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2023 6th International Conference on Advanced Communication Technologies and Networking (CommNet)最新文献

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Comparison between Emergency Calls over VoLTE and VoWiFi using IMS network 使用 IMS 网络通过 VoLTE 和 VoWiFi 进行紧急呼叫的比较
M. Damasceno, J. A. Arnez, Walmir Acioli E Silva, Caio B. Bezerra De Souza, Renata K. Gomes Dos Reis, Lucas Beltrão Cavalcante Tribuzy
The emergency call (eCall) service is an important part of the mobile communication networks since helps mobile users to be able to communicate during alert circumstances. eCall services were already widely used by 3G networks and can be utilized by 4G Long-Term Evolution (LTE) networks as well as by Wireless Local Network (WLAN) networks, both of them using IP Multimedia Subsystem (IMS) core. The present paper provides a guideline about how eCall services are used in Voice over Long-Term Evolution (VoLTE) and Voice over Wi-Fi (VoWiFi) technologies over IMS. Furthermore, the work assesses the Quality of Service (QoS) of calls over VoLTE and VoWiFi. Additionally, using a packet analyzer software, there were analyzed in detail the Session Initiation Protocol (SIP) message headers, the way each technology collects the information of the user location and the signaling process for eCall over VoLTE and VoWiFi.
紧急呼叫(eCall)服务是移动通信网络的重要组成部分,可帮助移动用户在紧急情况下进行通信。eCall 服务已在 3G 网络中广泛使用,并可在 4G 长期演进(LTE)网络和无线局域网(WLAN)网络中使用,这两种网络都使用 IP 多媒体子系统(IMS)核心。本文就如何将 eCall 服务用于 IMS 上的长期演进语音(VoLTE)和 Wi-Fi 语音(VoWiFi)技术提供了指导。此外,本文还评估了 VoLTE 和 VoWiFi 通话的服务质量(QoS)。此外,还使用数据包分析软件详细分析了会话启动协议(SIP)信息头、每种技术收集用户位置信息的方式以及 VoLTE 和 VoWiFi eCall 的信令过程。
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引用次数: 0
Early Malware Characterization based on Online Social Networks 基于在线社交网络的早期恶意软件特征描述
Alireza Sadighian, Ines Abbes, Gabriele Oligeri
Online social networks (OSNs) spread information worldwide and in a fast and effective way. Given the terrific number of sources, OSNs can be used for event forecasting and its characterization. Although the vast majority of information is noise, OSNs can be a source of data for the early detection and characterization of malware spreading-this representing a significant advantage for the defense team, which can be informed much in advance of when the malware affects the system. In this paper, we propose an early malware characterization technique that combines statistical analysis with Natural Language Processing (NLP). Using this approach, we analyze various malware behaviors over time and discover their characteristics, such as target system types, target applications, vulnerabilities, locations, propagation scale, etc., in order to appropriately prevent/detect/mitigate their malicious activities and implement suitable actions effectively. We tested and evaluated our approach on a dataset collected from Twitter that includes widespread ransomware indicators. The results show that our approach is effective in early characterizing various types of malware, thus can be considered as one of the first line of defense.
在线社交网络(OSN)以快速有效的方式在全球范围内传播信息。鉴于信息来源的巨大数量,OSN 可用于事件预测及其特征描述。虽然绝大多数信息都是噪音,但 OSN 可以成为早期检测和鉴定恶意软件传播的数据源,这对防御团队来说是一个重大优势,因为他们可以在恶意软件影响系统之前提前获得信息。在本文中,我们提出了一种结合统计分析和自然语言处理(NLP)的早期恶意软件特征描述技术。利用这种方法,我们可以分析恶意软件在一段时间内的各种行为,发现它们的特征,如目标系统类型、目标应用程序、漏洞、位置、传播规模等,从而适当地预防/检测/缓解它们的恶意活动,并有效地实施适当的行动。我们在从 Twitter 收集的数据集上测试并评估了我们的方法,该数据集包含了广泛的勒索软件指标。结果表明,我们的方法能有效地对各种类型的恶意软件进行早期特征描述,因此可被视为第一道防线之一。
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引用次数: 0
DoS Attack Detection with NIDS in Docker Environment 在 Docker 环境中使用 NIDS 检测 DoS 攻击
Nadia El Ghabri, E. Belmekki, Mostafa Bellafkih
In recent years, Docker containers have become very popular due to their interesting properties that lie in isolation, portability, and scalability. Like any technology, Docker containers can be vulnerable to attacks. For this reason, attack simulation is a good practice for testing the security of a system, including Docker containers. In this paper, we show how this attack simulation can be executed using the hping3 tool to launch the attack and official Docker images to run containers. The results show that the Snort container can quickly identify and report the simulated attack.
