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Performance Evaluation of Blockchain Platforms

Performance Evaluation of Blockchain Platforms

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2023 International Conference on IoT, Communication and Automation Technology, ICICAT 2023

作者： Gupta, Manish Kumar Dwivedi, Rajendra Kumar Sharma, Annu Farooq, Mansoor Britto Raj, S. Madan Mohan Malaviya University of Technology Department of Information Technology & Computer Application Gida Gorakhpur India RajaRajeshwari College of Engineering Department of Computer Science & Application Bengaluru India University of Kashmir Department of Management Studies Jammu & Kashmir India Rrase College of Engineering Department of Computer Science & Engineering Chennai601301 India

ISBN: (纸本)9798350302820

Blockchain (BC) is a cryptographic technology that enables the decentralized storage of an immutable record of transactions. As a result, many industries are interested in integrating BC into their IT systems. Although BC-based platforms are used in enterprise solutions, concerns regarding accessibility, privacy, performance, and scalability are still legitimate. Permissioned Blockchain (PBC) frameworks provide a solution to securely store private records. The main objective of this paper is to focuses on the performance and scalability of popular private BC platforms. To evaluate each platform, we varied the workloads and assessed performance metrics. Our comparative analysis provides valuable insights into the strengths and weaknesses of each platform, enabling enterprises to make informed decisions when choosing a private BC solution. © 2023 IEEE.

关键词： Blockchain

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Hate Speech detection in English and Malayalam Code-Mixed Text using BERT embedding

Hate Speech detection in English and Malayalam Code-Mixed Te...

引用

2022 International Conference on Computing, Communication, Security and Intelligent Systems, IC3SIS 2022

作者： Deepasree Varma, P. Vinod, P. Nandakumar, M. Akshay, K. Madhu, Akhil Scms School of Engineering and Technology Department of Computer Application Cochin India Cochin University of Science and Technology Department of Computer Application India Christ College of Engineering Irinjalakkuda Department of Electrical and Electronics Engineering India SCMS College of Engineering and Technology Karukkutty Department of Computer Application Ernakulam India

ISBN: (数字)9781665468831

ISBN: (纸本)9781665468831

Hate speech detection is a very popular research area for past few years. Hate speech is given various definition by various researchers. In this paper we try to analyse the use of BERT embedding in hate speech detection in low resource language like Malayalam. The crucial challenge faced by researchers in this area are that most non-English languages are represented in code-mixed form in Social media. Here we work with transformer-based models to classify tweets as hate or non-hate content. Hence this is a novel approach that uses BERT in non-English text. © 2022 IEEE.

关键词： Embeddings

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Exploring the Benefits of Interactive Communication Media Algorithms for Networking applications 3

Exploring the Benefits of Interactive Communication Media Al...

引用

3rd International Conference for Innovation in Technology, INOCON 2024

作者： Ahmed, Zahid Beemkumar, N. Ghosh, Debanjan Vivekananda Global University Department of Computer Science & Application Jaipur India School of Engineering and Technology Department of Mechanical Engineering Karnataka Bangalore India Arka Jain University Department of Computer Science & It Jharkhand Jamshedpur India

ISBN: (纸本)9798350381931

Interactive communication media algorithms are useful tools for creating efficient and effective networking applications. Such algorithms enable the application to accurately predict user behaviour and preferences, use natural language processing to automate conversations, and integrate with other systems. This paper investigates the benefits of using interactive communication media algorithms for developing networking applications, including improved user experience, scalability, and quicker response times. Additionally, this paper will address potential limitations, such as the need for significant data collection and availability of relevant computing resources. Finally, this paper will conclude with a discussion of the potential implications of further investigations into interactive communication media algorithms for networking applications. © 2024 IEEE.

关键词： Behavioral research

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Genetic Algorithm-Based Data Allocation in Multi Media Using Cloud Computing 3

Genetic Algorithm-Based Data Allocation in Multi Media Using...

