International Conference on Computing, Networking and Communications (ICNC)
Date
February 2025
Network Anomaly Detection Using a Graph Neural Network
Patrice Kisanga;Isaac Woungang;Issa Traore;Glaucio H. S. Carvalho
2023 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2023,Page(s):61 - 65
Cited by: Papers (9)
Contrary to the many traditional network security approaches that focus on volume-based threats, the Activity and Event Network (AEN) is a new approach built on a graph model, which addresses both volumetric attacks and long-term threats that traditional security tools cannot deal with. The AEN graph structural foundation can serve as a basis to construct a graph to be used in Graph Neural Network...Show More
WiSegRT: Dataset for Site-Specific Indoor Radio Propagation Modeling with 3D Segmentation and Differentiable Ray-Tracing: (Invited Paper)
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):744 - 748
The accurate modeling of indoor radio propagation is crucial for localization, monitoring, and device coordination, yet remains a formidable challenge, due to the complex nature of indoor environments where radio can propagate along hundreds of paths. These paths are resulted from the room layout, furniture, appliances and even small objects like a glass cup. They are also influenced by the object...Show More
Satellite Communication at Millimeter Waves: a Key Enabler of the 6G Era
2020 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2020,Page(s):383 - 388
Cited by: Papers (103)
While technical standard development for 5G radio services is still an ongoing process, the scientific community is drafting the key drivers, requirements, challenges and research questions towards 6th generation (6G) networks. 6G developments will foster, among other innovations, the evolution of wireless systems towards a 3D, continuous and ubiquitous service coverage by complementing terrestria...Show More
Prompt Fix: Vulnerability Automatic Repair Technology Based on Prompt Engineering
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):116 - 120
With the emergence of large-scale language models (LLM), the powerful capabilities of LLM in natural language processing have attracted attention. Based on programming language LLM (Programming Language Model, PLM), we use prompt templates to explore its potential in the field of automatic vulnerability repair, and combine it with a special workflow to improve its efficiency in automatic vulnerabi...Show More
UAV-assisted disaster management: Applications and open issues
2016 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2016,Page(s):1 - 5
The fast-paced development of Unmanned Aerial Vehicles (UAVs) and their use in different domains, opens a new paradigm on their use in natural disaster management. In UAV-assisted disaster management applications, UAVs not only survey the affected area but also assist in establishing the communication network between the disaster survivors, rescue teams and nearest available cellular infrastructur...Show More
Approximating the Void: Learning Stochastic Channel Models from Observation with Variational Generative Adversarial Networks
2019 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2019,Page(s):681 - 686
Cited by: Papers (77)
Channel modeling is a critical topic when considering accurately designing or evaluating the performance of a communications system. Most prior work in designing or learning new modulation schemes has focused on using simplified analytic channel models such as additive white Gaussian noise (AWGN), Rayleigh fading channels or other similar compact parametric models. In this paper, we extend recent ...Show More
Enhancing UAV Security Through Zero Trust Architecture: An Advanced Deep Learning and Explainable AI Analysis
Ekramul Haque;Kamrul Hasan;Imtiaz Ahmed;Md. Sahabul Alam;Tariqul Islam
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):463 - 467
Cited by: Papers (4)
In the dynamic and ever-changing domain of Unmanned Aerial Vehicles (UAVs), the utmost importance lies in guaranteeing resilient and lucid security measures. This study highlights the necessity of implementing a Zero Trust Architecture (ZTA) to enhance the security of unmanned aerial vehicles (UAVs), hence departing from conventional perimeter defences that may expose vulnerabilities. The Zero Tru...Show More
AnDet: ML-Based Anomaly Detection of UEs in a Multi-cell B5G Mobile Network for Improved QoS
Amar Sinha;Anmol Agrawal;Sandip Roy;Venkanna Uduthalapally;Debanjan Das;Rajarshi Mahapatra;Sachin Shetty
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):500 - 505
Cited by: Papers (1)
The rise of 5G technology has revolutionized wireless communication, ushering in a new era of unparalleled connectivity. Approaching Beyond 5G networks, Software Defined Networks have emerged as a promising paradigm to enhance flexibility and scalability in cellular networks. However, the challenge of 5G is to ensure the network's performance based on the different Quality of Service requirements ...Show More
