. Pusane, T. Tuğcu","doi":"10.1109/BalkanCom55633.2022.9900864","DOIUrl":"https://doi.org/10.1109/BalkanCom55633.2022.9900864","url":null,"abstract":"Molecular communications is a novel communication method that is ideal for nano- and micro-sized scenarios, where conventional radio-frequency communication systems are difficult to employ. Molecular communication via diffusion is a type of molecular communications, where molecules are utilized as information carriers between transmitters and receivers. To increase the communication quality/rate of these systems, multiple input multiple output setups are also considered. Index modulation, which uses the active transmitter index to convey information is one of the most recent methods that is considered in the literature. The main problem of the relevant literature is the dependence on analytical-only or simulation-based results due to the difficulty in designing proper experimental setups. This paper focuses on a physical testbed that implements index modulation for molecular communication. The considered channels are also modeled in COMSOL, and the corresponding simulations are performed. Results demonstrate that index modulated molecular communication systems can be physically achieved and can be used to successfully transmit data.","PeriodicalId":114443,"journal":{"name":"2022 International Balkan Conference on Communications and Networking (BalkanCom)","volume":"251 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121233459","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

Using Deep Learning for Detecting Mirroring Attacks on Smart Grid PMU Networks 基于深度学习的智能电网PMU网络镜像攻击检测

2022 International Balkan Conference on Communications and Networking (BalkanCom) Pub Date : 2022-08-22 DOI: 10.1109/BalkanCom55633.2022.9900658

Yusuf Korkmaz, Alvin Huseinović, Halil Bisgin, S. Mrdović, S. Uludag

{"title":"Using Deep Learning for Detecting Mirroring Attacks on Smart Grid PMU Networks","authors":"Yusuf Korkmaz, Alvin Huseinović, Halil Bisgin, S. Mrdović, S. Uludag","doi":"10.1109/BalkanCom55633.2022.9900658","DOIUrl":"https://doi.org/10.1109/BalkanCom55633.2022.9900658","url":null,"abstract":"Similar to any spoof detection systems, power grid monitoring systems and devices are subject to various cyberattacks by determined and well-funded adversaries. Many well-publicized real-world cyberattacks on power grid systems have been publicly reported. Phasor Measurement Units (PMUs) networks with Phasor Data Concentrators (PDCs) are the main building blocks of the overall wide area monitoring and situational awareness systems in the power grid. The data between PMUs and PDC(s) are sent through the legacy networks, which are subject to many attack scenarios under with no, or inadequate, countermeasures in protocols, such as IEEE 37.118-2. In this paper, we consider a stealthier data spoofing attack against PMU networks, called a mirroring attack, where an adversary basically injects a copy of a set of packets in reverse order immediately following their original positions, wiping out the correct values. To the best of our knowledge, for the first time in the literature, we consider a more challenging attack both in terms of the strategy and the lower percentage of spoofed attacks. As part of our countermeasure detection scheme, we make use of novel framing approach to make application of a 2D Convolutional Neural Network (CNN)-based approach which avoids the computational overhead of the classical sample-based classification algorithms. Our experimental evaluation results show promising results in terms of both high accuracy and true positive rates even under the aforementioned stealthy adversarial attack scenarios.","PeriodicalId":114443,"journal":{"name":"2022 International Balkan Conference on Communications and Networking (BalkanCom)","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115257373","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

Evaluating Path Selection Strategies with Blockchain-based Routing in Multi-Domain SDNs 多域sdn中基于区块链路由的路径选择策略评估

2022 International Balkan Conference on Communications and Networking (BalkanCom) Pub Date : 2022-08-22 DOI: 10.1109/BalkanCom55633.2022.9900749

Evrim Guler, Murat Karakus, S. Uludag

{"title":"Evaluating Path Selection Strategies with Blockchain-based Routing in Multi-Domain SDNs","authors":"Evrim Guler, Murat Karakus, S. Uludag","doi":"10.1109/BalkanCom55633.2022.9900749","DOIUrl":"https://doi.org/10.1109/BalkanCom55633.2022.9900749","url":null,"abstract":"Software-Defined Networking (SDN) has emerged as one of the most prolific inventions in the general area of computer communications over the past decade. Among many of the touted benefits, SDN architecture facilitated by OpenFlow has the potential to help network administrators to provide End-to-End (E2E) Quality of Service (QoS)-guaranteed paths for flows among networks while providing finer-granular flow management along with global network view. In our previous work, we have introduced QoSChain to amalgamate the advantages of blockchain and SDN for inter-network QoS provisioning to orchestrate an agile and software-driven traffic management framework in order to facilitate cross-network policy automation, assurance, E2E visibility, control and validation. In this study, we focus on the impact of the path selection strategies on the performance of the overall QoSChain performance. Specifically, we exploit three simple but effective path selection strategies, First Feasible Path Selection (FFPS), Random Feasible Path Selection (RFPS), and Minimum Hop Path Selection (MHPS), to evaluate their performance, impact, and overhead in terms of the flow setup time, message overhead, and network resource consumption metrics. Our preliminary simulations results show that the path selection plays an important role in the overall performance with hop count minimization delivering a superior performance offset by an initial higher setup times.","PeriodicalId":114443,"journal":{"name":"2022 International Balkan Conference on Communications and Networking (BalkanCom)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115380578","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

Health Risk Assessment with Federated Learning 健康风险评估与联邦学习

2022 International Balkan Conference on Communications and Networking (BalkanCom) Pub Date : 2022-08-22 DOI: 10.1109/BalkanCom55633.2022.9900733

Ioanna Diamantoulaki, P. Diamantoulakis, Pavlos S. Bouzinis, P. Sarigiannidis, G. Karagiannidis

{"title":"Health Risk Assessment with Federated Learning","authors":"Ioanna Diamantoulaki, P. Diamantoulakis, Pavlos S. Bouzinis, P. Sarigiannidis, G. Karagiannidis","doi":"10.1109/BalkanCom55633.2022.9900733","DOIUrl":"https://doi.org/10.1109/BalkanCom55633.2022.9900733","url":null,"abstract":"The latest growth of storage capabilities has led to an accumulating volume of medical data stored locally by various healthcare entities. Given the recent progress observed in the domain of artificial intelligence, these data could be efficiently exploited, leading to improved and less expensive healthcare conditions. However, the common practice is medical data to be solely locally used, ending up poorly exploited, due to strict sharing restrictions stemming mainly from privacy limitation of their sensitive nature. Considering the centralized character of conventional machine learning approaches, it is apparent that they cannot reassure the privacy required. On the other hand, federated learning (FL) can be regarded as an upcoming and promising answer to efficient exploitation of medical data, considering its decentralized approach. In more details, FL can enable collaboration among various participating entities on the development and training of a common, central and fully shared model without need of sharing owned sensitive data. Thus, apparently FL approach not only can mitigate the privacy-preservation issues but can lead to the development of reliable and robust healthcare tools. Indicatively, FL can facilitate the development of a model capable of assessing the health risk, which can be a vital tool for medical sciences. To this end, in this work we present a tool capable of assessing the occurrence of different diseases or complications. This tool is based on FL technique utilizing deep neural network model. The FL model developed herein is indicatively applied to four different medical applications proving its generality in the healthcare domain. The FL approach discussed herein is compared with a corresponding centralized learning. According to the demonstrated results, FL can consist a useful health risk assessment tool exhibiting acceptable performance while preserving privacy in sensitive medical data.","PeriodicalId":114443,"journal":{"name":"2022 International Balkan Conference on Communications and Networking (BalkanCom)","volume":"353 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115982746","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