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Sybil Attack Models of MM-Wave Communication for LEO Satellite Network in Cybersecurity

Sybil Attack Models of MM-Wave Communication for LEO Satelli...

引用

2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Mohamed, Abdiasis Ahmed Chang, Shih Hao National Taipei University of Technology Dept. Computer Science and Information Engineering Taiwan

ISBN: (纸本)9798350324174

With the rapid progress of six-generation (6G) wireless communication technologies, Low Earth Orbit (LEO) satellite global network technology played a very important role and promoted millimeter-wave (mm-wave) systems gained demand. However, security remains a critical concern in wireless network design and usage. In this paper, we propose a method based on an artificial intelligence technique, machine-learning algorithms in cybersecurity. This approach handles significant security dataset training, using different techniques such as decision trees and Recurrent Neural networks, which allow feature selection and Sybil attack classification. In addition, we refer to the guidelines and specifications of orbit satellite standards in ISO 16164-2015 and ISO 27852-16 to validate the satellite transmitter. Simulation results arise an improvement in security and the ability to detect and prevent Sybil attacks. Overall, this approach makes a significant contribution to the field of satellite cybersecurity by providing a standard-compliant solution © 2023 IEEE.

关键词： Recurrent neural networks

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Feature Extraction Based Acoustic Signal Detection in a Cost Effective Φ-OTDR System 2

Feature Extraction Based Acoustic Signal Detection in a Cost...

引用

2nd International Conference on Microwave, Optical and Communication engineering, ICMOCE 2023

作者： Verma, Shruti Mathew, Jimson Gupta, Sumanta Indian Institute of Technology Patna Dept. of Electrical Engineering India Indian Institute of Technology Patna Dept. of Computer Science and Engineering India

ISBN: (纸本)9798350321609

The paper presents an experimental demonstration of acoustic signal detection in a phase-optical time domain reflectometer (Φ-OTDR) system based on feature extraction. A commercially available off-the-shelf distributed feedback (DFB) laser is used as a light source with a minimum of 25kHz of linewidth. Also, a low sampling rate (60MS/s) data acquisition (DAQ) system is used to collect the backscattered traces. Using the digital signal processing (DSP) technique, the noisy signal from the Φ-OTDR system is processed to extract the different features of the signal. The location of the acoustic signal source is identified based on variance along the fiber length. Besides, power spectral density at that perturbed location is estimated to determine the acoustic signals frequencies. Using this low cost experimental set-up, the location of the acoustic signal source having 100Hz, 125Hz, and 150Hz frequencies were successfully detected over a 1 km of fiber length. © 2023 IEEE.

关键词： Location

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Zero Cost Online Food Delivery System with Machine Learning Prediction 7

Zero Cost Online Food Delivery System with Machine Learning ...

引用

7th International Conference on Intelligent Computing and Control Systems, ICICCS 2023

作者： Reddy, Yaparla Adithya Kumar Swaroop, Chebrolu Satya Terence, Sebastian Reddy, Kummetha Sai Manoj Santhosh, Korrapati Karunya Institute of Technology and Sciences Dept. of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350397253

The growth of Food Delivery Application (FDA), helps customers to get variety of food items in their door steps. This helps restaurant to serve their customers with different food items, and to increase their business. FDA also provides jobs to millions of food delivery persons. But the major drawback of FDA is high commission charges for food orders. This article presents zero cost online food delivery system with ML prediction models. Zero cost online food delivery system provides user friendly interface to restaurant, home makers, customers and delivery persons. In this system, the restaurant or home makers can showcase their food items. The customers would be able to place the order. Delivery person can show interest towards delivery of the order. The customers have an option to select the delivery person for delivery and pay the delivery charges. All the payments are done through UPI payment. Advantage of the system is, it will not collect commission from home makers (or) restaurant owners and customers for the orders and also Machine Learning models is used to suggest food items based on different factors. Random Forest, Decision Tree Regression, K-Nearest Neighbor, and Extra Tree Classifier models are used to suggest food items to the customer. © 2023 IEEE.

