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Deep Neural Network Based Smart Intrusion Detection and Alerting System 10

Deep Neural Network Based Smart Intrusion Detection and Aler...

引用

10th International Conference on comm.nication and Signal Processing, ICCSP 2024

作者： Karthikeyan, N. Mahapatro, Soumya Ranjan Akash, R. Rakesh Teja, P.V. Vellore Institute of Technology School of Computer Science and Engineering Chennai Campus Tamil Nadu India Vellore Institute of Technology School of Electronics and Comm. Engineering Chennai Campus Tamil Nadu India

ISBN: (纸本)9798350353068

With the increasing prevalence of surveillance systems, the need for an automated system that detects the presence of intruders from the surveillance camera and send an alert message to the user immediately has become very crucial. The research paper aims to provide a deep learning (DL) model-based solution to accurately detect the presence of human figures in the frame. The approach includes using YOLOv8 (You Only Look Once - Version 8) object detection model to detect human figures, paired with the implementation of the Non-Maximum Suppression technique to remove duplicate bounding boxes around humans. Additionally, Gaussian Noise Reduction technique has been used to remove Gaussian blur from the image for obtaining a clearer image of human figure present in the frame. The research paper demonstrates a procedure to quickly send alert message to the user when a human figure is detected in the camera using the Telegram application. The paper also demonstrates the implementation of frame skipping method based on periodic intervals for optimizing the computational efficiency. In addition to this, the paper also demonstrates a comparative study between the frequently used human detection algorithms namely YOLOv8, YOLOv4, SSD and HOG and provides statistical proof on how YOLOv8 outperforms the other standard models. © 2024 IEEE.

关键词： Intrusion detection

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Standardization Review on 5G LAN-Type Service 15

Standardization Review on 5G LAN-Type Service

引用

15th International Conference on Information and comm.nication Technology Convergence, ICTC 2024

作者： Kyung, Yeunwoong Lee, Donghun Lee, Jaewook Kim, Youngjun Ko, Haneul Oh, Seungmin Lee, Jaehwan Kongju National University Div. of Info. & Comm. Eng. Cheonan Korea Republic of Pukyong National University Dep. of Info. and Comm. Engineering Busan Korea Republic of School of Computer Science and Eng. Kyungnam University Changwon Korea Republic of Kyung Hee University Dep. of Electronic Eng. Yongin-si Korea Republic of Kongju National University Dep. of Computer Science and Eng. Cheonan Korea Republic of

ISBN: (纸本)9798350364637

The 5G LAN-type service refers to a service that supports comm.nication between users within a group through the 5G system. It provides functions similar to those of traditional Local Area Networks (LAN) or Virtual Private Networks (VPN), but it gains attention across various services due to the enhanced performance of 5G such as high throughput, low latency, mobility management, and security. The 3rd Generation Partnership Project (3GPP) introduced the 5G LAN-type service in Release 16 and defined the architecture, protocols, and requirements to support the 5G LAN-type service. In this paper, we briefly examine the architecture and components of the 5G network based on the 3GPP standard and introduce the structure and protocols for supporting 5G LAN-type services in a 5G network. © 2024 IEEE.

关键词： 5G mobile comm.nication systems

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PDU Set-Based Traffic Handling for XR Service Support in 5G User Plane 15

PDU Set-Based Traffic Handling for XR Service Support in 5G ...

引用

15th International Conference on Information and comm.nication Technology Convergence, ICTC 2024

作者： Kyung, Yeunwoong Lee, Donghun Lee, Jaewook Ko, Haneul Oh, Seungmin Lee, Jaehwan Kim, Youngjun Kongju National University Div. of Info. & Comm. Eng. Cheonan Korea Republic of Pukyong National University Dep. of Info. and Comm. Engineering Busan Korea Republic of Kyung Hee University Dep. of Electronic Eng. Yongin-si Korea Republic of Kongju National University Dep. of Computer Science and Eng. Cheonan Korea Republic of School of Computer Science and Eng. Kyungnam University Changwon Korea Republic of