近年来,Docker 容器因其在隔离性、可移植性和可扩展性方面的有趣特性而变得非常流行。与任何技术一样,Docker 容器也可能受到攻击。因此,攻击模拟是测试系统(包括 Docker 容器)安全性的一种好方法。在本文中,我们展示了如何使用 hping3 工具发起攻击和官方 Docker 镜像运行容器来执行攻击模拟。结果表明,Snort 容器可以快速识别并报告模拟攻击。
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引用次数: 0
A Hardware Validation Framework for a Networked Dynamic Multi-factor Security Protocol 网络动态多因素安全协议的硬件验证框架
Cheng-Yen Lee, Kyler R. Scott, Sunil P. Khatri, Ali Ghrayeb
As the use of low-power Internet of Things (IoT) devices becomes widespread, the volume of data generated and transmitted is increasing rapidly. However, transmitting sensitive data over unreliable wireless networks gives rise to an increased attack surface due to the lack of secure communication. Accordingly, a lightweight and secure communication protocol is required for transmitting data between IoT devices. In this paper, we present results of experiments to conduct the hardware validation of a novel secure communication protocol which was introduced in [1]. This previously developed protocol utilizes multiple factors for authentication, which are updated after every protocol iteration. Ensuring that the same factors are not reused for authentication reduces the risk of potential attacks. Our implementation of this protocol utilizes a True Random Number Generator (TRNG) for factor updates to ensure that the factors are not based on a deterministic algorithm. In addition, our experiments validate the unicast and multicast communication features of the protocol. Our hardware platform is based on a network of Raspberry Pi boards and is designed to be both fast and computationally lightweight. We present results of experiments we conducted to assess the ability of our implementation to withstand network errors and delays. We also present an approach to choose the timeout value for a hardware implementation of the protocol. Our results demonstrate that our unicast and multicast implementations are scalable, while exhibiting good power, energy, and delay characteristics, thereby making our approach suitable for secure communication for smart IoT applications.
随着低功耗物联网(IoT)设备的广泛使用,生成和传输的数据量也在迅速增加。然而,由于缺乏安全通信,在不可靠的无线网络上传输敏感数据会增加攻击面。因此,物联网设备之间需要一种轻量级的安全通信协议来传输数据。本文介绍了对 [1] 中介绍的新型安全通信协议进行硬件验证的实验结果。这个先前开发的协议利用多个因素进行身份验证,这些因素在每次协议迭代后都会更新。确保同一因素不被重复用于验证,可降低潜在的攻击风险。我们对该协议的实现采用了真随机数生成器(TRNG)进行因子更新,以确保因子不是基于确定性算法。此外,我们的实验还验证了该协议的单播和组播通信功能。我们的硬件平台基于树莓派(Raspberry Pi)电路板网络,旨在实现快速和计算轻量级。我们展示了实验结果,以评估我们的实施方案抵御网络错误和延迟的能力。我们还介绍了一种为协议的硬件实施选择超时值的方法。我们的结果表明,我们的单播和组播实现具有可扩展性,同时表现出良好的功耗、能耗和延迟特性,从而使我们的方法适用于智能物联网应用的安全通信。
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引用次数: 0
A Low-Profile Dual-Band Eight-Port MIMO PIFA Antenna for 5G/WLAN Sub-6 GHz Mobile Terminal 用于 5G/WLAN Sub-6 GHz 移动终端的扁平双频八端口 MIMO PIFA 天线
Rachida Boufouss, A. Najid
In this article, an 8-port, 8-element dual-band multiple input and multiple output (MIMO) Planar Inverted F-Antenna (PIFA) having a height of 2.5 mm is proposed for the 5G/WLAN sub-6 GHz mobile terminal. For achieving dual-band operation with wide bandwidth, a parasitic element and L-slot are added to the PIFA, whereas a rectangular open-ended ring is printed on the top substrate next to the parasitic element. The results show that the proposed MIMO antenna system operates at 3.43–3.8 GHz and 5.15–5.85 GHz with −6dB impedance bandwidth condition. The minimum isolation achieved between two adjacent antenna elements is better than 12.1 dB in the lower band, while in the upper band is 16 dB without using any extra decoupling techniques. Moreover, radiation efficiency, radiation pattern, envelop correlation coefficient and diversity gain are all presented in this article, showing good MIMO performances of the proposed antenna which makes it promising for 5G sub-6 GHz mobile terminal.
