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3rd International conference on Computational Electronics for Wireless Communications, ICCWC 2023

3rd International Conference on Computational Electronics fo...

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3rd International conference on Computational Electronics for Wireless Communications, ICCWC 2023

ISBN: (纸本)9789819719426

The proceedings contain 35 papers. The special focus in this conference is on Computational Electronics for Wireless Communications. The topics include: Design of a Four-Port MIMO Antenna for C-, X-, and Ku-Band Applications;Exploration of Diverse Techniques for Design and Optimization of QCA-Based Multiplexer Circuits;melanoma Detection Via Deep Convolutional Neural network;Pattern Diversity mm-Wave Rectangular Ring Shaped MIMO Antenna for 5G Communication and internet of Things Applications;Flexible Two/Eight-Port MIMO Antenna Configuration for LTE B41/WLAN/Wi-Fi 6E and C-Band Applications;Improvement in Machining Ability of Tungsten Carbide Tool Insert Through Microwave Hybrid Heating During Turning of EN 24 Steel;optimizing Airfare Pricing: A Data-Driven Approach for Affordable Travel Planning;advancements in Emotion Recognition: Systematic Review and Research Roadmap;epoc-Based Electroencephalography Signals Analysis of Different Stress Levels;Two-Element Tilted Rectangular MIMO UWB Antenna for Underwater Communications;deep Learning-Based Maize Crop Disease Detection and Remedial Recommendation System;design of Splash Plate Dielectric Hat Feed for Ka-Band Tracking Radar Applications;soft Computing Paradigms for Load Balancing in Cloud Computing;strategies for Effective network Congestion control: Insights from Parameter-Based Analysis;BICC: Optimizing Sensor network performance Via an Efficient Bioinspired Iterative Approach with Congestion control;Leakage Power Reduction and Stability Analysis of 5 nm Node GAA CNTFET SRAMs;bandwidth Enhancement and Improvement of Directivity of a Composite Conical Structure in the Presence of a Circular Loop Antenna;development of Compact Dual Polarized Corrugated Feed Horn Antenna with Low Cross-Polarization for Doppler Weather Radar Applications in C-Band;A Review on Recent Breakthroughs and Accomplishments in the Development of FeFET.

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3rd International conference on Computational Electronics for Wireless Communications, ICCWC 2023

3rd International Conference on Computational Electronics fo...

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3rd International conference on Computational Electronics for Wireless Communications, ICCWC 2023

ISBN: (纸本)9789819719457

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A Multi-Layered Representation for Intrusion Detection System in Cyber systems Using CNN Deep Learning Algorithm

A Multi-Layered Representation for Intrusion Detection Syste...

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2023 International conference on Data Science and network Security, ICDSNS 2023

作者： Mehra, Ritika Sohal, Asha Shrotriya, Shikha Gupta, Varun Kumar Kalra, Nuvita Dhabliya, Ritika School of Engineering and Computer Dev Bhoomi Uttarakhand University Uttarakhand India School of Engineering and Technology K. R. Mangalam University Department of Cse Gurugram India Invertis University Department of Law Bareilly India School of Computer Science and Applications Iimt University Meerut India Pune India Yashika Journal Publications Private Limited India

ISBN: (纸本)9798350301595

Convolutional Neural networks (CNNs), a kind of deep learning architecture, have recently shown remarkable progress in the field of computer vision. This study models network traffic as a time-series, in particular transmission control protocol/internet protocols (TCP/IP) packets in a predetermined time range, and applies supervised learning techniques to improve performance for the job of detection of intrusions (ID) in cyber security. Each experiment uses a learning rate between [0.01] and [0.05] to run the models for up to 1000 epochs. When compared to traditional machine learning classifiers, CNN and its different architectures perform very well. This is primarily because CNNs can abstractly represent low-level characteristic sets of traffic on network links in the form of high-level features. © 2023 IEEE.

关键词： network architecture

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Optimizing the Age of Information in Mixed-Critical Wireless Communication networks

Optimizing the Age of Information in Mixed-Critical Wireless...

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IEEE International conference on Communications (IEEE ICC)

作者： Reifert, Robert-Jeron Roth, Stefan Sezgin, Aydin Ruhr Univ Bochum Inst Digital Commun Syst Bochum Germany

ISBN: (纸本)9781538674628

Beyond fifth generation wireless communication networks (B5G) are applied in many use-cases, such as industrial control systems, smart public transport, and power grids. Those applications require innovative techniques for timely transmission and increased wireless network capacities. Hence, this paper proposes optimizing the data freshness measured by the age of information (AoI) in dense internet of things (IoT) sensor-actuator networks. Given different priorities of data-streams, i.e., different sensitivities to outdated information, mixed-criticality is introduced by analyzing different functions of the age, i.e., we consider linear and exponential aging functions. An intricate non-convex optimization problem managing the physical transmission time and packet outage probability is derived. Such problem is tackled using stochastic reformulations, successive convex approximations, and fractional programming, resulting in an efficient iterative algorithm for AoI optimization. Simulation results validate the proposed scheme's performance in terms of AoI, mixed-criticality, and scalability. The proposed non-orthogonal transmission is shown to outperform an orthogonal access scheme in various deployment cases. Results emphasize the potential gains for dense B5G empowered IoT networks in minimizing the AoI.

