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5th International Conference on Computing and Network Communications, CoCoNet 2023

作者： Bhowmik, Biswajit Dongala, Joshitha Reddy Sudhama, Kruthika K. Antony, Reshma Tresa Girish, K.K. Maharshi Sushrut CAS Lab BRICS Laboratory Department of Computer Science and Engineering National Institute of Technology Karnataka Mangalore Surathkal575025 India

ISBN: (纸本)9789819745395

The assimilation of technology into the financial sector, often referred to as FinTech, has brought about a significant transformation. This shift has not only widened the scope of financial inclusivity but has also fundamentally reshaped the contours of financial solutions delivered. As FinTech solutions continue to empower individuals with greater control over their finances through mobile banking, digital wallets, and advanced data analytics, the security of these innovations becomes paramount. While software security has traditionally received more attention, this paper underscores the significance of hardware security, which serves as the foundational infrastructure for software security measures. It delves into the factors used to evaluate hardware security and outlines various categories of hardware attacks. A case study, focusing on point-of-sale (PoS) systems, exemplifies the importance of hardware security in FinTech. Ultimately, this research contributes to a comprehensive understanding of the evolving FinTech landscape and its implications for both financial inclusion and cybersecurity. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Cybersecurity

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Enhancing Big Data Security Through Anomaly Detection 8

Enhancing Big Data Security Through Anomaly Detection

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

作者： Vakkund, Sharan Kumar, Sachin Rao, Shaifali Anusha Hegde, H. Bhowmik, Biswajit National Institute of Technology Karnataka Ishwarchandra Vidyasagar AIT Lab BRICS Laboratory Department of Computer Science and Engineering Mangalore575025 India

ISBN: (纸本)9798350350593

Securing the massive and fast-moving data streams typical in Big Data environments presents unique challenges that traditional static security measures simply can't handle. To effectively protect these data flows, we need methods that can analyze traffic in real-time and respond swiftly to potential threats. Anomaly detection is one such method, offering an automated way to identify unusual or suspicious activities within Big Data systems. In this study, we explore several widely-used anomaly detection algorithms, evaluating their effectiveness in identifying anomalies within large datasets. Specifically, we will assess these algorithms using the UNSW-NB15 Dataset, aiming to pinpoint which algorithm, or combination of algorithms, is best suited for the demands of Big Data security. © 2024 IEEE.

关键词： Adversarial machine learning

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Spike Sorting and Event Detection in Neuromorphic Computing 10

Spike Sorting and Event Detection in Neuromorphic Computing

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10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Vaishnavi, Vakada G. Sai Sree Bhowmik, Biswajit National Institute of Technology Karnataka Ishwarchandra Vidyasagar Ait Lab Brics Laboratory Department of Computer Science and Engineering Mangalore Surathkal India

ISBN: (纸本)9798350384369

Neuromorphic computing is a cutting-edge field of research that focuses on designing and developing computer systems and hardware architectures inspired by the structure and functioning of the human brain. The main objective of neuromorphic computing is to create computational systems that imitate the parallel processing, learning, and energy efficiency observed in biological neural networks. Two essential tasks in the analysis of brain data from extracellular recordings are spike sorting and event detection. Spike sorting involves identifying and categorizing discrete neural spikes, while event detection focuses on recognizing specific patterns or occurrences within the spiking activity of neuromorphic networks. Typically, each neuron generates spikes with a characteristic shape, and these clusters correspond to the activity of different neurons. Here, the outcome of spike sorting is the identification of which spike corresponds to which neuron. In-depth analysis of the spike sorting and event detection which are two critical processes in interpreting the intricate neuronal activity that underpins brain function are provided. © 2024 IEEE.

