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Data Analysis of Dark Web Marketplaces using Machine Learning 7

Data Analysis of Dark Web Marketplaces using Machine Learnin...

引用

7th International Conference on Signal Processing and Information Security, ICSPIS 2024

作者： Pratham Rao, U.N. Guruprasad, Rachit Raam Shetty, Omkaar J Sarasvathi, V. Rapate, Gauri Sameer PES UNIVERSITY Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350368673

People refer to the dark web as the anonymous part of the internet that is very hard to access, it has been described as lying some distance beyond the easily accessible surface web and more obscure deep web. This means that the dark web is accessed by using specially designed software, and it hosts all manner of illicit activities that present huge challenges to law enforcement. This section, known as the dark web, may only be accessed with the use of special designed programs, such as Tor. In this sphere of the net, it is feasible for both the user and the owners of any site to claim anonymity. The dark web is still notorious for offering illegal activities such as drugs markets, selling firearms, and providing services in cybercrime, though it is on the gray area of applying it towards journalists, social activists, and whistleblowers. But it is pretty much important to note here that the deep web or parts of the internet and the dark web are very much different things. In order to shed some light on how to overcome these challenges, we have come up with a custom web crawler specifically designed to work inside the Tor network, extracting data from various dark web marketplaces. In this paper, we will be focusing on the profiling of vendors according to categories and geographical origins, with an emphasis on operational patterns of these cloaked entities. To sum it all, our customized web crawler provides great insights about profiling vendors in dark web markets and categories where they originated. © 2024 IEEE.

关键词： Marketplaces

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An In-dept. Exploration of Machine Learning Algorithms and Performance Evaluation Approaches for Personalized Diabetes Prediction

An In-Depth Exploration of Machine Learning Algorithms and P...

引用

2024 International Conference on Emerging Innovations and Advanced Computing, INNOCOMP 2024

作者： Kaur, Inderdeep Ali, Aleem Chandigarh University Dept. of Computer Science and Engineering Kharar India

ISBN: (纸本)9798350376470

Diabetes is now recognised as a major worldwide health problem, demanding effective early detection and prediction measures to limit its repercussions. Machine learning algorithms have shown to be excellent tools in healthcare for creating prediction models. This paper delves into an extensive investigation of machine learning (ML) algorithms and methodologies for assessing their performance in the context of personalized diabetes prediction. Different machine learning models are rigorously explored and evaluated for how well they can customise forecasts to the unique characteristics of individual patients. The study also critically assesses several performance evaluation techniques in an effort to improve the accuracy and reliability of diabetes prediction algorithms. Furthermore, interpretability problems and class imbalance are addressed as challenges and limitations to the application of machine learning in the prediction of diabetes. This study aims to motivate researchers, facilitating a deeper understanding of disease prediction algorithms and conduct related research. © 2024 IEEE.

关键词： Prediction models

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Enhancing Efficiency in the IOTA Tangle: A POMDP-Based Tip Selection Approach

Enhancing Efficiency in the IOTA Tangle: A POMDP-Based Tip S...

引用

2024 International Conference on computer and applications, ICCA 2024

作者： Alshaikhli, Mays Al-Maadeed, Somaya Saleh, Moutaz Qatar university Dept. Computer Science and Engineering Doha Qatar

ISBN: (纸本)9798350367560

The IOTA Tangle represents a promising alternative to blockchain technology, particularly for the Internet of Things (IoT) environment. However, ensuring efficiency and fairness in transaction processing remains a significant challenge. This paper focuses on the efficiency of the Tangle by evaluating a novel POMDP-based Tip Selection Algorithm (TSA). Through comparative analysis against Weighted TSA, G-IOTA, and E-IOTA under varying network loads (lambda values), the POMDP algorithm demonstrates superior performance in maintaining the fastest confirmation process and more efficiency in different network conditions. These results establish POMDP as a scalable and efficient solution, contributing to the advancement of decentralized ledger technology. Future directions include real-world testing and the integration of adaptive network factors for enhanced scalability. © 2024 IEEE.

关键词： Blockchain

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Integrating Tradition and Technology: A Survey of AI applications in the Design of Temple Architecture

Integrating Tradition and Technology: A Survey of AI Applica...

