Blockchain technology has heralded a new era in digital innovation, revolutionizing our approach to designing and building distributed applications in the digital sphere. Blockchain technology operates as an immutable digital ledger, where each entry representing a digital transaction is indelible and cannot be altered once established. Initially designed as the fundamental framework for cryptocurrencies, blockchain has outgrown its original purpose, demonstrating significant potential in various industries and offering a variety of security and privacy features. Our study provides a thorough and current survey of blockchain applications, security, privacy concepts, primitives, and threat models. It stands out by concentrating on how blockchain technology intersects with emerging fields like IoT, EVs, FinTech, and healthcare systems in a single framework. To provide security and privacy features, blockchain systems employ different foundational notions and primitives while tackling diverse adversarial scenarios with various capabilities and goals. This study presents a fresh examination of the current state of applications, security and privacy notions and primitives, and threat models in blockchain systems. Additionally, this work highlights existing gaps in knowledge and outlines open questions, aiming to stimulate interest in further advancements in the field.
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SmartProvenance: A Distributed, Blockchain Based DataProvenance System
Blockchain technology has evolved from being an immutable ledger of transactions for cryptocurrencies to a programmable interactive environment for building distributed reliable applications. Although the blockchain technology has been used to address various challenges, to our knowledge none of the previous work focused on using Blockchain to develop a secure and immutable scientific data provenance management framework that automatically verifies the provenance records. In this work, we leverage Blockchain as a platform to facilitate trustworthy data provenance collection, verification, and management. The developed system utilizes smart contracts and open provenance model (OPM) to record immutable data trails. We show that our proposed framework can securely capture and validate provenance data that prevents any malicious modification to the captured data as long as the majority of the participants are honest.
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- