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Disaster Tweet Classification Based on Geospatial Data Using the BERT-MLP Method 9

Disaster Tweet Classification Based on Geospatial Data Using...

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9th international conference on Information and Communication Technology, ICoICT 2021

作者： Maulana, Iqbal Maharani, Warih Telkom University School of Computing Bandung Indonesia

ISBN: (纸本)9781665404471

as a popular social media in the world and even in Indonesia, Twitter has a variety of popular topics making these topics trending, including the topic of natural disasters that have occurred in Indonesia. the DKI Jakarta flood disaster in early 2020 made a big scene on trending twitter topics. this study aims to classify these tweets into "flooded"and "not flooded"predictions with the tweets and geospatial features. the model proposed for classifying is BERT-MLP. Bidirectional Encoder from Transformers (BERT) is used in the pre-trained model to classify these tweets and Multi Layer Perceptron (MLP) is used to classify geospatial features. the scenario designed for the model focuses on the preprocessing of tweets as follows without stopword removal, without stemming, with both, and without both. Once classified, the tweet will be visualized into a two-dimensional interactive map. the best scenario results have an accuracy of 82% in scenarios without stemming and with stopword removal. this is due to the stemming process eliminates some of the features in tweets around 6%. this study also shows the relationship between the influence of negative context tweets on the "not flooded"class with an orientation of 65% of the total data. However, defining manual stopwords can affect because stopword removal will not delete words that still have context related features to the topic. © 2021 IEEE.

关键词： Social networking (online)

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FaaSter Troubleshooting - Evaluating distributed Tracing Approaches for Serverless Applications 9

FaaSter Troubleshooting - Evaluating Distributed Tracing App...

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9th IEEE international conference on Cloud Engineering (IC2E)

作者： Borges, Maria C. Werner, Sebastian Kilic, Ahmet Tech Univ Berlin Informat Syst Engn Berlin Germany Tech Univ Berlin Berlin Germany

ISBN: (纸本)9781665449700

Serverless applications can be particularly difficult to troubleshoot, as these applications are often composed of various managed and partly managed services. Faults are often unpredictable and can occur at multiple points, even in simple compositions. Each additional function or service in a serverless composition introduces a new possible fault source and a new layer to obfuscate faults. Currently, serverless platforms offer only limited support for identifying runtime faults. Developers looking to observe their serverless compositions often have to rely on scattered logs and ambiguous error messages to pinpoint root causes. In this paper, we investigate the use of distributed tracing for improving the observability of faults in serverless applications. To this end, we first introduce a model for characterizing fault observability, then provide a prototypical tracing implementation-specifically, a developer-driven and a platform-supported tracing approach. We compare both approaches with our model, measure associated trade-offs (execution latency, resource utilization), and contribute new insights for troubleshooting serverless compositions.

关键词： Serverless computing FaaS Platforms distributed Tracing Observability

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Enhance Security for the E-payment Application with Blockchain Technology

Enhance Security for the E-payment Application with Blockcha...

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international conference on Integrated Circuits, Design, and Verification (ICDV)

作者： Hung Le-Huy thuat Nguyen-Khanh Quan Le-Trung Faculty of Computer Networks and Communications University of Information Technology Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Vietnam

ISBN: (数字)9798350371864

ISBN: (纸本)9798350371871

E-payment systems, despite their practicality, face challenges such as data manipulation, limited bandwidth, and potential denial-of-service attacks. these issues can impact businesses, financial institutions, and individual users conducting transactions, as they struggle to manage large amounts of traffic simultaneously. Addressing these issues is crucial for ensuring secure and efficient transactions. this research presents a system that integrates Hyperledger Fabric with software-defined networking to enhance system throughput without significantly altering the Blockchain’s functionality. It also uses Hyperledger Aries technology for improved client identity recognition efficiency. the proposed system aims to reduce deployment time, maintain secure data, and provide a non-stop payment platform for client identification within a decentralized framework. It supports multiple concurrent users or system attacks with minimal average delay, ensuring efficient communication among components. the system is being researched to find a feasible solution that balances security and performance in real time while minimizing internal platform modifications.

关键词： Integrated circuit synthesis distributed ledger Face recognition throughput Denial-of-service attack Real-time systems Fabrics

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A Smart NIDS Design for SDN-based Cloud IoT Network using Optimal Path Selection and RNN

A Smart NIDS Design for SDN-based Cloud IoT Network using Op...