引用

2024 International Conference on Artificial Intelligence, Metaverse and Cybersecurity, ICAMAC 2024

作者： Meghana, J. Bellad, Harshavardana R. Pardhi, Diya Magdum, Ishwari Nagaraj, Chaitra Dept. Computer Science Engineering PES University Bengaluru India

ISBN: (纸本)9798350353488

This article will delve into the complicated inter-building of artificial intelligence and traditional skill of temple architecture of South India. It meticulously analyzes the historical roots of temple design, explaining in detail the subtle means and methods that have always been used in temple construction. Apart from detailed preparation and skilled craftsmanship, it is the cultural heritage that is demonstrated with these monumental creations. In the sequel, the paper sheds light on how AI technologies are transforming temple architecture through systems analysis and optimization, generative design and other methods. Living examples of Artificial Intelligence work do not only confirm the successful AI implementations but also illustrate the smooth link between tradition and novelty in the modern temple designs. © 2024 IEEE.

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Enhancing Network Security with AdvancedNetwork Scanning Tools 6

Enhancing Network Security with AdvancedNetwork Scanning Too...

引用

6th Parul International Conference on engineering and Technology, PICET 2024

作者： Patel, Shubh Christian, Prarthan Mistry, Kartikay Raj, Krenil Raithatha, Hiren Dept. Computer Science and Engineering Parul University Vadodara India

ISBN: (纸本)9798350369748

This research paper introduces a sophisticated network scanning tool designed to enhance cybersecurity measures by integrating advanced techniques in operating system (OS)detection, service scanning, and intrusion detection system (IDS) / intrusion prevention system (IPS) detection. The tool aims to provide a comprehensive approach to network security assessment, offering robust capabilities for identifying potential vulnerabilities and mitigating security risks. The OS detection module employs a combination of fingerprinting techniques and heuristics to accurately identify the underlying operatingsystems of networked devices. This information is crucial forunderstanding the network environment, enabling administrators to implement targeted security measures. The tool incorporatesa sophisticated IDS/IPS detection mechanism to identify and evaluate the effectiveness of intrusion detection and prevention systems in place. This feature is vital for assessing the net- work’s resilience against potential threats and ensuring that the deployed security mechanisms are robust and up-to-date. The research paper details the methodology behind each scanning module, highlighting the innovation and integration of cutting- edge technologies. Additionally, practical use cases and real-world scenarios are presented to demonstrate the tool’s effectiveness in identifying and addressing security concerns in diverse network environments. © 2024 IEEE.

关键词： Network intrusion

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Intelligent Trolley System: Revolutionizing Retail Shopping 18

Intelligent Trolley System: Revolutionizing Retail Shopping

引用

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

作者： Patel, Urmi Aglodiya, Mohmmadali Paliwal, Manish Shastri, Aditya Sabale, Ketan Sot Pdeu Dept. of Computer Science and Engineering Gandhinagar India

ISBN: (纸本)9789380544519

A smart shopping trolley incorporates technology to improve the shopping experience by providing features such as automatic checkout, item scanning, tailored suggestions, and budget tracking, boosting efficiency and convenience while optimizing purchases. This paper presents a prototype for an intelligent trolley system that follows a human being and does automatic billing. Human followers leverage HC05 Bluetooth, HMC5883L Compass, and GPS Neo 6M. Automatic billing leverages RFID tags for the unique identification of the product. The absence of GPS sensors led to the adoption of a sonar sensor for human followers. The article unfolds innovative solutions and insights gained from navigating IoT complexities, costs, and environmental factors. The paper envisions a future where machine learning and AI optimize the shopping journey, contributing to the continuous evolution of the retail narrative. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Human Following Robot Obstacle Avoidance RFID Sensor Smart IoT System

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Forensic science: AI-Powered Image and Audio Analysis 5

Forensic Science: AI-Powered Image and Audio Analysis

引用

5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Renukadevi, P. John, Sincy Shivani, N. Jain University Dept. of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798331504403

Forensic science demands the precise application of advanced scientific principles and procedures to investigate crimes and ensure justice. This process involves the analysis of vast and complex data. The research explores the potential of modern science and technologies, particularly Artificial Intelligence (AI), to develop innovative techniques across various branches of forensic science. It provides a comprehensive examination of AI applications in forensic fields, focusing on image and audio analysis to identify instruments used in crimes and determine causes of death. By integrating AI, the research aims to enhance the accuracy and efficiency of forensic investigations while maintaining ethical standards. The paper also discusses the difficulties with AI in forensic science, highlighting the need for open and moral AI systems. It highlights that forensic errors leading to wrongful convictions often result from factors such as incompetence, spam, weak scientific foundations, or organizational deficiencies, rather than blunders made by forensic scientists. These issues highlight the importance of addressing the root causes of forensic errors to improve the reliability of forensic practices. The study also delves into the specific challenges AI encounters, such as data quality, interpretability of AI models, and the unification of AI into current forensic procedures. By tackling these challenges, the research aims to ensure that AI applications in forensic science are effective and trustworthy. Overall, this work highlights the critical role of AI in advancing forensic science and the importance of addressing the underlying issues that contribute to forensic errors, ultimately striving for a more reliable and just forensic process © 2024 IEEE.