关键词： Decision trees

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Efficiency Measurement of k-Partitioning of Mobile WSN 4

Efficiency Measurement of k-Partitioning of Mobile WSN

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4th IEEE International Conference on Computing, Communication, and Intelligent Systems, ICCCIS 2023

作者： Hossain, Azad Rehena, Zeenat Murshidabad Institute of Technology Lecturer in Computer Science and Technology Berhampore India Aliah University Dept. of Computer Science and Engineering Kolkata India

ISBN: (纸本)9798350306118

Network partitioning improves the energy efficiency of the network. In this work, the algorithm (KP-MWSN) can determine the no. of partitions (k) required based on the delay tolerance limit of each node of MWSN. It can be fruitful for the events where a small amount of delay can be accepted but efficiency has not been calculated in respect of a metric. So, we have measured the efficiency of KP-MWSN algorithm and the results are compared with the Topology Partitioning Scheme (TPS). The simulation result shows that in every randomly created event the efficiency of KP-MWSN is always better than other related state-of-The-Art work. © 2023 IEEE.

关键词： Energy efficiency

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An Overview on Breast Cancer Detection & Classification Methods Using Machine Learning Techniques 3

An Overview on Breast Cancer Detection & Classification Meth...

引用

3rd International Conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Philip, Rohan Mathew Raj, Rishabh K Shaji, Ashwin Althaf, Fathima Sudarsan, Dhanya Muthoot Institute of Technology and Science Dept. of Computer Science & Engineering Kerala India

ISBN: (纸本)9798350322842

Breast cancer is a prevalent and deadly disease that primarily affects women. Breast cancer has claimed the lives of many people all over the world. Early breast cancer detection, on the other hand, can significantly improve a woman's chances of survival. There are various approaches and procedures for detecting cancer in breast tissue. Breast cancer may be detected using Image Processing, Machine Learning, and Deep Learning methodologies and techniques. People who use trustworthy techniques and make better selections will be able to discover breast cancer in its early stages and save a woman's life. This research aims to contemplate and make inferences from diverse studies on the subject of classification using Machine Learning approaches. The researchers and physicians who devote their time and expertise to enhancing breast cancer screening methods will definitely profit from this research study. © 2023 IEEE.

关键词： Convolutional neural networks

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A Systematic Study of Challenges in Cervical Cytology Image Segmentation of Intelligence based Cervical Cancer Screening 4

A Systematic Study of Challenges in Cervical Cytology Image ...

引用

4th IEEE Global Conference for Advancement in technology, GCAT 2023

作者： Anu, P.M. Lakshmi, C. Dept. of Computer Science and Engineering SRM Institute of Science and Technology Kattankulathur India

ISBN: (纸本)9798350305258

Cervical Cancer (CC) is the fourth frequent dreadful cancers that prevails in women across the globe. Cervical cytology is being adopted as the standard technique for the screening of pre-cancerous stage and cancerous lesions detection. For accurate segmentation in cervical cytology, the smear images play a crucial role in any Artificial Intelligence based computer Aided Diagnosis (CAD) method. This relies upon the precise segmentation of nucleus present in the cervical cytology smear images. The motive of this study deals with a systematic analysis of the various challenges that are encountered while segmenting the Cervical Cell Nucleus and the countermeasures that are incorporated to eliminate the misdiagnosis and missed diagnoses in the early stage of screening. With the motive of this, a systematic study of the published articles from the sources - Scopus, PubMed and Web of Science are analyzed and reviewed. The importance of this study is due to the intensity of the disease that still positions cervical cancer as a bothering disease that disrupts the life of about five lakh female population, every year across the world. © 2023 IEEE.

关键词： Cervical Cancer Cervical Cytology Cervical Nucleus Challenges in Cervical Cytology Segmentation Intelligence based Cervical screening

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Sentiment Analysis of Political Party Twitter Data using Ensemble Learning Classifier 14

Sentiment Analysis of Political Party Twitter Data using Ens...

引用

14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Kumar, Sunny Uddin Haider, Md. Tanwir National Institute of Technology Patna Dept. of Computer Science & Engineering Patna India

ISBN: (纸本)9798350335095

Sentiment analysis is a field that has gained a lot of popularity in the last decade. We can identify the sentiment of a user in various fields like 'Movie Reviews', 'Hotel reviews', 'Online Product reviews' etc. Analysis of sentiment helps the other user in decision-making. Nowadays, sentiment analysis is also being used in the political scenario to select appropriate candidates/parties. Seeing this fact, we have performed a sentiment analysis on the political Twitter dataset to find out which Indian political party is getting positive/negative reviews. Generally, researchers use Textblob which is a lexicon-based sentiment analyzer to predict sentiment. The lexicon-based technique does not provide good accuracy to predict sentiment therefore in this paper we have applied ensemble learning using boosting techniques along with basic machine learning and deep learning techniques like SVM and LSTM. The result in terms of accuracy and ROC-AUC shows that ensemble learning *** with SVM outperform as compared to other ML technique. The accuracy is 87% and the ROC-AUC score is 93%. © 2023 IEEE.