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international conference on Signal Processing and Communication (ICSC)

作者： Narendra Kumar Ishaan Dawar Anurag Aeron Santosh Kumar Department of computer science and engineering Amity University Jharkhand Ranchi INDIA School of Computing DIT University Dehradun Dehradun INDIA Computer science and Information Technology Siksha ‘O’ Anusandhan University Bhubaneshwar INDIA

the Internet of things (IoT) has greatly increased the possibility for developing intelligent connections and applications in many facets of daily life. Traditional security solutions frequently fail to solve security issues in cloud-based IoT systems, proving ineffective and insufficient. Software Defined networking (SDN), which effectively detects and monitors network security vulnerabilities thanks to its programmable characteristics, presents a viable solution to these problems. In order to strengthen computer systems and fend off threats to network security, machine learning (ML) techniques have recently been included into SDN-Network Intrusion Detection Systems (NIDS). Deep learning (DL), one of these cutting-edge ML techniques, has become more popular in the SDN environment. For SDN-based cloud IoT networks, this paper design an efficient path selection system in this study utilizing DL approaches. the strategy comprises employing a Recurrent Neural Network (RNN) to identify threats and a selection mechanism to pick the best route for data delivery. this study performed tests on two datasets, KDD and UNSWNB15, and the results show that the suggested RNN outperformed existing DL methods by achieving an amazing accuracy ranging from 91% to 95% on both datasets.

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Optimal Placement of Tie-Switches Among Networked Microgrids Considering Annual Load Demand and distributed Energy Resource Power Supply and Absorption

Optimal Placement of Tie-Switches Among Networked Microgrids...

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Big Data, Cloud computing, Data Science & Engineering (BCD)

作者： Wei-Tzer Huang Wei-Chen Lin Chai-Hsien Hsiao Kai-Chao Yao Zong-Tai Li Pei-Hsun Tsai Department of Industrial Education and Technology National Changhua University of Education Changhua City Taiwan

ISBN: (数字)9798350394191

ISBN: (纸本)9798350394207

Guided by the standards outlined in IEEE Std 1547.4, it is feasible to organize distribution networks into a configuration known as networked microgrids, which significantly enhances the resilience of distribution network operations. this study proposes an approach for determining the optimal placement of tie-switches within these networked microgrids. this tactic is crucial for determining the boundaries of microgrids to attain superior configurations, thereby the placement and quantity of tie-switches is decided to improve the efficiency and reliability of the distribution networks. the analysis conducted in this study is based on 48 scenarios that utilize extensive big data on annual load demand as well as distributed energy resource power supply and absorption. this data is instrumental in defining the boundaries of the microgrids. the results aim not only to prevent the overloading of main transformers and distribution feeders and to improve the operational performance of distribution networks but also to facilitate efficient power restoration through the autonomous, self-regulating operation of dynamic boundaries. this approach provides an alternative to traditional restoration processes in emergency situations caused by natural disasters.

关键词： Power supplies Absorption Disasters Microgrids Distribution networks Big Data Transformers Stability analysis distributed power generation Standards

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Artificial Intelligence-Driven Unmanned Aerial Vehicle Base Station Placement: Current Advances, Challenges, and Use Case

Artificial Intelligence-Driven Unmanned Aerial Vehicle Base ...

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international conference on Fog and Mobile Edge computing (FMEC)

作者： Sharief Abdel-Razeq Ayat Al-Khdouer Haythem Bany Salameh Yaser Jararweh Ghaleb Elrefae Department of Telecommunications Engineering Yarmouk University Irbid Jordan Department of Communications and Networking Al Ain University Al Ain United Arab Emirates Department of Computer Science Jordan University of Science and Technology Irbid Jordan College of Business Al Ain University Al Ain United Arab Emirates

ISBN: (数字)9798350366488

ISBN: (纸本)9798350366495

In recent years, there has been a lot of interest in using drones as aerial base stations (BSs), namely drone base stations (DBS), to help with ground connection under unique situations. Despite the apparent benefits of DBSs, they present some significant obstacles that must be solved in order to provide a robust drone-assisted wireless network service. Optimal placement of DBSs in the air and their movement to ensure optimum coverage is one of the most crucial difficulties. In this paper, we provide an overview of DBSs and their challenges, focusing on the main challenge, the placement, and how artificial intelligence (AI) can be utilized to solve such a challenge effectively. Finally, we present a use case in which we propose an AI-based approach for distributing multiple DBSs to serve zones within a network while allowing for dynamic behavior in user demand and services over time. this problem is solved using the RL approach based on the SARSA algorithm for exploration and continuously learns and adapts DBS allocation strategies in response to environmental interactions. the simulation results show an increase in operator profit compared to equal policy dispatch.

关键词： Base stations Multi-access edge computing Heuristic algorithms Simulation Wireless networks Focusing Resource management Vehicle dynamics Artificial intelligence Drones

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Enhanced Web Security Using Cross-Feature Analysis of Visual Design, Live Logs and Code Structures

Enhanced Web Security Using Cross-Feature Analysis of Visual...