本文为 5G/WLAN sub-6 GHz 移动终端提出了一种高度为 2.5 毫米的 8 端口、8 元件双频多输入多输出(MIMO)平面反向 F 天线(PIFA)。为实现宽带双频工作,在 PIFA 上添加了寄生元件和 L 型槽,并在寄生元件旁边的顶部基板上印刷了一个矩形开口环。结果表明,拟议的多输入多输出天线系统可在 3.43-3.8 GHz 和 5.15-5.85 GHz 频率下工作,阻抗带宽条件为 -6dB。在不使用任何额外去耦技术的情况下,两个相邻天线元件之间的最小隔离度在低频段优于 12.1 dB,而在高频段为 16 dB。此外,本文还介绍了辐射效率、辐射模式、包络相关系数和分集增益,显示了所提天线良好的多输入多输出性能,使其有望应用于 5G sub-6 GHz 移动终端。
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引用次数: 0
Enhancement in Quality of Routing Service in Vehicular ad-hoc Networks Based on the MPR Selection Algorithm of the OLSR Protocol 基于 OLSR 协议的 MPR 选择算法提高车载 ad-hoc 网络的路由服务质量
Oussama Sbayti, Said Ouhmi, Brahim Es-Sousy, Khalid Housni
In the transport domain, vehicles share a variety of information among themselves, including speed, road conditions, and accident data. Using the Vehicular Ad hoc Networks (VANETs), these vehicles effectively exchange this information. However, the issue lies in the quality of data transmission and reception. In another way, Enhancing Routing Services (ERS) improves the rate of data transmission and reception in VANETs. Our goal is to enhance routing services in VANETs based on the proactive Optimized Link State Routing (OLSR) protocol. This protocol relies on the concept of MultiPoint Relays (MPR) for neighbor selection and an intelligent algorithm for determining the shortest path between source and destination vehicles. Our idea consists of enhancing the MPR selection algorithm by increasing the maximum number of hops to three. We conducted simulations using the Simulation of Urban Mobility (SUMO) and the Network Simulator (NS3). The simulation results demonstrate favorable outcomes for the modified OLSR in various scenarios. We evaluated a set of metrics such as End-To-End Delay (E2ED), Packet Loss Rate (PLR), Overhead, and ERS.
在运输领域,车辆之间共享各种信息,包括速度、路况和事故数据。利用车载 Ad hoc 网络(VANET),这些车辆可以有效地交换这些信息。然而,问题在于数据传输和接收的质量。从另一个角度看,增强路由服务(ERS)可以提高 VANET 的数据收发率。我们的目标是在主动优化链路状态路由(OLSR)协议的基础上增强 VANET 中的路由服务。该协议依靠多点中继(MPR)的概念来选择邻居,并采用智能算法来确定源车和目的车之间的最短路径。我们的想法是通过将最大跳数增加到三跳来增强 MPR 选择算法。我们使用城市交通仿真(SUMO)和网络仿真器(NS3)进行了仿真。仿真结果表明,改进后的 OLSR 在各种场景下都取得了良好的结果。我们评估了一系列指标,如端到端延迟(E2ED)、丢包率(PLR)、开销和 ERS。
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引用次数: 0
Backstepping Control of a Double-Stage Photovoltaic System Connected to the Tree-Phase Grid Under Partial Shading Conditions 部分遮光条件下与树相电网连接的双级光伏系统的反步进控制
Khadija Sabri, O. E. Maguiri, A. Farchi
This paper solves the problem of controlling maximum power in photovoltaic systems connected to the grid in order to track changes and meet energy demand. Our work focuses on two crucial objectives: i. extracting the maximum available power (MPPT) in case of partial shading, ii. unifying the power factor (FPU). To accomplish this, we integrated a non-linear backstepping controller to extract the Maximum Power Point (MPP) using the Particle Swarming Algorithm (PSO), influencing the duty cycle of the DC/DC converter. Additionally, we applied this approach to the three-phase voltage-source inverter for achieving a unified power factor (FPU). We validated the efficacy of the introduced system through modeling and simulation in MATLAB/Simulink. The controlled system’s asymptotic stability is demonstrated mathematically, and simulation results show that the controller has successfully accomplished all of its goals with excellent dynamic performance even in the partial shading conditions. The suggested controller also exhibits excellent robustness against system disturbances, which is its primary advantage over alternative control systems.