Reinforcement Learning with Large Language Models (LLMs) Interaction for Network Services
Hongyang Du;Ruichen Zhang;Dusit Niyato;Jiawen Kang;Zehui Xiong;Dong In Kim
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):799 - 803
Artificial Intelligence-Generated Content (AIGC)-related network services, especially image generation-based services, have garnered notable attention due to their ability to cater to diverse user preferences, which significantly impacts the subjective Quality of Experience (QoE). Specifically, different users can perceive the same semantically informed image quite differently, leading to varying ...Show More
Comparison of FHE Schemes and Libraries for Efficient Cryptographic Processing
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):584 - 590
In recent years, opportunities to collect and analyze big data in the cloud have increased. Cryptographic processing is imperative for protecting data on cloud servers, and homomorphic encryption, which can perform calculations in an encrypted state, is highly expected for this purpose. Fully Homomorphic Encryption (FHE) is an encryption scheme that allows for addition and multiplication operation...Show More
Impacts of Positive and Negative Comments of Social Media Users to Cryptocurrency
2020 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2020,Page(s):187 - 192
Cited by: Papers (10)
Blockchain implementation brought several benefits to many areas. One of the usages of blockchain is in digital currencies. Digital currency (cryptocurrency) is a new era for the global financial system. Cryptocurrencies draw significant attention from researchers because of their advantages. Although there are several risks (e.g., speculation, 51% attack) related to cryptocurrency, billions of do...Show More
Evaluating the Performance and Energy Efficiency of OpenGL and Vulkan on a Graphics Rendering Server
2019 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2019,Page(s):777 - 781
Cited by: Papers (3)
Open Graphics Library (OpenGL) has been the de facto industry standard of 2D and 3D graphics rendering for decades. As OpenGL continued to evolve, it becomes easier to use and more powerful by accommodating heterogeneous hardware and hiding optimization details from developers. As a side effect, its overhead gradually increases and its performance becomes unpredictable. To address the weaknesses o...Show More
Short term power load forecasting using Deep Neural Networks
2017 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2017,Page(s):594 - 598
Cited by: Papers (98)
Accurate load forecasting greatly influences the planning processes undertaken in operation centres of energy providers that relate to the actual electricity generation, distribution, system maintenance as well as electricity pricing. This paper exploits the applicability of and compares the performance of the Feed-forward Deep Neural Network (FF-DNN) and Recurrent Deep Neural Network (R-DNN) mode...Show More
A Zero-Trust Framework for Industrial Internet of Things
2023 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2023,Page(s):331 - 335
Cited by: Papers (2)
Interactions between different types of systems from various environments are increasing continuously due to the nature of business and commercial requirements. All of these interactions require a level of trust given for each system in order to enable essential operations and functions. Traditional trust models and frameworks implemented in different environments define static levels of trust giv...Show More
Digital Forensic Analysis of Instant Messaging Applications on Android Smartphones
2018 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2018,Page(s):647 - 651
Cited by: Papers (12)
In this paper, we discuss the digital forensic procedure and techniques for analyzing the local artifacts from four popular Instant Messaging applications in Android. As part of our findings, the user chat messages details and contacts were investigated for each application. By using two smartphones with different brands and the latest Android operating systems as experimental objects, we conducte...Show More
Trustful Blockchain-Enabled Identity Management for VANET with Short-Latency Authentication
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):659 - 663
Blockchain technology has emerged as a popular research topic, particularly in the area of identity management, which provides with a decentralized ID system due to its inherent distributed architecture. This paper focuses on the security issues for vehicular ad-hoc networks (VANETs), where there exists significant obstacles to deploy blockchain-based identity manage-ment system. The idea of light...Show More
A Case Study of Security and Privacy Threats from Augmented Reality (AR)
2018 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2018,Page(s):442 - 446
Cited by: Papers (12)
In this paper, we present a case study of potential security and privacy threats from virtual reality (VR) and augmented reality (AR) devices, which have been gaining popularity. We introduce a computer vision-based attack using an AR system based on the Samsung Gear VR and ZED stereo camera against authentication approaches on touch-enabled devices. A ZED stereo camera is attached to a Gear VR he...Show More
