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检索条件"任意字段=5th International Conference on Distributed Computing and Internet Technologies"

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An AI-Driven Based Cybersecurity System for Network Intrusion Detection System in Hybrid with EPO and CNNet-LAM 5

An AI-Driven Based Cybersecurity System for Network Intrusio...

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5th IEEE international conference on computing, Power, and Communication technologies, IC2PCT 2024

作者： Anu Disney, D. Yugha, R. Karachi, S.Bangaru Gangadevi, E. Balusamy, Balamurugan Gite, Shilpa Sathyabama Institute of Science and Technology School of Computing Chennai600119 India Sathyabama Institute of Science and Technology Department of Computer Science Chennai600119 India Loyola College Department of Computer Science Chennai600034 India Delhi India Symbiosis Institute of Technology Aiml Department Pune India Pune412115 India

ISBN: (纸本)9798350383522

the proliferation of large data made possible by ubiquitous internet use has led to an uptick in cyberattacks, despite the proliferation of AI-based security keys like intrusion detection systems (IDS). Improved data classification is one benefit of the suggested detection system's foundation in deep learning (DL) and Convolutional Neural Networks (CNNs). With the use of the IDSAI dataset, this research takes a close look at intrusion detection systems. Z-Score Normalisation and Min-Max Normalisation are used for data preparation. Picking out the most relevant characteristics from the preprocessed data is the next step after data preprocessing. As a result, the feature selection method makes use of an optimisation known as the Eagle Perching Optimisation (EPO) Algorithm. Convolutional Neural Networks with Long Short-Term Memory and Attention Mechanism (CNNet-LAM) are used for classification after selection. It is common practice to employ EPO during hyperparameter tweaking due to its efficacy. Classification issues may be effectively resolved by using the CNNet-LAM hybrid model. the suggested model consistently surpasses the competition, according to the testing data, and it can predict varying time delays with an accuracy of 99.31%. © 2024 IEEE.

关键词： Attention mechanism Convolutional layer Eagle perching optimization Intrusion detection system Long short-term memory

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Scalable Transparent Access to 5G Edge Services 7

Scalable Transparent Access to 5G Edge Services

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7th IEEE international conference on Fog and Edge computing (ICFEC) / 23rd IEEE/ACM international Symposium on Cluster, Cloud and internet computing (CCGRID)

作者： Hammer, Josef Hellwagner, Hermann Alpen Adria Univ Klagenfurt Inst Informat Technol Klagenfurt Austria

ISBN: (纸本)9798350322880

the challenging demands for the next generation of the internet of things have led to a massive increase in edge computing and network virtualization technologies. One significant technology is Multi-access Edge computing (MEC), a central piece of 5G telecommunication systems. MEC provides a cloud computing platform at the edge of the radio access network and is particularly essential to satisfy the challenging low-latency demands of future applications. Our previous publications argue that edge computing should be transparent to clients. We introduced an efficient solution to implement such a transparent approach, leveraging Software-Defined Networking (SDN) and virtual IP+port addresses for registered edge services. Building on our already efficient approach, in this work, we propose significant improvements to scale our transparent solution to large-scale real-world access networks. First, by improving the modularity of our SDN controller design, we enable various options to distribute both the SDN controller's load and the switches' flows. Second, we introduce the Unique Mask, a solution superior to the Unique Prefix presented in our previous work that considerably reduces the number of required flows in the switches. Our evaluations show that both algorithms perform very well, with the Unique Mask capable of reducing the number of flows by up to 98 %.

关键词： Multi-Access Edge computing MEC Fog computing Software-Defined Networking SDN Patricia Trie

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On the Challenge of Generating Multivariate Time Series Data from distributed Sensors in IoT-enabled Scenarios 24

On the Challenge of Generating Multivariate Time Series Data...

引用

14th international conference on the internet of things, IoT 2024

作者： Bañuelos, Julián Jerónimo Costa-Requena, Jose He, Jiayuan Salim, Flora D. Sigg, Stephan Department of Information and Communications Engineering School of Electrical Engineering Aalto University Espoo Uusimaa Finland School of Computing Technologies RMIT University MelbourneVIC Australia Cumucore Oy Espoo Uusima Finland School of Computer Science and Engineering University of New South Wales Sydney Australia

ISBN: (纸本)9798400712852

Smart sensing environments supported by an internet of things (IoT) infrastructure are enabling a wide array of possibilities for data-intensive remote monitoring applications. Although nowadays it is possible to access and deploy complex setups of sophisticated sensors, the telecommunications infrastructures are struggling to deal with the massive amounts of generated data for transmission, processing, and storage from the diverse range of IoT devices. As data corruption and the loss of data are realistic scenarios in current IoT deployments, it is relevant to find an alternative solution that circumvents the limitations of the physical infrastructure for dealing with potential missing data in remote sensing environments. In this paper, we analyze the feasibility of reproducing missing sensor data due to a communication failure from correlated sources in the same experimental context. We rely on generative adversarial models for the prediction of acceleration data and evaluate the usefulness of the synthetic data with a standard human activity recognition (HAR) classifier. © 2024 Copyright held by the owner/author(s).