引用

3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Yadav, Surendra Kaur, Manpreet 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 recent growth of Internet-of-Things (IoT) applications using cloud computing has been amazing. One of the advancements is heterogeneous cloud computing, which has made it possible to use the cloud for a range of infrastructure solutions, including multimedia big data. The optimizations of on-premise heterogeneous memory have been the subject of several past studies. However, the performance and financial limits brought on by hardware distributions and manipulative techniques are placing restrictions on the heterogeneous cloud memory. It is an NP-hard combinatorial issue to distribute data jobs across dispersed memory with different capacities. In order to provide high performance cloud-based heterogeneous memory service offerings, this study focuses on this problem and suggests a unique solution called Cost-Aware Heterogeneous Cloud Memory Model. It allocates data to the cloud-based memory via genetic programming. In our suggested method, we take into account a number of important elements that have a significant influence on how well Communication expenses, data transfer operating costs, energy performance, and time constraints all play a role in how cloud memories operate. Finally, we put our suggested paradigm to the test via experimental assessments. The trial findings have demonstrated the viability and scalability of our technique as a cost-conscious cloud-based solution. © 2023 IEEE.

关键词： Genetic algorithms

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Handling High-Dimensional Data and Classification Using a Hybrid Feature Selection Approach 2

Handling High-Dimensional Data and Classification Using a Hy...

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2nd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2022

作者： Agrawal, Shobit Sharma, Dilip Kumar Gla University Department of Computer Engineering Application Mathura India

ISBN: (纸本)9781665437899

Recently, we published a paper on feature selection and extraction technique on time series data classification: A Comparative analysis mainly focusing on classifiers, in this paper, we are implementing 10 classifiers on 3 open source datasets of UCI machine learning and measuring accuracy, precision, recall, and f1 score. On classifying using 10 classifiers over 3 open-source datasets results reveal that the confusion matrix attributes show the best results in the case of two classifiers, i.e. XGBoost and LightGBM. We proposed a hybrid approach by combining the filter class Minimum Redundancy and Maximum Relevance method and wrapper class Recursive Feature Elimination method with the above two classifiers. Results reveal that XGBoost and LightGBM Classifier outperforms the other classifiers in terms of confusion matrix attributes and the proposed hybrid model gives 95.28% accuracy with 13 feature by the lightgbm classifier and 93.4% accuracy by XGBoost classifier with 10 features on the ionosphere dataset. © 2022 IEEE.

关键词： Clustering algorithms

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A Multi-Objective Decision Assistance System for Selecting Security Controls Based On Simulation 3

A Multi-Objective Decision Assistance System for Selecting S...

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3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Shree, Ritu Sandhu, Komal 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

In this work, we present the results of our continuing investigations into simulation-based risk analysis for information security and multi-objective investment optimization for security controls. We provide a methodological approach that takes into account the organization's features, information architecture, assets that must be safeguarded, unique threat sources encountered, and decision-makers' risk preferences. This framework includes dynamic attack graph generation techniques, ontological modelling of security knowledge, probabilistic reenactment of assaults by objective driven danger specialists, Identification of compelling arrangement of data security controls utilizing meta-heuristics, and intuitive choice help. These components make it possible for cutting-edge techniques to generate attack graphs and infer potential attack routes based on the motivations, goals, skills, and available entry points of attackers, Then, using this inferred information, simulate assaults based on the infrastructure a model of an organisation. The strategy aids decision-makers weigh financial and non-financial factors related to risks, costs, and benefits when assessing possible security control initiatives. In order to assess the strategy through application case studies, we are now constructing a prototype implementation of the framework. © 2023 IEEE.

关键词： Decision support systems

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A Case of Customer Segmentation in the Saving and Finance Industry

A Case of Customer Segmentation in the Saving and Finance In...

引用

Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference

作者： Khalilbayli, Fidan Köse, Zekeriya Computer Engineering Department Istanbul Technical University Istanbul Turkey IT Application Solutions Division Eminevim Istanbul Turkey

ISBN: (纸本)9783031397769

Businesses in the finance and investment sector are continually looking for different ways to gain a competitive advantage. One of the most effective ways to achieve this is through customer segmentation. The aim of the conducted study is to implement segmentation on demographic and behavioral customer data of the company Eminevim. After the pre-processing stage, the optimum cluster number is decided using the Elbow method. The performance of different clustering techniques is compared using the SI score where K-means outperformed. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Data mining

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BIFT: A federated learning System for Connected and Autonomous Vehicles Based on Blockchain 3

BIFT: A federated learning System for Connected and Autonomo...

