Journal Articles
Permanent URI for this collectionhttp://10.0.100.92:4000/handle/123456789/21
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Item Emerging Blockchain and Reputation Management in Federated Learning: Enhanced Security and Reliability for Internet of Vehicles (IoV)(IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2025-02-02) Mun, H; Han, K; Yeun, H.K; Damiani, E; Puthal, D; Kim, T; Yeun, C.YArtificial intelligence (AI) technologies have been applied to the Internet of Vehicles (IoV) to provide convenience services such as traffic flow prediction. However, concerns regarding privacy and security are on the rise as huge amounts of data are aggregated to form large models (LMs). Although federated learning (FL), which trains and updates a model without sharing the actual datasets, has been intensively researched to prevent privacy breaches, there are still potential security threats like a single point of failure and intentional tampering with malicious data. This is because of the vulnerability of a central curator and a lack of authentication. As participants, they (i.e., vehicles) may unintentionally update low-quality data caused by poor wireless connectivity, unstable availability, and insufficient training datasets. They may also intentionally update unreliable data to carry out poisoning attacks. The divergence among local models, trained on non-independent and identically distributed (non-IID) data, can slow convergence and diminish model accuracy when these models are aggregated. Therefore, it is important to carefully select trustworthy participants. In this paper, we propose a new reliable and secure federated learning for IoV based on decentralized blockchain and reputation management. To cope with a single point of failure, injection of malicious data, and lack of authentication while ensuring privacy and traceability, our scheme combines blockchain and a lightweight digital signature. Moreover, we employ the concept of the reputation of vehicles to select suitable participants with reliability, ultimately improving accuracy. Security analysis results, including comparisons with previous works, prove that the proposed scheme can address security concerns. The results of performance evaluations demonstrate the effectiveness of our proposed schemeItem Past, present, and future of block-chain in finance(Journal of Business Research, 2024-04) Sharma, Gagan Deep; Tiwari, Aviral Kumar; Chopra, Ritika; Dev, DhairyaDiverse businesses are investigating the possibility of redefining their current operational systems in light of the latest blockchain, initially developed for Bitcoin traBitcoinns. This research examines the existing literature on blockchain and its application in the finance sector. This paper provides a systematic literature review of the uses of blockchain in the finance sector. To conduct the review, we performed a boolean search on the Scopus database and obtained 149 records, which we then analyzed bibliometrically using the bibliometrix package in R. The categorization of the existing literature into themes resulted in identifying the following six significant research themes: financial inclusion, sustainable finance, blockchain technology, cryptocurrencies, and artificial intelligence. Following the inductive analysis, we propose a conceptual framework that includes components such as the digital financial revolution, innovation, entrepreneurship, the financial market, sustainable business development, and financial innovation and sustainability. These findings are utilized to suggest future lines of inquiry for this area of study, including the necessity of methodological development and theoretical foundation.