关键词： Time series

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AI-Enabled Fast Detection of DDoS and Adversary DDoS Attacks in SDN 14

AI-Enabled Fast Detection of DDoS and Adversary DDoS Attacks...

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14th international conference on computing Communication and Networking technologies, ICCCNT 2023

作者： Prathap, Pratheeksha Duttagupta, Subhasri Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Amritapuri India

ISBN: (纸本)9798350335095

the importance of network services especially telemedicine services has increased dramatically after the global spread of the Covid-19 virus. Telemedicine services may include live audio and video chats, uploading of images or files etc. in real-time. the efficiency of a network service relies on the dependability and resilience of its foundational infrastructure. the rapid increase of telemedicine services has also resulted in a steady rise in security attack methods, the breadth of their effects, and the ferocity with which they are launched. distributed denial-of-service (DDoS) attacks have become a major source of worry for internet service providers. Software Defined Network (SDN), in which the control plane is shifted to a logically centralized location, is widely used for providing large-scale internet services due to advantages such as programmability, flexibility, etc. But a logically centralized control plane in SDN makes it more vulnerable to DDoS attacks due to a larger attack surface. In this paper, we focus on DDoS attack detection approaches and their adversarial behavior in SDN using the latest Deep Learning techniques. Our technique is able to achieve a detection accuracy of 98.49% for the primary DDoS dataset and 93.19% for the adversary dataset generated by us. © 2023 IEEE.

关键词： Denial-of-service attack

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Containerized Data-Flow Processing for Scalable Real-Time Analytics on Edge Devices 25th

Containerized Data-Flow Processing for Scalable Real-Time A...

引用

25th international conference on Parallel and distributed computing, Applications and technologies, PDCAT 2024

作者： HoseinyFarahabady, MohammadReza Y. Zomaya, Albert School of Computer Science Center for Distributed and High Performance Computing The University of Sydney SydneyNSW2006 Australia

ISBN: (纸本)9789819642069

the increasing demand for real-time data analysis in internet of things (IoT) ecosystems has created several challenges, particularly in environments where resources are limited, and minimizing data processing latency is critical. this paper investigates the use of Linux Containerization (LXC) as a lightweight, resource-efficient alternative to traditional virtual machine managers for accelerating data-flow processing applications. We propose an architecture that integrates Linux Containerization (LXC) with a Proportional-Integral-Derivative (PID) controller to dynamically manage I/O resource allocation, ensuring Quality of Service (QoS) for I/O-intensive data analytics workloads. the proposed PID controller continuously monitors system performance and dynamically adjusts I/O resource allocation to mitigate performance degradation. through a series of experiments, we demonstrate that LXC-based solutions outperform traditional methods in managing I/O-intensive data analytics workloads in IoT and edge ecosystems. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Quality of service

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An Analysis of Edge computing with Multi Access in 5-G Technology 3

An Analysis of Edge Computing with Multi Access in 5-G Techn...

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3rd international conference on Advance computing and Innovative technologies in Engineering, ICACITE 2023

作者： Gupta, Sitaram Sonia Vivekananda Global University Department of Computer Science Engineering Jaipur India Chandigarh School of Business Department of Master of Computer Application Jhanjeri India

ISBN: (纸本)9798350399264

the demands of the rapidly expanding internet. However, since most end users have confined storage space and limiting computing power, it lately evolved into a natural issue how to execute computationally complex apps on resource-bound consumers. the emerging fifth generation (5G) corporation can benefit from Mobile Edge computing (MEC) innovation upgrade portable assets by facilitating figure concentrated applications, handling a lot of information prior to sending them to the cloud, finding distributed computing assets inside the radio access organization (RAN) close to versatile clients, and giving setting mindful administrations utilizing RAN information. In reality, the paradigm shift from 4G to 5G is accompanied by the introduction of new technical concepts. We first give a comprehensive introduction of MEC technology and some of its possible applications. the most recent research on MEC integration with upcoming technologies that will be employed in 5G and beyond is then is summarized. © 2023 IEEE.