引用

3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Yadav, Aarti Kaur, Amandeep 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

Algorithms for machine learning(ML) are essential for autonomous driving. The vast majority of history's automated and connected cars send a significant quantity of movement data collected from many automobiles to a central server for regular training. Nonetheless, the info process has made the safety and confidentiality of information essential. Nowadays, the development of federated learning (FL) for data security has the potential to potential to enhance distributed machine learning's data privacy. The malicious attackers might still target the training process, though. FL is extremely vulnerable because of its total dependency on the central server. We suggest BIFT as a solution to the aforementioned issue, which consists of two parts: 1) a completely decentralized 2) A blockchain-based machine learning system for CAVs that guarantees privacy. With the use of their own driving data, BIFT's scattered CAVs may train local machine learning models, which they can subsequently upload to improve the global model. In order to fend off potential attackers, BIFT offers a consensus mechanism called Proof of Federated Learning. We assess BIFT's performance and demonstrate that it is scalable, reliable, and capable of fending off harmful assaults. © 2023 IEEE.

关键词： Autonomous vehicles

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Convolutional Neural Network-Based Anomaly Detection for Cyber Security: A Survey 3

Convolutional Neural Network-Based Anomaly Detection for Cyb...

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3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Agarwal, Neha Kaur, Amandeep 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

There are many security risks as computer and communication technologies continue to advance. To reduce these worries, several different kinds Numerous processes with cyber-security enabled have been developed. Anomaly detection is one of these methods. Finding anomalies involves employing a variety of approaches and procedures to identify various patterns that do not adhere to predetermined characteristics of the entire body of data. Deep learning techniques have recently been accepted as an adequate option due to their capacity to take data properties directly from the data. Convolution neural network (CNN) is employed primarily because it can handle input with many dimensions. This study offers a thorough analysis of the use of CNN as a primary tool for anomaly identification. The majority of the known remedies have been compiled and categorized in the literature. Additionally, this research provides a bound together cross framework that mimics complete anomaly detection methods that were previously offered examinations, as per the information source. In-depth assessment from a brought together cross system upgrades this paper's top to bottom conversation of how CNN is utilized in the writing's response to the irregularity identification issue. Finally, this article makes a number of recommendations for future study areas that the audience may find useful in their own further activities in this area. © 2023 IEEE.

关键词： Anomaly detection

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Groundwater Evaluation with Classification Techniques

Groundwater Evaluation with Classification Techniques

引用

2023 International Conference on Artificial Intelligence and Smart Communication, AISC 2023

作者： Dogra, Yakesh Khan, Mizan Ali Chandigarh School of Business Department of Master of Computer Application India Sanskriti University Department of Computer Science Engineering Uttar Pradesh Mathura India

ISBN: (纸本)9798350322309

We has researched that your earth area contains % comprised of water and the remaining 28 part also with soil. From the 28 per cent, % water is seawater namely it is excessively salted for consuming, for agricultural production and more critical items. That's because the freshwater which seems utilised is extremely small in bulk and its condition is every day growing worse. The condition of the water must be kept since it is a crucial life factor not just the individuals as well as other creatures and flora. Humans demand a suitable level sustained liquid to consume and employ in varied daily tasks Assessments of groundwater recharge and assessment are thus essential for the development of economy and society. Photogrammetry is now a crucial technique for ground component assessment as a result of advances. So to assure if the groundwater we get is excellent or wouldn't we have gathered a set and used multiple Ml techniques to assess the auc. So, the research intends to determine the prognosis of water whether it is of good standard or not by utilizing two algorithms, rbfnn and perceptron and to demonstrate which outperforms. © 2023 IEEE.

关键词： Support vector machines

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