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5th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2024

作者： Ashwatha, K. Smilarubavathy, G. St Joseph's Institute of Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350385649

Recent years have witnessed a substantial increase in website phishing attacks. Many researchers have developed software solutions to detect phishing websites, however it cannot detect these attacks completely. There were several minor challenges in identifying the fraudulent websites. Therefore, the most effective way to detect phishing websites is to incorporate machine learning algorithms into the attack detection process. This improves the overall accuracy of the project and allows for more efficient computation. Implementing machine learning algorithms can also help to overcome the challenges faced by the existing phishing attack detection models. The major purpose of this research is to use the dataset collected to train the ENASSEMBLE Machine Learning (ML) model to detect the phishing websites. © 2024 IEEE.

关键词： Websites

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Aiding Emergency Services Through Real Time Traffic Congestion Monitoring And Route Optimization Using Pic 2

Aiding Emergency Services Through Real Time Traffic Congesti...

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2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies, TQCEBT 2024

作者： SThamarai Selvi, S.B. Thirumurugan, S. Kanish, P. Surya, M. K S Rangasamy College of Technology Department of Computer Science and Engineering Tiruchengode India

ISBN: (纸本)9798350384277

The management of road traffic has emerged as a pressing concern due to a significant increase in accidents and congestion, particularly in densely populated urban areas. To address these challenges, a comprehensive solution has been proposed, consisting of a smart traffic light control and congestion avoidance system tailored for emergency situations such as ambulance services. This system comprises two main components: a smart traffic light control system and a smart traffic routing system. The former intelligently manages traffic lights to prioritize emergency vehicles, while the latter aims to mitigate congestion by providing alternative routes. Equipped with vehicle sensors linked to embedded systems, which in turn connect to ZIGBEE for data exchange, the controller efficiently regulates traffic flow at signal junctions. By strategically placing sensors near traffic signal poles, the system accurately assesses lane densities, facilitating real-time traffic management. Data storage is facilitated through ZIGBEE, while a microcontroller unit communicates alternative route information via LCD display, enhancing overall traffic management efficacy. © 2024 IEEE.

关键词： Zigbee

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Safe and Secure Online Item Bidding using DAPP 8

Safe and Secure Online Item Bidding using DAPP

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8th IEEE International Conference on Computing, Communication, Control and Automation, ICCUBEA 2024

作者： Dixit, Rashmi Kothari, Aditi Jain, Shantala Walchand Institute of Technology Solapur Department of Computer Science & Engineering Maharastra Solapur India

ISBN: (纸本)9798350391770

Electronic communication is expanding quickly right now, and many new applications are following suit. This aided numerous enterprises in turning a profit in their corresponding industries. Online item bidding has become a popular method for buying and selling goods in the digital age. Online item bidding traces its roots back to the early days of the internet when platforms like eBay revolutionized the way people buy and sell goods. Over the years, online item bidding has evolved to include various platforms and technologies, making it a convenient and accessible way for individuals and businesses to engage in commerce. E-Auction System is one of the numerous electronic communication applications that is now receiving a lot of positive feedback from users. An efficient E-Commerce system that enables online communication between a party offering to buy an asset and a party who sells through E-Auction System. The many restrictions of traditional auctions, such as physical location, timing and travel, a finite number of participants, etc., have been greatly reduced by this online format. BlockChain and smart contracts can be used as a ground-breaking technology in our auction system that has caught the interest of numerous sectors. The security of payment gateways is very strong. Our model's objective is to enable everyone to organise their own auctions or participate in the auction from any location on Earth. We must adapt ourselves in accordance with the changes in technology. © 2024 IEEE.

关键词： Smart contract

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Enhancing Web Security: Hybrid Deep Learning Model for Robust URL Phishing Detection 2

Enhancing Web Security: Hybrid Deep Learning Model for Robus...

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2nd IEEE International Conference on Interdisciplinary Approaches in technology and Management for Social Innovation, IATMSI 2024

作者： Dubey, Madhukar Makwana, Rajni Ranjan Singh Madhav Institute of Technology & Science Department of Computer Science & Engineering MP Gwalior India

ISBN: (纸本)9798350360523

Security is the primary difficulty in the realm of the Internet and different kinds of electronic communication. It's significant to remember that phishing is only one of many methods that can be used to compromise a user's security on the internet;in fact, it's become one of the greatest and most successful cyber dangers, responsible for losses of hundreds of millions of dollars & millions of data breaches annually. To steal sensitive user information, phishers create websites that seem almost identical to legitimate ones. Users' private data might be compromised, putting them at risk of identity theft or financial loss. To identify phishing sites, current anti-phishing methods rely on experts manually extracting features from malicious sites and external services. In particular, it takes a lot of effort and skill to extract phishing features using these methods, which is a drawback. In addition, phishing site detection is slowed when external services are used. That's why it's crucial to have a method that can effectively identify phishing websites. To identify malicious websites, this research develops a Deep Learning (DL) model that combines conventional CNNs with BiLSTMs. No content or external services are required for this approach to accurately forecast whether or not a URL is legitimate. The proposed CNN-BiLSTM model is accurate in experiments, with an accuracy of 98.8% being achieved. The results of the DL-based hybrid system prove the superiority of the suggested phishing detection strategy. © 2024 IEEE.