关键词： Neurons

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Historical Analysis of Financial Fraud and Its Future

Historical Analysis of Financial Fraud and Its Future

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International Conference on Applied Soft Computing and Communication Networks, ACN 2023

作者： Girish, K.K. Bhowmik, Biswajit Department of Computer Science and Engineering Ishwarchandra Vidyasagar AIT Lab BRICS Laboratory National Institute of Technology Karnataka Surathkal Mangalore575025 India

ISBN: (纸本)9789819720033

As the world is sailing toward a highly advanced digital financial culture with the advent of financial technologies (FinTech), more and more people are now under the shore of financial inclusion. Subsequently, new opportunities are created in the financial sector, making it possible for people who were previously unbanked or underbanked to access financial services. However, the rise in financial fraud and its potential implications are creating a rift in the financial sector, resulting in substantial economic losses across the globe. This paper provides an in-depth comprehension of financial fraud, encompassing its historical perspectives and ramifications. After that, factors contributing to fraudulent behavior are highlighted. In addition, the paper presents a comprehensive framework for fraud classification and accentuates the impacts of financial fraud. Furthermore, the paper underscores the aspects influencing future occurrences of financial fraud, enabling the formulation of proactive strategies to prevent and mitigate it. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Losses

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A survey on cross-user federated recommendation

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science China(Information sciences) 2025年第4期68卷 7-32页

作者： Enyue YANG Yudi XIONG Wei YUAN Weike PAN Qiang YANG Zhong MING College of Computer Science and Software Engineering Shenzhen University School of Electrical Engineering and Computer Science The University of Queensland WeBank AI Lab WeBank Department of Computer Science and Engineering Hong Kong University of Science and Technology College of Big Data and Internet Shenzhen Technology University Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ)

Recommender systems are effective in mitigating information overload, yet the centralized storage of user data raises significant privacy concerns. Cross-user federated recommendation(CUFR) provides a promising distributed paradigm to address these concerns by enabling privacy-preserving recommendations directly on user devices. In this survey, we review and categorize current progress in CUFR, focusing on four key aspects: privacy, security, accuracy, and efficiency. Firstly,we conduct an in-depth privacy analysis, discuss various cases of privacy leakage, and then review recent methods for privacy protection. Secondly, we analyze security concerns and review recent methods for untargeted and targeted *** untargeted attack methods, we categorize them into data poisoning attack methods and parameter poisoning attack methods. For targeted attack methods, we categorize them into user-based methods and item-based methods. Thirdly,we provide an overview of the federated variants of some representative methods, and then review the recent methods for improving accuracy from two categories: data heterogeneity and high-order information. Fourthly, we review recent methods for improving training efficiency from two categories: client sampling and model compression. Finally, we conclude this survey and explore some potential future research topics in CUFR.

关键词： cross-user federated recommendation federated recommendation federated learning recommender systems user privacy

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Optimizing Lender Portfolios: A P2P Lending Recommendation Approach 4

Optimizing Lender Portfolios: A P2P Lending Recommendation A...

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4th IEEE Asian Conference on Innovation in Technology, ASIANCON 2024

作者： Sannapareddy, Varshini Rifah, Umais Anusha Hegde, H. Bhowmik, Biswajit National Institute of Technology Karnataka Ishwarchandra Vidyasagar Ait Lab Brics Laboratory Department of Computer Science and Engineering Surathkal Mangalore575025 India

ISBN: (纸本)9798350354218

The proliferation of peer-to-peer (P2P) lending platforms has ushered in a new era of financial accessibility, but it has also brought to the forefront the growing concern of loan defaults. This paper explores the increasing significance of P2P lending platforms and addresses the critical issue of loan default prediction. The study focuses on the application of machine learning techniques, specifically employing the Random Forest algorithm and logistic regression, to train a predictive model for assessing the likelihood of default within a loan portfolio. The primary objective is to enhance the decision-making process for lenders by recommending optimal loan portfolios based on the predictive insights generated by the model. By leveraging the capabilities of this robust algorithm, the research aims to contribute to the advancement of risk assessment methodologies in P2P lending, ultimately fostering more informed and secure lending practices on these platforms. We trained and compared logistic Reression and random forest models and derived resultant optimal portfolio by considering both the models which is intended to give better results than a single model. © 2024 IEEE.

关键词： Decentralized finance

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Sensor Classifications and Their Applications in IoT Systems

Sensor Classifications and Their Applications in IoT Systems

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2023 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2023

作者： Sajja, Komalsai Bhowmik, Biswajit National Institute of Technology Karnataka Maharshi Vasistha IoT Lab Brics Lab Department of Computer Science and Engineering India

ISBN: (纸本)9798350340129

The Internet of Things (IoT), which connects various systems and devices to create more innovative environments, has completely changed how we interact with technology. Sensors are essential to the success of IoT systems because they are vital in gathering and analyzing real-time data from the physical environment. This paper comprehensively analyses sensor classifications and their applications in IoT systems. It explores the different types of sensors commonly used in IoT, their functionality, and their suitability for various IoT-enabled intelligent applications. This paper also provides valuable insights for IoT designers and researchers in selecting appropriate sensors and developing more efficient and reliable intelligent systems for the future. © 2023 IEEE.