关键词： Mobile edge computing

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Boosting-based DDOS Detection in internet of things System 14

Boosting-based DDOS Detection in Internet of Things System

引用

14th international conference on Advances in computing, Control, and Telecommunication technologies, ACT 2023

作者： Suresh, Rathod Kawarsing Pagare, J.D. Computer Science & Engineering Jawaharlal Nehru Engineering College MH Aurangabad India

the internet of things (IoT) is an innovative communication framework due to its wide variety of applications. Existing systems, such as home networks made up of various IoT devices, still struggle to resist distributed Denial-of-Service (DDoS) attacks. the IoT network is one smart environment that this research helps to make more secure. IoT offers a vast network to connect objects globally in an effort to lessen human effort & make a digitalized environment easier to operate. DDoS attacks, which recently have targeted many IoT networks & resulted in large losses, are one of the main risks that can completely disable a targeted system's availability. Two machine learning techniques, namely the LGBM & extreme gradient boosting, were used to identify the attacks that are currently taking place in the dataset (XG Boost). these techniques were chosen due to their superior capacity to forecast in large data volumes in a shorter amount of time than other techniques. the accuracies attained by LGBM & XG Boost in 30 & 229 seconds(s), correspondingly, was 94.88% & 94.89%. © Grenze Scientific Society, 2023.

关键词： Denial-of-service attack

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Smart Services Implementation in Smart Cities: A Comprehensive Review of State-of-the-art technologies 23

Smart Services Implementation in Smart Cities: A Comprehensi...

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5th international conference on Management Science and Industrial Engineering, MSIE 2023

作者： Arin, Ikrar Adinata Supangkat, Suhono Harso Gaol, Ford Lumban Ranti, Benny Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Indonesia Smart City and Community Innovation Center Institut Teknologi Bandung Indonesia Computer Science Department Faculty of Computer Science University of Indonesia Indonesia

ISBN: (纸本)9798400708381

this paper discusses comprehensively the advanced technologies used in the implementation of smart services, which are key elements of a smart city. Smart cities are becoming eco-friendly, livable, and sustainable to deliver essential services to their citizens by leveraging internet and communication technology advancements. Starting from a short literature review about smart cities and smart services, a recent trend in the technology used to implement smart services is collected. Smart service can be defined as a service conveyed using intelligent products that possess awareness and connectivity. All kinds of smart services can be connected in smart cities to offer citizens comprehensive solutions. Pre-emptive services, self-services, or highly interactive services, for example, have the potential to be implemented using current technology such as the internet of things, artificial intelligence, cloud computing, big data, machine learning, machine-to-machine communications, and the digital twin. therefore, there is scope for research and implementation of other technology for smart services in the future. © 2023 ACM.

关键词： Smart city

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Identification of distributed Denial of Service Attacks Employing L-BFGS Tuning 14

Identification of Distributed Denial of Service Attacks Empl...

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14th international conference on computing Communication and Networking technologies, ICCCNT 2023

作者： Singh, Vikas Dehalwar, Vasudev Bharti, Jyoti Manit Bhopal Department of Cse Bhopal India

ISBN: (纸本)9798350335095

internet speed and capacity are crucial components of any communication technology in the modern era. Customers should expect excellent speed and a lot of bandwidth. A DDoS (distributed denial of service) assault, which is a well-known attack, is the biggest threat in communication. DDoS attacks limit the user's speed and bandwidth. In order to produce this work, we used the updated dataset, CICDDoS2019, and undertook tests using a variety of machine learning methods. We investigated which features had the strongest relationships with the analysis's projected classes. this research proposal offers a machine learning-based L-BFGS (Limited-memory Broyden-Fletcher-Goldfarb-Shanno) algorithm-based DDoS assault detection method. An HPC Python platform was used to carry out the simulation and experiment for the suggested research project. the accuracy, true and false negatives, along with true and false positives, confusion matrix structures, and other outcome measures are all evaluated in this study. the proposed method shows better results as compared to other previous methods. Index Terms - DDoS attack, MLP Classifier, LBFGS, Machine Learning. © 2023 IEEE.

关键词： Denial-of-service attack

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Role of Edge computing in IoT 14

Role of Edge Computing in IoT

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14th IEEE international conference on Communication Systems and Network technologies, CSNT 2025

作者： Singh, Pragya Gautam, Preeti Arya, Namita Centre of Internet of Things MITS Gwalior Madhya Pradesh India

ISBN: (纸本)9798331531935

computing stands at a crossroads between speed and scale. the cloud promises vast computing power and storage, yet shuffling data to and from those distant servers takes time - often too much. Edge computing looks to resolve that dilemma by shifting processing closer to the devices generating all that data. Rather than relying solely on gargantuan centralized cloud servers, edge computing utilizes nearby devices and micro data centers to enable real-time, location-aware services and this distributed approach brings quicker responses and leaner loads by leveraging local gadgets to handle localized computing chores. However fully activating edge computing's potential requires surmounting a few obstacles first. Efficiently coordinating myriad devices for data storage and number-crunching poses logistical challenges. Integrating these decentralized nodes into the centralized cloud framework demands care and forethought. And securing expansive networks of hardware and software is no simple feat. Still, the promised gains in speed and adaptability compel this revolution in computing. © 2025 IEEE.

关键词： Mobile edge computing

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