Security-Enhanced WireGuard Protocol Design Using Quantum Key Distribution
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):718 - 723
WireGuard is a pioneering and lightweight Virtual Private Network (VPN) protocol that has been merged into the Linux kernel. It leverages the Noise secure framework to provide advanced security functionalities, such as identity hiding and perfect forward security. Although WireGuard has an optional pre-shared key mode to ensure key security, the advanced security features are guaranteed by asymmet...Show More
Decoding of Polar Code by Using Deep Feed-Forward Neural Networks
2018 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2018,Page(s):238 - 242
Cited by: Papers (30)
With the success of image classification problems, deep learning is expanding its application areas. In this paper, we apply deep learning to decode a polar code. As an initial step for memoryless additive Gaussian noise channel, we consider a deep feed-forward neural network and investigate its decoding performances with respect to numerous configurations: the number of hidden layers, the number ...Show More
Application identification via network traffic classification
Baris Yamansavascilar;M. Amac Guvensan;A. Gokhan Yavuz;M. E. Karsligil
2017 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2017,Page(s):843 - 848
Cited by: Papers (86)
Recent developments in Internet technology have led to an increased importance of network traffic classification. In this study, we used machine-learning methods for the identification of applications using network traffic classification. Contrary to existing studies, which classify applications into categories like FTP, Instant Messaging, etc., we tried to identify popular end-user applications s...Show More
Federated Learning-Based Solution for DDoS Detection in SDN
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):875 - 880
Cited by: Papers (1)
One major threat to Software Defined Network (SDN) environments and other computing systems is Distributed Denial of Service (DDoS) attacks. For the longest time, conventional Machine Learning (ML) techniques have been used for DDoS detection, but they have limitations because of their centralised training requirements, which can lead to excessive bandwidth utilization, increased latency, and serv...Show More
Advanced Cyber Deception Framework (ACDF): A Comprehensive Study
Mark Maldonado;Caleb Johnson;Manbir Gulati;Todd Jaspers;Paul F. Roysdon
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):203 - 208
Cited by: Papers (1)
Deception frameworks provide an effective environment for data collection on cyber criminals. Using deception techniques these frameworks help security professionals identify and deceive attackers. Information security is an increasingly complex problem as cyber attacks evolve and attackers become more competent in exploitation. Honeypots or honey networks provide an opportunity for counter-intell...Show More
Performance Evaluation of DSRC and C-V2X Coexistence in the 5.895-5.925 GHz Spectrum
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):862 - 867
Cited by: Papers (1)
Two competing radio access technologies (RATs) are presently available for intelligent transportation systems: Dedicated short-range communication (DSRC) and cellular vehicle-to-everything (C-V2X). Recent FCC rulings allocate 30 MHz worth of spectrum (5.895-5.925 GHz) for both RATs, recommending 20 MHz (2 channels) for C-V2X and 10 MHz (one channel) for DSRC. However, significant debate has ensued...Show More
Early detection of DDoS attacks against SDN controllers
2015 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2015,Page(s):77 - 81
A Software Defined Network (SDN) is a new network architecture that provides central control over the network. Although central control is the major advantage of SDN, it is also a single point of failure if it is made unreachable by a Distributed Denial of Service (DDoS) Attack. To mitigate this threat, this paper proposes to use the central control of SDN for attack detection and introduces a sol...Show More
Deep Learning based Framework for Automatic Damage Detection in Aircraft Engine Borescope Inspection
2019 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2019,Page(s):1005 - 1010
Cited by: Papers (17)
To ensure high safety in civil aviation, borescope inspection has been widely applied in early damage detection of aircraft engines. Current manual damage inspection on borescope images inevitably results in low efficiency for engine status inspection. Traditional recognition methods are inefficient for damage detection due to complicated and noisy scenarios inside them. In this paper, a deep lear...Show More
Weighted Multi-Task Vision Transformer for Distraction and Emotion Detection in Driving Safety
Yixiao Wang;Zhe Li;Guowei Guan;Yipin Sun;Chunyu Wang;Hamid Reza Tohidypour;Panos Nasiopoulos;Victor C.M. Leung