关键词： internet of things

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Reviewing SDN Adoption Strategies for Next Generation internet of Things networks 3rd

Reviewing SDN Adoption Strategies for Next Generation Intern...

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3rd International conference on Smart systems - Innovations in Computing (SSIC)

作者： Lopez, Cesar Lacalle, Ignacio Belsa, Andreu Kopertowski, Zbigniew Palau, Carlos E. Esteve, Manuel Univ Politecn Valencia Camino Vera S-N Valencia 46022 Spain Orange Poland Al Aleje Jerozolimskie 160 PL-02326 Warsaw Poland

ISBN: (纸本)9789811628771;9789811628764

internet of Things networks grow in heterogeneity and complexity, the associated industry needs to improve the performance of traditional network deployments. One of the main relevant evolutions on network architectures is depicted by the remote control of the forwarding state of the equipment. The advance here consists in having the data plane managed by a remotely controlled plane decoupled from the former, enabling to program the behavior of a network without being tied to inflexible rules and conditions. To support this network evolution, software-defined networking (SDN) allows programmability as the main role in improving resource efficiency and increasing service reliability and security. The analysis conducted in this paper aims at reviewing the different adoption strategies to effectively deploy SDN-enabled Next Generation IoT systems, analyzing in detail the variations found between the types of access network layers, and the SDN applications that can be carried out. The analysis ranges from basic deployments (where the concerns are specific to the direct connection end devices-network) to complex, multi-application advanced ones (where alternative configuration and layouts come into play). The paper concludes with the presentation of the approach taken in the project ASSIST-IoT, that will apply the previous knowledge toward the definition of a blueprint architecture for the Next Generation internet of Things.

关键词： Adoption strategies Cellular networks IoT Mesh Next generation networks RAN SD-WAN SDN

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Analysing the Effectiveness of Intrusion Detection systems against the Mirai Botnet: A Comparative Study 15

Analysing the Effectiveness of Intrusion Detection Systems a...

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15th International conference on Advances in Computing, control, and Telecommunication Technologies, ACT 2024

作者： Binu, P.K. Kumar, Barun Sethia, Rishav Department of Computer Science and Application Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (纸本)9798331300579

The rise of the internet of Things (IoT) has led to an increased risk of cyber attacks on IoT devices, including botnet attacks. Botnets are networks of compromised devices that can be controlled remotely by cybercriminals to carry out malicious activities, such as distributed denial of service (DDoS) attacks. The Mirai botnet is one of the most notorious botnets that have caused significant damage to IoT devices worldwide. To protect IoT devices from such attacks, intrusion detection systems (IDSs) are used to detect and mitigate attacks. However, the effectiveness of IDSs against botnet attacks is still a subject of debate, as botnets are becoming more sophisticated and difficult to detect. To address this issue, this research paper aims to analyse and compare the effectiveness of three widely used IDSs, namely Snort, Zeek, and Suricata, against the Mirai botnet. The study involves simulating Mirai botnet attacks in a controlled environment and evaluating the performance of each IDS in terms of detection and mitigation capabilities. The findings of this research can help organisations to select and implement effective IDSs to mitigate the impact of botnet attacks on IoT devices. By understanding the strengths and weaknesses of different IDSs, organisations can improve the security of their IoT devices and reduce the risk of cyber attacks. Overall, this research paper contributes to the existing literature on IDSs and their effectiveness against botnet attacks, highlighting the importance of selecting and implementing effective IDSs to protect IoT devices from cyber threats. © Grenze Scientific Society, 2024.

关键词： IDS Malware Mirai network Security Snort Suricata Zeek

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AA-DL: AoI-Aware Deep Learning Approach for D2D-Assisted Industrial IoT

AA-DL: AoI-Aware Deep Learning Approach for D2D-Assisted Ind...

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2023 IEEE Global conference on Artificial Intelligence and internet of Things, GCAIoT 2023

作者： Farag, Hossam Ragab, Mohamed Stefanovic, Cedomir Aalborg University Department of Electronic Systems Denmark Aswan University Department of Electrical Engineering Egypt Centre for Frontier AI Research Singapore

ISBN: (纸本)9798350382020

In real-time Industrial internet of Things (iioT), e.g., monitoring and control scenarios, the freshness of data is crucial to maintain the system functionality and stability. In this paper, we propose an AoI-Aware Deep Learning (AA-DL) approach to minimize the Peak Age of Information (PAoI) in D2D-assisted iioT networks. Particularly, we analyzed the success probability and the average PAoI via stochastic geometry, and formulate an optimization problem with the objective to find the optimal scheduling policy that minimizes PAoI. In order to solve the non-convex scheduling problem, we develop a Neural network (NN) structure that exploits the Geographic Location Information (GLI) along with feedback stages to perform unsupervised learning over randomly deployed networks. Our motivation is based on the observation that in various transmission contexts, the wireless channel intensity is mainly influenced by distance-dependant path loss, which could be calculated using the GLI of each link. The performance of the AA-DL method is evaluated via numerical results that demonstrate the effectiveness of our proposed method to improve the PAoI performance compared to a recent benchmark while maintains lower complexity against the conventional iterative optimization method. © 2023 IEEE.