ISBN: (纸本)9798350364637

To support XR services, the 3GPP standards intro-duce a protocol data unit (PDU) set, which is the minimum group of packets needed to carry a video frame, and also define the relative importance of different PDU sets. This allows the network operator to handle network traffic based on the importance of PDU sets. 3GPP standards define two options for PDU set-based traffic handling in the user plane: 1) gNB-based and 2) UPF-based. This paper introduces a basic concept of PDU set and specifies two procedures for PDU set-based traffic handling in the user plane. © 2024 IEEE.

关键词： 5G mobile comm.nication systems

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Objective quality assessment of generated high-resolution human face images 12

Objective quality assessment of generated high-resolution hu...

引用

12th IEEE International Conference on Identification, Information and Knowledge in the Internet of Things, IIKI 2024

作者： Gu, Jiacheng Yue, Ding Yu, Shaode Zhang, Peng Sun, Qiurui Beijing Institute of Technology School of Computer Science Beijing China Communication University of China School of Info. and Comm. Engineering Beijing China Education Management Information Center Ministry of Education of the Prc Beijing China Beijing Normal University Center of Information & Network Technology Beijing China

ISBN: (纸本)9798331510633

Human face image generation can be used in media, marketing, education, creativity, research and privacy protection. Many deep learning networks have been proposed for generating high-resolution human face images, while the quality of generated human face images are not fully investigated. To bridge this gap, 11 StyleGAN-based networks are firstly trained via the database Flickr-Faces-HQ (FFHQ). Then, each network produces 10,000 high-resolution (1024 × 1024) human face images. After that, the quality of these generated images are evaluated with 6 Face Image Quality Assessment (FIQA) metrics. The average metric values suggest that the generated human face images are with higher quality than the realistic images in the FFHQ database. However, the failure cases of generated images remind us that artifacts and distortions exist, and unreasonable combinations and meaningless contents are produced. Therefore, significant progress is still required for achieving reliable quality assessment and high-accuracy generation of human faces. © 2024 IEEE.

关键词： face image quality assessment human face image image generation StyleGAN

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RF Energy Harvesting Effectiveness in Relay-based D2D comm.nication

RF Energy Harvesting Effectiveness in Relay-based D2D Commun...

引用

2023 International Conference on computer Science, Information Technology and engineering, ICCoSITE 2023

作者： Salim, Mahmoud M. Elsayed, Hussein A. Abdalzaher, Mohamed S. Fouda, Mostafa M. October 6 University Electronics and Comm. Engineering Department Giza Egypt School of Electrical Engineering Cognitive Enhancement Meta-Communication ERC Research Center Korea University Seoul Korea Republic of Ain Shams University Electronics and Comm. Engineering Department Cairo Egypt National Research Institute of Astronomy and Geophysics Seismology Department Cairo Egypt Idaho State University Department of Electrical and Computer Engineering PocatelloID United States Idaho FallsID United States

ISBN: (纸本)9798350320954

The energy harvesting (EH) of radio frequency (RF) has taken attention to solve the wireless devices' energy problem. On the other hand, relays play a crucial role in improving device-to-device (D2D) comm.nication performance with regard to data rate and energy efficiency (EE) as well as network coverage and extendability. Relay nodes (RNs) can take advantage of EH while benefiting the D2D networks. This paper provides an answer to the controversial question of whether it is worth using RF EH in relay-based D2D comm.nication. As such, it presents the main EH protocols for relay-based D2D wireless networks, namely power splitting (PS) and time switching (TS). Besides, it models a network of relay-based D2D comm.nication links sharing the spectrum of a number of conventional comm.nication links under the quality of service (QoS) conditions. The results show that the effectiveness of EH depends on factors like the density of the nodes in the investigated area. © 2023 IEEE.