本文解决的问题是控制与电网相连的光伏系统的最大功率,以跟踪变化并满足能源需求。我们的工作侧重于两个关键目标:i. 在部分遮光的情况下提取最大可用功率 (MPPT);ii. 统一功率因数 (FPU)。为此,我们集成了一个非线性反步进控制器,利用粒子群算法 (PSO) 提取最大功率点 (MPP),影响 DC/DC 转换器的占空比。此外,我们还将这种方法应用于三相电压源逆变器,以实现统一功率因数(FPU)。我们通过 MATLAB/Simulink 建模和仿真验证了所引入系统的功效。仿真结果表明,即使在部分遮阳条件下,控制器也能成功实现其所有目标,并具有出色的动态性能。所建议的控制器还对系统干扰表现出卓越的鲁棒性,这是它与其他控制系统相比的主要优势。
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引用次数: 0
A scalable SDN in-band control protocol for IoT networks in 6G environments 用于 6G 环境中物联网网络的可扩展 SDN 带内控制协议
David Carrascal, Elisa Rojas, D. Lopez-Pajares, Nicolas Manso, Emma Gutierrez
The proliferation of intelligent Machine-to-Machine (M2M) environments provided by the Internet of Things (IoT) has led to an increase in concurrent communications, thereby generating new demands in terms of capacity, performance, latency, and network efficiency that must be addressed. While it is true that the fifth generation of mobile technologies (5G) is already in place, addressing some of the mentioned needs, the upcoming the sixth generation of mobile technologies (6G) communication network is positioned as a technology to address future requirements, with a particular emphasis in the field of IoT. 6G harnesses the Software-Defined Networking (SDN) technology as a pivotal component of its architecture due to the flexibility and programmability it offers to enhance performance and optimize the network’s backbone. However, the SDN paradigm has drawbacks in IoT environments, such as the connectivity scheme between each network node and the SDN controller. This paper introduces the implementation of a scalable SDN in-band control protocol, which leverages the data network for control information transmission, particularly suitable for IoT networks. This implementation has been designed and implemented for both wired and wireless networks, utilizing the Basic OpenFlow User-space Software Switch (BOFUSS).