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):152 - 156
Cited by: Papers (1)
Detecting drivers' distraction and emotion has raised attention due to its importance in ensuring driving safety, especially with the increasing number of accidents caused by distracted or emotionally unstable drivers. Previous research has employed the multitasking method to detect these two factors simultaneously but paid insufficient attention to the emotion detection part. Meanwhile, existing ...Show More
Hybrid Quantum Machine learning using Quantum Integrated Cloud Architecture (QICA)
2023 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2023,Page(s):419 - 425
Cited by: Papers (3)
Gate-based and Annealing Quantum Computing backend systems purposely built and deployed based on Quantum Integrated Cloud Architecture (QICA) design patterns, provide enhanced quantum computational capabilities that consist of a suite of hybrid quantum-classical cloud-based software and specialized hybrid quantum-classical machine learning algorithms, tools, solvers, and simulators using physics-i...Show More
Optimal Dynamic Resource Allocation for Multi-RIS Assisted Wireless Network: A Causal Reinforcement Learning Approach
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):881 - 885
This study explores optimal dynamic resource allocation in mobile reconfigurable intelligent surface (RIS)-aided wireless networks facing uncertain, time-varying channels. Unmanned aerial vehicles (UAVs) strategically deploy multiple RIS to enhance mobility. Addressing uncertainties, a novel causal reinforcement learning-based online dynamic resource allocation algorithm is proposed. It features a...Show More
Parameter tuning for accurate heart rate measurement using Wi-Fi signals
Brenda G. Gouveia;Iandra Galdino;Egberto Caballero;Julio C. H. Soto;Taiane C. Ramos;Raphael Guerra;Débora Muchaluat-Saade;Célio V. N. Albuquerque
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):407 - 411
Heart rate monitoring is crucial for detecting possible changes in human health. Therefore, in recent years, the development of applications and devices that monitor vital signs has evolved significantly. This work proposes a non-contact approach to heart rate monitoring through the processing of channel state information from a commodity Wi-Fi network. Various settings for signal processing param...Show More
AIGC for RF Sensing: The Case of RFID-Based Human Activity Recognition
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):1092 - 1097
Cited by: Papers (1)
The performance of deep learning (DL) empowered wireless communications, networking, and sensing depends on the availability of sufficient high-quality radio frequency (RF) data, which is more difficult and expensive to collect than other types. To overcome this obstacle, we propose to harness the power of diffusion models on latent domains to generate hyper-realistic RF data for RF sensing. We de...Show More
Demystifying Cyberattacks: Potential for Securing Energy Systems With Explainable AI
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):430 - 434
Modernization of energy systems has led to in-creased interactions among multiple critical infrastructures and diverse stakeholders making the challenge of operational decision making more complex and at times beyond cognitive capabilities of human operators. The state-of-the-art machine learning and deep learning approaches show promise of supporting users with complex decision-making challenges,...Show More
Lightweight Internet protocols for web enablement of sensors using constrained gateway devices
2013 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2013,Page(s):334 - 340
Lightweight Internet protocols are increasingly being used in ubiquitous environment in order to optimize the resource usage of a constrained device like a smart mobile gateway. This paper presents a study on the various such protocols to optimize the usage of energy, and network resources, computation cost of a constrained gateway device. Comprehensive analysis and feature wise categorization of ...Show More
A Generative Adversarial Network Based Tone Mapping Operator for 4K HDR Images
Junbin Zhang;Yixiao Wang;Hamidreza Tohidypour;Mahsa T. Pourazad;Panos Nasiopoulos
2023 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2023,Page(s):473 - 477
Cited by: Papers (4)
High dynamic range (HDR) has arguably been established as the preferred image and video format for content providers. As standard dynamic range (SDR) displays still dominate the market, there is a need for finding efficient ways to convert HDR content to the SDR format, a process known as tone mapping. Recently, many tone mapping operators (TMOs) have been proposed that are based on deep learning ...Show More
Towards Instant Clustering Approach for Federated Learning Client Selection
Sarhad Arisdakessian;Omar Abdel Wahab;Azzam Mourad;Hadi Otrok
2023 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2023,Page(s):409 - 413
Cited by: Papers (4)