关键词： Digital forensics

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Optimizing Human Activity Recognition for Precision in Yoga Practice Analysis 8

Optimizing Human Activity Recognition for Precision in Yoga ...

引用

8th IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2024

作者： Salian, Supriya Preethi Salian, K. Rodrigues, Maria Viola Ritesh Muhammed Elham, P.N. Mannan, Mohammed Abdul St. Joseph Engineering College Vamanjoor Dept. of Computer Science and Engineering Mangaluru India Dept. of Information Science and Engineering Udupi India

ISBN: (纸本)9798350350593

The proposed system on enhancing human activity recognition in yoga presents an innovative solution using advanced technologies to accurately and quickly analyze data of yoga poses. Through meticulous data collection and preprocessing, including noise removal, normalization, and handling missing data, the system ensures a clean and standardized dataset. Pose estimation algorithms contribute to accurately mapping the body's posture, extracting essential features like joint angles and body orientation. The features form the basis for a powerful machine learning model, trained on a labelled dataset and employing neural networks, enabling the system to recognize yoga poses with remarkable precision. The study embraces an iterative enhancement process, continuously refining the model based on feedback and performance metrics, ensuring ongoing improvements in accuracy. Ultimately, the proposed system represents a cutting-edge solution for advancing human activity recognition in yoga, providing practitioners with real- time feedback and guidance, fostering improved techniques, and enhancing the overall yoga experience. © 2024 IEEE.

关键词： Mapping

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A Hybrid Model for Deciphering Doctors' Handwriting Notes Recognition 6

A Hybrid Model for Deciphering Doctors' Handwriting Notes Re...

引用

6th IEEE International Conference on Artificial Intelligence in engineering and Technology, IICAIET 2024

作者： Khanal, Santosh Bista, Rabindra Kathmandu University Dept. of Computer Science and Engineering Kavre Nepal

ISBN: (纸本)9798350389692

Handwritten Text image Recognition (HTR) in the medical profession has become the major challenge due to the complexity of doctors' handwriting styles and the critical need for precise and efficient text recognition. This study proposes an innovative approach that combines the power of Bidirectional Long Short-Term Memory networks (BLSTM) and Convolutional Neural Networks (CNN) to address these challenges effectively. The proposed model harnesses the bidirectional capabilities of BLSTMs to capture contextual dependencies within doctors' handwritten notes, enabling it to understand and interpret handwriting more accurately. Additionally, CNNs are employed for feature extraction, enabling the model to recognize salient patterns and representations within handwritten text images. This paper presents comprehensive experiments conducted on a diverse dataset of doctors' handwritten notes, demonstrating the model's superior performance compared to conventional approaches and outperforms the existing work in terms of accuracy. Two different crucial metric word error rate and character error rate are accessed through the combination of BLSTM and CNN that yields state-of-the-art accuracy, robustness to variations in handwriting styles, and remarkable adaptability across various medical documents in the context of Nepal. © 2024 IEEE.

关键词： Convolutional neural networks

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Analytical Survey of Domain Effective Sentiment Lexicon for Aspect-Centric Opinion Analysis 8

Analytical Survey of Domain Effective Sentiment Lexicon for ...

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

作者： Purbey, Lal Babu Lakhwani, Kamlesh Jecrc University Dept. Computer Science of Engineering Jaipur India

ISBN: (纸本)9798350391770

Aspect-level sentiment analysis is a modern technology that enables people to share their views or emotions with products, services, or topics based on their aspects. Aspect-level sentiment analysis focuses on aspect extraction, which considers aspects from user reviews. Various methods and approaches have been employed for aspect extraction. Although these methods show better performance and attempt to overcome various challenges, many unsolved problems still need to be solved, such as sentimental ambiguity, opinion misprediction, a weak sentiment lexicon, and implicit sentiment detection. Numerous sentiment lexicons have been employed for word polarity extraction. Dictionaries also play an important role in sentiment classification. There are various dictionaries, but it has been found that issues such as one dictionary might not work properly for all domains. This study analyzes various existing sentiment lexicons employed for domain-specific sentiment analysis. Various approaches have been employed to create a domain-dependent sentiment lexicon and its effect on aspect-level sentiment analyses. © 2024 IEEE.

关键词： Aspect Extraction Aspect level sentiment analysis Domain dependent dictionaries Sentiment Analysis Sentiment Lexicon

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