由物联网(IoT)提供的智能机器对机器(M2M)环境的激增导致了并发通信的增加,从而在容量、性能、延迟和网络效率方面产生了必须解决的新需求。诚然,第五代移动技术(5G)已经到位,满足了上述部分需求,但即将推出的第六代移动技术(6G)通信网络被定位为满足未来需求的技术,尤其侧重于物联网领域。6G 利用软件定义网络(SDN)技术作为其架构的关键组成部分,因为该技术具有灵活性和可编程性,可提高性能并优化网络主干。然而,SDN 范式在物联网环境中存在一些缺陷,例如每个网络节点与 SDN 控制器之间的连接方案。本文介绍了一种可扩展的 SDN 带内控制协议的实现,该协议利用数据网络进行控制信息传输,尤其适用于物联网网络。利用基本 OpenFlow 用户空间软件交换机(BOFUSS)设计并实现了有线和无线网络。
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引用次数: 0
Fractal analysis to BEMD’s IMFs: Application CT-Scan 对 BEMD 的 IMF 进行分形分析:应用 CT 扫描
F. Ghazil, A. Benkuider, F. Ayoub, M. Zraidi, K. Ibrahimi
Osteoporosis is a serious disease due to the fractures it causes which can lead to pain, impotence, loss of independence and excess mortality (femoral neck fractures). In addition, it is a disease with a high recurrence rate and is age-specific. Therefore, the impact of osteoporosis on the already sensitive healthcare system will increase, and thus several preventive measures can be taken to reduce its impact Based on texture analysis, which is crucial for image interpretation in the biomedical domain. We propose a fresh approach for classifying medical images in this context using bidimensional empirical multimodal decomposition (BEMD), this approach is based on the fractal analysis of BIMFs. BEMD is an extension of the one-dimensional case because it has proven to be an adaptive way to represent non-stationary and non-linear signals. Its application to image processing breaks down a image into the total of a number of hierarchical elements “bidimensional intrinsic mode functions (BIMFs)” and residues and the decomposition procedure is iterative. In order to objectively assess the effectiveness of the various BIMF modes and to characterize two states: osteoporotic and healthy, the fractal dimension was calculated for each BIMF using the DBC “Differential Box Counting” method. This novel strategy was applied on a database of CT-Scan medical images of bone textures which contains images of normal and pathological cases. Experimental results indicate that the third mode BIMF achieves higher separation rates compared to the other mode between normal and osteoporotic cases. We use classification rate evaluation criteria, such that the classification rate is given by KNN
骨质疏松症是一种严重的疾病,因为骨折会导致疼痛、阳痿、丧失独立能力和过高的死亡率(股骨颈骨折)。此外,骨质疏松症的复发率很高,而且具有年龄特异性。因此,骨质疏松症对本已敏感的医疗保健系统的影响将会增加,因此可以采取几种预防措施来减少其影响 基于纹理分析,这对生物医学领域的图像解读至关重要。在此背景下,我们提出了一种使用二维经验多模态分解(BEMD)对医学图像进行分类的全新方法,这种方法基于 BIMF 的分形分析。BEMD 是一维情况的扩展,因为它已被证明是表示非稳态和非线性信号的一种自适应方法。它在图像处理中的应用是将图像分解为若干层次元素 "二维本征模态函数(BIMF)"和残差的总和,分解过程是迭代的。为了客观地评估各种 BIMF 模式的有效性,并描述骨质疏松和健康这两种状态,使用 DBC "差分盒计数 "方法计算了每个 BIMF 的分形维度。这种新颖的策略被应用于包含正常和病理病例图像的骨纹理 CT 扫描医学图像数据库。实验结果表明,与其他模式相比,第三种模式 BIMF 在正常病例和骨质疏松病例之间实现了更高的分离率。我们使用分类率评价标准,分类率由 KNN 给出
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引用次数: 0
Improving IoT Botnet Detection Using Ensemble Learning 利用集合学习改进物联网僵尸网络检测
Youssra Baja, Khalid Chougdali, A. Kobbane
With the increasing use of Internet of Things (IoT) devices in various domains, including offices, homes, hospitals, cities, and transportation, cyberattacks using malicious attacks have become more frequent and complex, posing new challenges and risks. Therefore, it is crucial to enhance the speed and accuracy of security measures. In this paper, we propose an ensemble machine-learning model that utilizes various techniques, such as Stacking and Bagging, in combination with individual classifiers based on machine learning models to detect botnet attacks using the N-BaIoT dataset. Our results demonstrate the efficiency and efficacy of the proposed stacking model, which outperformed other techniques for every evaluation metric. We conclude that the selected model can achieve a very good accuracy rate.
随着物联网(IoT)设备在办公室、家庭、医院、城市和交通等各个领域的应用日益广泛,利用恶意攻击进行的网络攻击变得更加频繁和复杂,带来了新的挑战和风险。因此,提高安全措施的速度和准确性至关重要。在本文中,我们提出了一种集合机器学习模型,该模型利用堆叠(Stacking)和装袋(Bagging)等多种技术,结合基于机器学习模型的单个分类器,利用 N-BaIoT 数据集检测僵尸网络攻击。我们的结果证明了所提出的堆叠模型的效率和功效,该模型在每个评估指标上都优于其他技术。我们的结论是,所选模型可以达到非常高的准确率。
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引用次数: 0
期刊
2023 6th International Conference on Advanced Communication Technologies and Networking (CommNet)
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