关键词： Sentiment analysis

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Secured Full-Duplex UAV-Aided Spectrum-Sharing Network Based on NOMA 20

Secured Full-Duplex UAV-Aided Spectrum-Sharing Network Based...

引用

20th IEEE International Conference on Mobile Ad Hoc and Smart Systems, MASS 2023

作者： Hasan, Moh Khalid Yu, Shucheng Song, Min Stevens Institute of Technology Dept. of Electrical and Computer Engineering Hoboken United States

ISBN: (纸本)9798350324334

Non-Orthogonal Multiple Access (NOMA) has emerged as an effective approach for improving spectral efficiency. In addition, Unmanned Aerial Vehicle (UAV)-aided communication offers rapid deployment and flexibility in challenging environments. Studying physical layer security in these scenarios is crucial to protect sensitive data from eavesdropping in spectrum-sharing networks. Nonetheless, there is limited research on comprehensive secrecy analysis in NOMA-based spectrum-sharing networks, particularly in the context of full-duplex UAV-assisted scenarios. In this paper, we investigate the secrecy performance of a UAV-aided and full-duplex NOMA-based spectrum-sharing network. The system primarily involves a primary source communicating with a full-duplex secondary source, which then simultaneously relays combined data from both sources to the primary and secondary receivers. Considering the susceptibility of both transmission stages to an external eavesdropper, the secondary source employs artificial jamming to enhance secrecy for both primary and secondary users. We analytically derive the ergodic secrecy achievable rate (ESAR) for the primary and secondary networks. The closed-form expressions are obtained by characterizing the channels' probabilistic nature while considering the Nakagami-m fading properties of each channel. Through our analysis and Monte Carlo simulations, we demonstrate that our proposed scheme achieves a positive ESAR and outperforms benchmark schemes relying on OMA. © 2023 IEEE.

关键词： Antennas

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A Review on Dam Water Level Alerting System Using IoT

A Review on Dam Water Level Alerting System Using IoT

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2023 IEEE International Students' Conference on Electrical, Electronics and computer Science, SCEECS 2023

作者： Dudhe, Priyanka Magarde, Gaurav Raj, Madan Karemore, Aditya Wankhede, Jayesh Jhulelal Institiue of Technology Dept. of Computer Science Engineering Maharashtra Nagpur India

ISBN: (纸本)9798350398748

The goal we outline in this article is the application system with Internet of Things (lOT) integration to secure the public's safety regarding the early warning of flood events caused by a rise in water levels in the dams and reservoirs. To accomplish the goal, a Software-as-a-Service is upheld, incorporating information about the area and data from periodic water level monitoring using wireless technologies and Global System for Mobile Communication (GSM). As a result, the public is automatically informed of the earlier stages of the water level rise. © 2023 IEEE.

关键词： Water levels

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DeFy: P2P Crypto Lending 14

DeFy: P2P Crypto Lending

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Thalakottur, Joel Ray, Ben Abraham Victor, Alex Vyas, Aryan St. Francis Institute of Technology Dept. of Computer Engineering Mumbai India

ISBN: (纸本)9798350335095

The debt market is a substantial industry, estimated to be of significant value and projected to grow further in the near future. However, its size is marred by inefficiencies due to a lack of transparency and trust. To address these issues, DeFy, a blockchain-based system, offers loans to borrowers using their cryptocurrency assets as collateral. Leveraging smart contract technology and a decentralized network, DeFy creates a secure and transparent lending environment that operates globally without intermediaries. Empowering users with autonomy to select preferred lenders through a robust bidding system, DeFy enhances transparency in the borrowing process and empowers borrowers to make informed decisions. This user-driven lending approach provides an efficient and secure means for borrowers to access capital without liquidating their cryptocurrency holdings, while allowing lenders to earn interest on their capital through the lending process. © 2023 IEEE.

关键词： Blockchain

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