Shah Md. Imtiyaj Uddin’s research while affiliated with Inje University and other places

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Publications (4)


BDAPS: Blockchain Decentralized Approach for Privacy-Preserving and Security in IoT Framework
  • Conference Paper

November 2024

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18 Reads

Md Kamran Hussain Chowdhury

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Shah Md. Imtiyaj Uddin

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The Internet of Things (IoT) has changed the way gadgets interconnect and communicate, resulting in substantial progress in different sectors. However, this interconnectivity also brings significant challenges in terms of privacy and security. To address these challenges, this paper outlines a mechanism through which blockchain can enhance the security of the IoT environment thereby protecting the components of IoT from unauthorized access or security breaches. We also looked at using Blockchain-based Interplanetary File Systems (BIFS) and Hyperledger Fabric to make sure the storage solution is not just large-scale efficient but that it cannot be easily tampered with due to its inherent decentralization. We also heavily leaned on the concepts of Decentralized Identities (DIDs) to protect our IoT ecosystem which can improve data privacy and withstand general adversaries as well.The outcome from the experimental section, namely, the cost and security assessment of the deployed Ethereum-based Decentralized Identities(DIDs) indicate that it is less advantageous to protect IoT environment and data by using Blockchain and distributed storage systems.


Kickstarter: A Secure Automated Crowdfunding Ecosystem Design Framework Using Blockchain & Federated Learning Technology

October 2024

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6 Reads

There has been a rapid development of crowdfunding as the most efficient method of gathering funds for different goals, such as business and commercial projects or ideas and inventions, education enhancement, healthcare institutions, and social needs. However, despite its efficiency, traditional CS present severe issues related to their vulnerabilities, becoming the primary reason for giving hackers and malicious users access to investors' and project initiators' personal and financial data. These problems can be solved in this paper by introducing blockchain and federated learning to enhance the security and decentralization of transactions. As options to the centralized cloud storage, the authors suggest applying decentralized file sharing methods such as Inter-Planetary File System (IPFS).This paper focuses on the model of the blockchain crowdfunding with the help of the proof-of-model framework with the use of the Ethereum Smart Contracts (ESC) for the automated release of the funds on the achievement of milestones that might be observed when designing and launching the efficient blockchain crowdfunding environment.


Integrating Federated Machine Learning in Blockchain Crowdfunding Ecosystem for Increased Security and Transparency

October 2024

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11 Reads

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1 Citation

Crowdfunding has emerged as a popular and effective means of raising funds for various purposes, from business ventures and innovative projects to educational initiatives, healthcare facilities, and social causes. However, traditional crowdfunding systems face significant challenges due to inherent vulnerabilities that commonly lead to data breaches, compromising the personal and financial information of both investors and project creators. Developing and implementing a robust AI model in real-world environments is highly challenging, as many organizations are reluctant to share sensitive information with third parties, such as project creators, due to privacy concerns. Furthermore, creating a generalized prediction model is difficult because crowdfunding participants' data is fragmented across the ecosystem. To address these multifaceted challenges, this paper presents a novel approach that leverages the strengths of blockchain and AI technologies. Blockchain technology will ensure secure data access, while AI-based federated learning will be employed to develop a robust global model for real-time use.


A Secure Smart Contract-Based Crowdfunding Platform Utilizing Blockchain Technology.

June 2024

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22 Reads

Crowdfunding is a great way of financing across industries and is widely used in the entrepreneurial world, education, health, and social causes. However, traditional crowdfunding is not devoid of certain problems such as data breaches and scams related to the undertaken projects. This paper aims to increase the security and transparency of crowdfunding, where blockchain and federated learning can be implemented. Contributor data are given private treatment in operations that involve Secure Multi-Party Computation (SMPC) to preserve anonymity and secure the transaction. Using the concept of smart contact-based crowdfunding in this paper, the author has analyzed the available literature, to gain an understanding of how to unlock the disbursement of funds based on specific milestones assisted by smart contracts on the Ethereum platform. The paper offers a wide framework of reference that points out the best practices and potential flaws of the envisaged blockchain crowdfunding ecosystem used in the paper.

Citations (1)


... Deep learning methods that have shown improved performance in the segmentation and classification of skin lesions are (CNNs). CNNs, as demonstrated by Esteva et al., achieved dermatologist-level accuracy in diagnosing skin cancer [21][22][23]. Attention mechanisms like CBAM and SENet further enhance CNN performance by focusing on key image regions, improving feature representation. Transformer architectures, originally designed for natural language processing, have been adapted for medical imaging, proving effective in tasks like skin lesion diagnosis by capturing long-range dependencies and global context. ...

Reference:

DeepLesionNet: Precise Segmentation and Classification of Skin Lesions via Convolutional Neural Networks
Integrating Federated Machine Learning in Blockchain Crowdfunding Ecosystem for Increased Security and Transparency
  • Citing Conference Paper
  • October 2024