关键词： Energy harvesting

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A Novel Meta-Hierarchical Active Inference Reinforcement Learning Approach for QoS-Driven Resource Allocation in Dynamic Clouds

A Novel Meta-Hierarchical Active Inference Reinforcement Lea...

引用

2024 IEEE Global comm.nications Conference, GLOBECOM 2024

作者： Xian, Peijie He, Ying Yu, F. Richard Du, Jianbo Shenzhen Univ. College of Computer Science and Software Engineering Shenzhen China Xi'an Univ. of Posts & Telecomm. Shaanxi Key Lab. of Information Comm. Network and Security Shaanxi Xi'an China Carleton Univ. School of Information Technology OttawaON Canada

ISBN: (纸本)9798350351255

The cloud computing environment is highly dynamic due to a variety of external factors such as seasonal changes, market trends, and social events. In this case, tenant behavior patterns exhibit significant variability. Therefore, the cloud computing resource allocation model must continuously adapt to these changes. To this end, we propose an adaptive algorithm for dynamic cloud resource allocation based on meta-hierarchical active inference reinforcement learning (MHAIRL). The algorithm combines active inference with meta-hierarchical reinforcement learning. It improves the overall performance of the algorithm, as well as quickly adapts to environmental changes, and improves the generalization performance. In addition, we design a novel polling scheduling framework combined with long short-term memory (LSTM) network. The framework ensures scheduling fairness and flexibility while greatly reducing the state and action space dimensions of the agent. Extensive simulation results show that our method outperforms baseline algorithms in quality of service (QoS) metrics and significantly improves system performance in highly dynamic cloud resource allocation. © 2024 IEEE.

关键词： Active learning

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Standardization Review on Non-Terrestrial Networks 39

Standardization Review on Non-Terrestrial Networks

引用

39th International Conference on Information Networking, ICOIN 2025

作者： Kyung, Yeunwoong Lee, Jaewook Ko, Haneul Oh, Seungmin Lee, Jaehwan Kim, Youngjun Kongju National University Div. of Info. & Comm. Eng Cheonan Korea Republic of Pukyong National University Dep. of Info. and Comm. Engineering Busan Korea Republic of Kyung Hee University Dep. of Electronic Eng Yongin-si Korea Republic of Kongju National University Dep. of Computer Science and Eng Cheonan Korea Republic of Kyungnam University School of Computer Science and Eng Changwon Korea Republic of

ISBN: (纸本)9798331506940

As the demand for global connectivity increases, non-terrestrial networks (NTNs), particularly satellite-based systems, have gained significant attention in comm.nication network standardization. The 3rd Generation Partnership Project (3GPP) has been at the forefront of developing standards that incorporate satellite comm.nications into the broader terrestrial network framework. This paper reviews the progression of NTN standardization, focusing on three key stages: (1) the use of satellites as relays or the next generation NodeBs (gNBs), (2) the integration of user plane functions (UPF) within satellites, and (3) the inclusion of control plane network functions (NFs) within satellites. These developments in standardizations reflect a shift from basic relay functions to fully integrated satellite networks. © 2025 IEEE.

关键词： Network function virtualization

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Safeguarding Authenticity in Text with BERT-Powered Detection of AI-Generated Content 7

Safeguarding Authenticity in Text with BERT-Powered Detectio...

引用

7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Chakraborty, Utsho Gheewala, Jaydeep Degadwala, Sheshang Vyas, Dhairya Soni, Mukesh Gujarat Technological University Computer Engineering India Sarvajanik College of Engineering And Technology Gujarat Surat India Sigma University Dept. of Comm. Engg. Gujarat India The Maharaja Sayajirao University of Baroda Gujarat Vadodara India Dr. D. Y. Patil School of Science & Technology Tathawade Pune India

ISBN: (纸本)9798350359299

This research study explores the crucial domain of upholding textual authenticity by introducing a comprehensive method for identifying AI-generated content, employing BERT (Bidirectional Encoder Representations from Transformers). In a time when Artificial Intelligence (AI) significantly shapes written comm.nication, it becomes imperative to differentiate between text produced by humans and that generated by machines. The proposed approach utilizes the capabilities of BERT by delving into contextual embedding, revealing complex patterns that serve as indicators of AI origin. Through meticulous experimentation and evaluation, we substantiate the effectiveness of our method in precisely discerning AI-generated text. This contribution adds to the ongoing endeavors to safeguard the integrity of human-authored content in the ever-evolving digital landscape. © 2024 IEEE.