关键词： Websites

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Mechanical properties prediction of metakaolin and fly ash - based geopolymer concrete using SVR

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Journal of Building Pathology and Rehabilitation 2024年第1期9卷 1-14页

作者： Pratap, Bheem Sharma, Sanjay Kumari, Pooja Raj, Sumit Department of Civil Engineering National Institute of Technology Jamshedpur Jharkhand Jamshedpur 831014 India Department of Electrical Engineering National Institute of Technology Jamshedpur Jharkhand Jamshedpur 831014 India Department of Computer Science and Engineering National Institute of Technology Jamshedpur Jharkhand Jamshedpur 831014 India

The field of construction materials and sustainable infrastructure has witnessed a significant shift towards environmentally friendly alternatives. Geopolymers, as an emerging class of materials, have gained substantial attention due to their eco-friendly nature and mechanical properties. One of the key ingredients in geopolymer formulations is metakaolin, a thermally activated aluminosilicate material derived from kaolin clay. This paper delves into an in-depth exploration of the diverse applications of fly ash and metakaolin in geopolymer concrete, highlighting its contributions to the construction industry, environmental sustainability, and technological advancements. In this investigation, the fly ash was substituted in varying proportions of 0%, 10%, 20%, 30%, and 40% across NaOH molar concentrations of 1 M, 3 M, 5 M, and 7 M. The objective was to assess the mechanical characteristics of the newly formulated geopolymer concrete. As consider the scenario where the concentration of NaOH was maintained at 5 M. In this case, the compressive strength of a geopolymer concrete (FM2), which comprised 20% metakaolin, demonstrated a maximum compressive strength of 55.28 MPa. Notably, the influence of metakaolin on bolstering compressive strength seems to be most noticeable when employed as a substitute at the 20% proportion. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Compressive strength Fly ash Geopolymer Metakaolin Sodium hydroxides

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Novel Framework for Dengue Classification and Early Recovery using Machine Learning Algorithms 18

Novel Framework for Dengue Classification and Early Recovery...

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Faritha Banu, J. Hariprasad, G. Archana, T. Srivatsan, Prahadees Srm Institute of Science and Technology Department of Computer Science and Engineering Chennai Ramapuram India

ISBN: (纸本)9789380544519

Dengue fever is a fast-emerging public health hazard that primarily affects tropical and sub-tropical regions. Arthropods that feed on blood, such as fleas, parasites, and mosquitoes, are the carriers of this disease, which can infect humans and cause significant illness. Five serotypes of the dengue virus - DEN V1, DEN V2, DEN V3, DEN V4, and DEN V5 are spread by Aedes aegypti mosquitoes. Currently, this illness is spreading to many other countries. A delayed diagnosis combined with the wrong method of treatment increases the chance of death. Based on the severity of the infection, dengue is classified into Dengue Hemorrhagic Fever (DHF) or Dengue Shock Syndrome (DSS) which are categorized into febrile, critical, and recovery phases. A framework model is essential to analyze the severity of the infection and identify the phase of severity. Among various machine learning algorithms, this study uses Support Vector Machine and Random Forest for their proficiency in handling complex data. Through rigorous feature engineering and data preprocessing, critical information for precise discrimination was extracted and examined for DHF phases. Experimental results demonstrate both models are competent, but SVM is more suitable for the proposed prediction model with an accuracy 95%, precision of 93%, recall of 94%, and F-measure metrics of 94%. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Dengue Dengue Haemorrhagic Fever Dengue Shock Syndrome Support Vector Machine and Random Forest

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Emotion-Aware Music Recommendations: Evaluating Custom CNN vs. VGG16 and InceptionV3

Emotion-Aware Music Recommendations: Evaluating Custom CNN v...