关键词： Internet of things

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Automated Segmentation of COVID-19 Infected Lungs via Modified U-Net Model 15

Automated Segmentation of COVID-19 Infected Lungs via Modifi...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Kumar, Sunil Bhowmik, Biswajit National Institute of Technology Maharshi Patanjali Cps Lab Brics Laboratory Department of Computer Science and Engineering Mangalore Karnataka Surathkal575025 India

ISBN: (纸本)9798350370249

The COVID-19 pandemic has led to significant outbreaks in more than 220 countries worldwide, profoundly impacting the public health and lives. As of February 2024, over 774 million cases have been reported, with more than 7,035,337 deaths recorded. Therefore, there is a significant need for automated image segmentation to serve as clinical decision support. This paper presents a novel automated segmentation framework that dynamically generates distinct and randomized image patches for training using preprocessing techniques and extensive data augmentation. The proposed architecture employs a semantic segmentation approach, ensuring accuracy despite limited data availability. Experimental assessment comprises a visual inspection of the predicted segmentation outcomes. Quantitative evaluation of segmentation includes standards performance metrics such as precision, recall, Dice score, and Intersection over Union (IoU). The results exhibit a remarkable Dice coefficient score of 98.3% and an IoU rate surpassing 96.8%, demonstrating the model's robustness in identifying COVID-19-infected lung regions. © 2024 IEEE.

关键词： Computed Tomography COVID-19 Deep Learning Lung Segmentation U-Net

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FinTech Revolution in Bharat 1

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3rd International Conference on Advanced Computing and Intelligent Technologies, ICACIT 2023

作者： Doddamani, Sachin Shivaji Bhowmik, Biswajit Department of Computer Science and Engineering Ishwarchandra Vidyasagar AIT Lab BRICS Laboratory National Institute of Technology Karnataka Surathkal Mangalore575025 India

ISBN: (数字)9789819719617

ISBN: (纸本)9789819719600

Due to rapid advancements in technology, the financial sector has experienced significant changes in the last few decades. In particular, financial technology (FinTech) has revolutionized the financial services industry, reshaping customer experiences and transforming conventional banking practices. FinTech had a substantial positive impact on the growth of several economies worldwide, and Bharat (India) is at the forefront of this drive. This study explores the advancements of FinTech in Bharat and the role of the public and private sectors in realizing its full potential. The cutting edge technologies like UPI and India Stack and their economic impacts are discussed. The study also focuses on how government initiatives and FinTech disruptors are instrumental in expanding financial inclusion in the country. Furthermore, it delves into the challenges FinTechs face today and provides insights into the evolving solutions to address the key issues. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Finance

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Enhancing Financial Accessibility: A Tailored UPI Payment Application for Divyangjan 10

Enhancing Financial Accessibility: A Tailored UPI Payment Ap...

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10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Bhowmik, Biswajit Sudhama, Kruthika K. Dongala, Joshitha R. Antony, Reshma T. Girish, K.K. National Institute of Technology Karnataka Maharshi Sushrut Cas Lab Brics Laboratory Department of Computer Science and Engineering Mangalore Surathkal575025 India

ISBN: (纸本)9798350384369

The emergence of financial technology (FinTech) has transformed the financial sector, introducing a new era characterized by state-of-the-art technologies that enhance speed, affordability, and accessibility. The proliferation of the internet and smartphones has further accelerated this transformation, fostering greater connectivity and global interaction. Subsequently, these advancements have significantly expanded financial inclusion, ensuring access to financial services for previously under-served populations. While the rise of FinTech has propelled financial inclusion for many, individuals with disabilities have not experienced commensurate improvements in their financial accessibility. As the banking sector increasingly migrates to online platforms, people with disabilities encounter barriers stemming from inaccessible websites, mobile applications, and online banking services. This paper introduces a specialized UPI payment application designed explicitly for individuals with disabilities. The objective is to integrate this underserved demographic into the digital financial landscape, fostering financial inclusion and enhancing access to essential financial services. © 2024 IEEE.

关键词： Decentralized finance

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