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international conference on Communication and Electronics Systems (ICCES)

作者： Rahul Kumar Tanvi Sharma G. Saranya Department of Networking and Communication School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Tamil Nadu India

ISBN: (数字)9798350377972

ISBN: (纸本)9798350377989

threats using website visual designs and content structures, along with standard coding vulnerabilities, represent an increasing danger to web security. To enhance web security, this paper introduces a new method called cross-feature analysis that integrates the investigation of visual design, live logs, code structures and other vulnerabilities. Based on this threefold correlation, this method identifies discrepancies that might have otherwise gone undetected by traditional approaches reliant on discrete elements. this research rightly provides a thorough methodology for evaluating XSS detection, SQL injection error and time-based testing, CSRF vulnerability checking, clickjacking protection, information disclosure detection, and risk assessment are all included in this. It includes several test vectors for each vulnerability, port scanning with service discovery, analysis of SSL/TLS and security headers, assessment of DNS setup, and integration of WHOIS data. Live monitoring is supported by real-time logging, and actionable insights to strengthen security posture across infrastructure and online applications are provided via a risk-based grading system with recommendations.

关键词： Visualization Codes SQL injection Vectors Real-time systems Security Risk management Protection Standards Testing

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Evaluation of Selected APIs for Emotion Recognition from Facial Expressions 9th

Evaluation of Selected APIs for Emotion Recognition from Fac...

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9th international Work-conference on the Interplay Between Natural and Artificial Computation (IWINAC)

作者： Kutt, Krzysztof Sobczyk, Piotr Nalepa, Grzegorz J. Jagiellonian Univ Jagiellonian Human Ctr Artificial Intelligence La Krakow Poland Jagiellonian Univ Inst Appl Comp Sci Krakow Poland

ISBN: (纸本)9783031065279;9783031065262

Facial expressions convey the vast majority of the emotional information contained in social utterances. From the point of view of affective intelligent systems, it is therefore important to develop appropriate emotion recognition models based on facial images. As a result of the high interest of the research and industrial community in this problem, many ready-to-use tools are being developed, which can be used via suitable web APIs. In this paper, two of the most popular APIs were tested: Microsoft Face API and Kairos Emotion Analysis API. the evaluation was performed on images representing 8 emotions anger, contempt, disgust, fear, joy, sadness, surprise and neutral distributed in 4 benchmark datasets: Cohn-Kanade (CK), Extended Cohn-Kanade (CK+), Amsterdam Dynamic Facial Expression Set (ADFES) and Radboud Faces Database (RaFD). the results indicated a significant advantage of the Microsoft API in the accuracy of emotion recognition both in photos taken en face and at a 45 degrees angle. Microsoft's API also has an advantage in the larger number of recognised emotions: contempt and neutral are also included.

关键词： Affective computing Facial expression Emotions Benchmark datasets

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Two-Factor distributed Authentication Scheme for Cloud Storage

Two-Factor Distributed Authentication Scheme for Cloud Stora...

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international conference on Computers, Communications, and Systems (ICCCS)

作者： Yunxia Han Chunxiang Xu Shanshan Li Jingjie Lu School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Information Engineering Zhongnan University of Economics and Law Wuhan China

ISBN: (数字)9798350350210

ISBN: (纸本)9798350350227

distributed authentication plays a crucial role in cloud storage, requiring users to authenticate their identity to a set of key management servers. this process guarantees that only authenticated users gain access to cryptographic keys stored in these servers for decrypting outsourced data. How-ever, existing distributed authentication schemes rely solely on passwords, posing a critical weakness due to the recent surge in password-based attacks. Once passwords are compromised, adversaries can impersonate users, gaining unauthorized access to key management servers and acquiring cryptographic keys. To address this vulnerability, a recent multi-factor scheme has been proposed that introduces a distributed authentication mechanism for each popular factor such as passwords, Universal 2nd Factor (U2F), and email. Users could select multiple factors and utilize their corresponding mechanisms when authenticating to servers. Nevertheless, a simple combination of these authentication mechanisms incurs substantial overheads. In this paper, we propose a combined verification mechanism for passwords and U2F, allowing servers to efficiently verify both factors. Based on the mechanism, we present a two-factor distributed authentication for cloud storage, dubbed TDAC. In TDAC, users could authenticate to key management servers through a single password entry and a touch on their U2F. Experiments show that TDAC is efficient in terms of computation and communication overhead.

关键词： Cloud computing Costs Communication systems Authentication Passwords Multi-party computation Computational efficiency

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Supporting IoT Applications with Serverless Edge Clouds 9

Supporting IoT Applications with Serverless Edge Clouds

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IEEE 9th international conference on Cloud networking (CloudNet)

作者： Wang, I Liri, E. Ramakrishnan, K. K. Univ Calif Riverside Riverside CA 92521 USA

ISBN: (纸本)9781728194868

Cloud computing has grown because of lowered costs due to economies of scale and multiplexing. Serverless computing exploits multiplexing in cloud computing however, for low latency required by IoT applications, the cloud should be moved nearer to the IoT device and the cold start problem should be addressed. Using a real-world dataset, we showed through implementation in an open-source cloud environment based on Knative that a serverless approach to manage IoT traffic is feasible, uses less resources than a serverfull approach and traffic prediction with prefetching can mitigate the cold start delay penalty. However applying the Knative framework directly to IoT traffic without considering the execution context gives unnecessary overhead.

关键词： Cloud computing

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