In just few years, Federated Learning (FL) started to gain unprecedented attention given its ability to solve some fundamental privacy and communication challenges of traditional machine learning. Client selection is one of the main challenges in FL and is usually done in a random fashion, where the central server arbitrarily selects a certain number of clients to participate in each training roun...Show More
Fast Frequency-Direction Mapping Design for Data Communication With True-Time-Delay Array Architecture
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):1071 - 1076
In recent times, beamforming architectures utilizing True-Time-Delay arrays have gained significant interest in the field of wide-band data communication due to their abilities to generate frequency-dependent responses with great flexibility. This paper proposes a new heuristic fast algorithm with the goal of beamforming signals to different directions in different sub-bands. The proposed algorith...Show More
A Routing Method with Link Information-based Rule Selection in Non-Terrestrial Networks
Tomohiro Korikawa;Chikako Takasaki;Kyota Hattori;Hidenari Oowada
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):850 - 855
Non-terrestrial networks (NTN) are a promising approach in beyond 5G/6G era to provide ubiquitous connectivity to everywhere, including uncovered or underserved areas. NTN enables covering wide areas from the sky by employing satellites and unmanned aerial vehicles (UAVs) as movable network nodes such as base stations and routers. In contrast, the node mobility of NTN introduces dynamic changes in...Show More
Revisiting Multi-Factor Authentication Token Cybersecurity: A TLS Identity Module Use Case
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):33 - 38
Cited by: Papers (2)
Multi-factor authentication (MFA) procedures are widely used by digital systems. There are usually performed by hardware tokens comprising a microcontroller and an USB interface. The security level is increased by computing cryptographic procedures in secure elements such as smartcards. Authenticity of MFA token is a critical topic since hardware or software components may be cloned or modified, f...Show More
Variable Code Size Autoencoder (VCSA) Meets CSI Compression in Model Generalization
Yifei Song;Juan Roa;Renjian Zhao;Zhigang Rong;Weimin Xiao;Jalal Jalali;Baoling Sheen
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):209 - 214
To fully exploit the advantages of spatial multiplexing gains in Multiple-Input Multiple-Output (MIMO) systems operating in Frequency Division Duplex (FDD) mode, it is crucial to develop a robust Channel State Information (CSI) feedback compression and reconstruction strategy. This strategy should effectively reduce the communication overhead while maintaining close-to-optimal reconstruction accur...Show More
An Attention-based AI Model for 3D Beam Prediction in THz Unmanned Aerial Vehicle Communication
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):761 - 766
Cited by: Papers (2)
In this study, we considered the Terahertz (THz) Unmanned Aerial Vehicle (UAV) communication scenario, where we are dealing with the problem of beam prediction. UAVs have emerged as a critical component in evolving sixth-generation (6G) wireless networks, bringing seamless communication and extensive coverage. The usage of the THz spectrum allows for high-speed data throughput for the envisioned 6...Show More
Multi-Objective Cognitive Routing in Space DTNs
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):376 - 381
In space networking and other challenging environments, optimizing bundle routing is crucial. Traditional routing objectives focus on finding the shortest path or achieving the earliest delivery time. However, with the growth of these networks in size and diversity of applications, there is a need to expand the scope of routing objectives. In this paper, we explore a decentralized bundle routing m...Show More
An approach for detection and family classification of malware based on behavioral analysis
Steven Strandlund Hansen;Thor Mark Tampus Larsen;Matija Stevanovic;Jens Myrup Pedersen
2016 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2016,Page(s):1 - 5
Malware, i.e., malicious software, represents one of the main cyber security threats today. Over the last decade malware has been evolving in terms of the complexity of malicious software and the diversity of attack vectors. As a result modern malware is characterized by sophisticated obfuscation techniques, which hinder the classical static analysis approach. Furthermore, the increased amount of ...Show More
Machine Learning for Caching Placement in Edge Computing Networks
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):259 - 264
Internet of Things devices (IoTDs) that deployed for various applications have limited size, power, storage, and computing capabilities, and many of them are used for low-latency applications. Mobile edge computing (MEC) can be leveraged to reduce the latency of IoTDs, and judicious caching placement can help further to improve the quality of service. In this paper, we study multi-content placemen...Show More