关键词： internet of things

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MPC-Based Coordinated Voltage control in LV Distribution systems: A Case Study in Chalmers Campus network

MPC-Based Coordinated Voltage Control in LV Distribution Sys...

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2023 IEEE Asia Meeting on Environment and Electrical Engineering, EEE-AM 2023

作者： Tran, Minh-Quan Tran, Trung Thai Huu Nguyen, An Thien Nguyen, Phuong H. Steen, David Tuan, Le Anh Mai, Tam T. Eindhoven University of Technology Department of Electrical Engineering Eindhoven Netherlands Chalmers University of Technology Department of Electrical Engineering Gothenburg Sweden Dnv Netherlands B.V. Arnhem Netherlands

ISBN: (纸本)9798350381061

This paper presents detailed analysis results of a model predictive control (MPC)-based coordinated voltage control demonstrated in a real low voltage network, the Chalmers campus in Sweden. First, the modeling of the MPC is presented, and the state space mode is obtained by linearization of the power flow equation around the operation point. Thus, an updated voltage vector in the grid is calculated through the sensitivity gain corresponding to reactive power deviation in the grid. Second, the developed MPC model is integrated into an internet of Things (IoT) platform developed under the European FlexiGrid project. The state measurements in the Chalmers campus network are collected through the IoT platform as the input for the MPC model. Then, the optimal setpoints for distributed energy resources (DERs) are calculated and sent to DERs via the IoT platform. Lastly, onsite demonstration results are analyzed, showing the performance of the MPC-based voltage control in low-voltage distribution systems. © 2023 IEEE.

关键词： Sensitivity analysis

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A Hybrid Deep Learning Spectrum Sensing Architecture for IoT Technologies Classification 17

A Hybrid Deep Learning Spectrum Sensing Architecture for IoT...

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17th International conference on Engineering of Modern Electric systems, EMES 2023

作者： Mutescu, Partemie M. Lavric, Alexandru Petrariu, Adrian I. Popa, Valentin Stefan Cel Mare University of Suceava Computers Electronics and Automation Department Suceava Romania

ISBN: (纸本)9798350310634

In recent years, there has been a significant expansion of the internet of Things concept, because of its versatile and extensive range of applications across various industries such as transportation, logistics, smart metering, or agriculture. The rapid expansion of internet of Things networks has resulted in a limitation of radio frequency spectral resources, giving in turn a substantial rise in packet collision rate, interference level, bit error rate parameters and reducing the communication channel capacity altogether. Employing spectrum sensing techniques can aid in overcoming these challenges by providing key information on the radio spectrum occupancy and the modulation schemes used. This data can be leveraged to develop collision avoidance schemes, which can enhance the performance level of wireless networks increasing the network capacity. This paper proposes and evaluates a hybrid deep learning spectrum sensing technique for simultaneous detection and classification of LoRa and Sigfox internet of Things communication technologies in the 868 MHz frequency band. The developed hybrid deep learning spectrum sensing architecture is capable of effectively detect and classify multiple IoT technologies represented by LoRa communications using different spreading factors and Sigfox within the 868 MHz frequency band, achieving an average precision of 85.51 % and an average intersection over union metric of 0.77. © 2023 IEEE.

关键词： internet of things

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Designing Low-Power Industrial networks with the internet of Things 5th

Designing Low-Power Industrial Networks with the Internet of...

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5th International conference on Data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Kannagi, A. Ansari, Tabish Nasurudeen Ahamed, N. Alam, Intekhab Karnataka Bangalore India Department of Civil Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

The internet of Things (IoT) revolution is evolving conventional commercial networks to fulfill the demands of present-day technological advancements. Low-electricity business networks are becoming increasingly vital to allow a green communique between linked systems and remote monitoring and management of gadgets. Designing and deploying low-electricity networks for business programs brings many demanding situations, which include energy control, conversation latency, and cease-to-give-up safety. This summary will offer a top-level view of the layout issues while implementing IoT and occasional-power business networks, in addition to the capability of high-quality practices for ensuring low-strength, comfortable, and reliable communications among connected devices. Furthermore, IoT techniques for localizing network accessibility, improving facts accuracy, and boosting community performance may be discussed. Subsequently, some of the trendy trends and trends in the industrial networking area could be highlighted. Low-power business networks are getting increasingly important to allow the green conversation of connected structures and remote tracking of devices. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Capability Management Strength

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