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2024 IEEE International Conference on Future Machine Learning and Data Science, FMLDS 2024

作者： Patel, Varesh Mehta, Khyati G H Patel College of Engineering and Technology Computer Department Gujarat Anand India

ISBN: (纸本)9798350391213

This study conducts a comparative analysis of various pretrained models for detecting emotions from facial expressions, introducing a novel Convolutional Neural Network (CNN) designed to enhance accuracy. We evaluate the performance of well-known models such as VGG16 and InceptionV3 alongside our proposed CNN architecture to determine the most effective model for incorporating facial emotion detection into music recommendation systems. Our system utilizes facial expressions captured through webcams or images to deliver personalized music suggestions that reflect users' current emotional states, aiming to enhance user engagement on music streaming platforms. By outlining methodology, including dataset compilation and preprocessing strategies, we test and validate our CNN architecture, revealing its superiority over existing models in accuracy. The integration of sophisticated facial emotion detection into recommendation systems offers a transformative way to improve the user experience by providing emotionally attuned music suggestions. Our findings demonstrate that this advancement holds promise for applications in digital music streaming, enhancing user engagement and personalization. By leveraging facial expression analysis, we can create more effective music recommendation systems that cater to individual users' emotional needs, leading to increased user satisfaction and loyalty. © 2024 IEEE.

关键词： Convolutional neural networks

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Securing Secret Information 1st

Securing Secret Information

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1st International Conference on Sci/Tech and engineering, ICSTE 2023

作者： Shamsi, Zeba Singh, Laiphrakpam Dolendro Department of Computer Science and Engineering National Institute of Technology Assam Silchar788010 India

ISBN: (纸本)9789819947126

The art of information concealment has become a crucial subject since information security has grown to be a primary concern in the online world. Using cryptography and steganography plays a significant role in secure data transfer. Steganography is a covert writing technique;the message is contained behind a cover medium. Cryptography encrypts messages to hide their contents. Two-dimensional bar codes called QR codes can store text strings. They can encode data both vertically and horizontally, encoding more information. By combining the ideas of cryptography, steganography, and QR codes, an innovative method for covert communication is proposed in this paper. Statistical and security analyses of the proposed method show that the proposed method provides better imperceptibility, security, and robustness. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Steganography

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A Real-time Approach for Multi-physics Field Reconstruction of Active Phased Array Antenna

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IEEE Transactions on Antennas and Propagation 2025年第6期73卷 3585-3592页

作者： Feng, Shizhe Chen, Qihang Li, Zhixiong Sotelo, Miguel Angel The State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin300130 China The Faculty of Mechanical Engineering Opole University of Technology Opole45-758 Poland The Department of Computer Engineering University of Alcalá Madrid28801 Spain

This study proposes an effective approach to reconstruct the multi-physics field of the active phased array antenna (APAA) through limited information of temperature and strain. First, the multi-physics coupling model of the APAA is constructed to analyze the thermal-mechanical-electromagnetic responses;the model calculation accuracy is verified by experimental testing. Then, a large number of samples containing the temperature and deformation information are generated through the coupling model. Subsequently, the multi-physics field reconstruction model is established based on the extreme gradient boosting (XGBoost) method, in which the parallelization computing is implemented to fully improve the prediction efficiency. Lastly, the testing samples are used to evaluate the performance of the reconstruction model. The obtained results indicate that the developed model is able to reconstruct the multi-physics field of the APAA in real time more precisely through comparing with existing machine learning methods. This approach can provide reliable temperature and displacement reconstruction information for the compensation of the APAA electromagnetic performance. © 1963-2012 IEEE.

关键词： Antenna phased arrays

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A Weighted Privacy Mechanism under Differential Privacy 4

A Weighted Privacy Mechanism under Differential Privacy

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4th International Conference on Intelligent Technologies, CONIT 2024

作者： Hemkumar, D. Prashanth, Pvn Visvesvaraya National Institute of Technology Department of Computer Science and Engineering Maharhastra Nagpur India

ISBN: (纸本)9798350349900

As digital technology advances, electronic databases are amassing an ever-growing volume of personal data. Even with the removal of explicit identifiers, such as names and addresses, the remaining data fields can still be leveraged to create distinct individual profiles, posing a significant threat to privacy. Therefore, safeguarding the privacy of individuals within datasets is of utmost importance. One highly effective technique for preserving privacy is differential privacy. Existing literature has employed various methods, such as Laplace and output perturbation, to achieve differential privacy. However, the accuracy of these mechanisms varies depending on the specific queries and the chosen value of є. Consequently, there exists a necessity for a differential privacy mechanism that can maintain accuracy across a wide range of queries. In this paper, we propose a method within the differential privacy framework known as the 'weighted mechanism'', which integrates elements from both Laplace and perturbation mechanisms. This approach involves releasing outputs with the addition of random noise from a defined distribution. To evaluate its effectiveness, we conduct a series of experiments comparing the accuracy of established differential privacy methods with the proposed weighted mechanism across various types of queries. © 2024 IEEE.

关键词： Differential privacy

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