AI-based Cyber Event OSINT via Twitter Data
2023 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2023,Page(s):436 - 442
Cited by: Papers (6)
Open-Source Intelligence (OSINT) is largely regarded as a necessary component for cybersecurity intelligence gathering to secure network systems. With the advancement of artificial intelligence (AI) and increasing usage of social media, like Twitter, we have a unique opportunity to obtain and aggregate information from social media. In this study, we propose an AI-based scheme capable of automatic...Show More
Shallow- and Deep- fake Image Manipulation Localization Using Deep Learning
Junbin Zhang;Hamidreza Tohidypour;Yixiao Wang;Panos Nasiopoulos
2023 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2023,Page(s):468 - 472
Cited by: Papers (3)
Forged image localization is an important research task, as such images may have a tremendous impact of various aspects of society. Images can be manipulated using image editing tools (known as “shallowfakes”) or, recently, artificial intelligence techniques (“deepfakes”). While there are many existing works that are designed for manipulated areas localization on either shallow- or deep-fake image...Show More
Using Artificial Intelligence and IoT Solution for Forest Fire Prevention
Giovanni Pettorru;Mauro Fadda;Roberto Girau;Mariella Sole;Matteo Anedda;Daniele Giusto
2023 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2023,Page(s):414 - 418
Cited by: Papers (5)
Natural ecosystem conservation is a topical issue that is receiving increasing attention from different branches of the scientific community. Forests and woodlands are major contributors to climate change mitigation, able to absorb significant amounts of carbon dioxide. The conservation of tree areas has been addressed through the adoption of different solutions. This paper proposes a new monitori...Show More
DL-SIC: Deep Learning Aided Successive Interference Cancellation in Shared Spectrum
Zhiwu Guo;Wenhan Zhang;Ming Li;Marwan Krunz;Mohammad Hossein Manshaei
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):754 - 760
With the increasing demand for wireless capacity, multiple wireless technologies will inevitably coexist over shared bands. Successive interference cancellation (SIC) is a promising technique for improving spectrum utilization by utilizing the difference in the powers of concurrently received signals. However, enabling SIC over a shared band faces several challenges, related to the heterogeneity o...Show More
Implementation of Real-Time Adversarial Attacks on DNN-based Modulation Classifier
Eyad Shtaiwi;Ahmed Refaey Hussein;Awais Khawar;Ahmed Alkhateeb;Ahmed Abdelhadi;Zhu Han
2023 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2023,Page(s):288 - 292
Cited by: Papers (1)
In this paper, we provide a hardware implementation for over-the-air (OTA) adversarial attack on a deep neural network (DNN)-based modulation classifiers. Although Automatic modulation classification (AMC) using the DNN-based method outperforms the traditional classification, it has been proven that the machine learning (ML) approaches lack robustness against adversarial attacks. Therefore, the ad...Show More
Stereo-Aided Blockage Prediction for mmWave V2X Communications
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):624 - 628
Cited by: Papers (1)
Vision-aided blockage prediction has been recognized as a promising approach for stable Millimeter wave (mmWave) vehicle-to-everything (V2X) communications. For the supplement of channel-based prediction, the vision-aided approach can predict the communication condition in the near future, i.e., several hundred milliseconds; however, both the accuracy and prediction time of exiting work using mono...Show More
Social Media Development and Multi-Modal Input for Stock Market Prediction: A Review
2024 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2024,Page(s):198 - 202
In the realm of behavioral finance, the influence of information—particularly that disseminated by media sources—plays a pivotal role in shaping stock market prices. This study categorizes social media into three distinct evolutionary phases, each characterized by its media agency and mode of interaction: authoritative media, grassroots media, and digital interactive media. As we transition into t...Show More
Downlink Resource Allocation in Cell-Free Massive MIMO Systems
2019 International Conference on Computing, Networking and Communications (ICNC)
Publication Year: 2019,Page(s):883 - 887
Cited by: Papers (24)
Cell-free Massive Multiple-Input Multiple-Output (MIMO) is introduced as a promising network architecture for the upcoming fifth-generation (5G) wireless communication networks. It enhances user experience and improves the overall system performance by providing huge throughput and coverage probability to all users throughout a system. In this paper, a resource allocation problem is studied for do...Show More
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