关键词： Embeddings

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Deep Neural Network Based Smart Intrusion Detection and Alerting System

Deep Neural Network Based Smart Intrusion Detection and Aler...

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International Conference on comm.nications and Signal Processing

作者： N Karthikeyan Soumya Ranjan Mahapatro R Akash P V Rakesh Teja School of Computer Science and Engineering Vellore Institute of Technology Chennai Campus Tamil Nadu India School of Electronics and Comm. Engineering Vellore Institute of Technology Chennai Campus Tamil Nadu India

ISBN: (数字)9798350353068

ISBN: (纸本)9798350353075

With the increasing prevalence of surveillance systems, the need for an automated system that detects the presence of intruders from the surveillance camera and send an alert message to the user immediately has become very crucial. The research paper aims to provide a deep learning (DL) model-based solution to accurately detect the presence of human figures in the frame. The approach includes using YOLOv8 (You Only Look Once – Version 8) object detection model to detect human figures, paired with the implementation of the Non-Maximum Suppression technique to remove duplicate bounding boxes around humans. Additionally, Gaussian Noise Reduction technique has been used to remove Gaussian blur from the image for obtaining a clearer image of human figure present in the frame. The research paper demonstrates a procedure to quickly send alert message to the user when a human figure is detected in the camera using the Telegram application. The paper also demonstrates the implementation of frame skipping method based on periodic intervals for optimizing the computational efficiency. In addition to this, the paper also demonstrates a comparative study between the frequently used human detection algorithms namely YOLOv8, YOLOv4, SSD and HOG and provides statistical proof on how YOLOv8 outperforms the other standard models.

关键词： YOLO Measurement Computational modeling Surveillance Gaussian noise Intrusion detection Signal processing

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Prediction of User Behaviour of Electric Vehicles Utilizing Ensembled Machine Learning Technique

Prediction of User Behaviour of Electric Vehicles Utilizing ...

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2024 IEEE International Conference on comm.nication, Computing and Signal Processing, IICCCS 2024

作者： Garg, Raghav Deogaonkar, Anant Garia, Prakash Ahamad, Isarar Kharayat, Pushpendra Singh Joshi, Tripuresh Tula's Institute Deptt. of Computer Science & Engg. UK Dehradun India Ramdeobaba University School of Management Nagpur India Graphic Era Hill University School of Management India Integral University Department of Electrical Engineering Lucknow India Graphic Era Deemed to be University Department of Electrical Engineering Dehradun India Tula's Institute Deptt. of Electronics & Comm. Engg. U.K. Dehradun India

ISBN: (纸本)9798350390759

Although they help reduce greenhouse gas emissions, electric vehicles (EVs), a fundamental component of smart mobility in applications for smart cities, are becoming more and more popular. One of the main challenges, meanwhile, is the strain that a large-scale EV deployment puts on the electrical grid's infrastructure. Electric vehicles are the most significant part of transportation. An application for mobility in smart cities is built on electric automobiles. The lack of structures for charging electric vehicles is the biggest obstacle to their acceptance to solve the issue of EV charging time and usage. We are using Ml algorithms to anticipate charge analysis to solve the problem, which is advantageous for drivers. It gives comprehensive details about the energy use of an electric car and illustrates how long it takes for the battery to charge completely. Predictive analytics uses machine learning (ML) algorithms because they can be trained on even larger data sets and, with little deployment adjustments, can conduct deeper analysis on many factors. © 2024 IEEE.

关键词： Adversarial machine learning

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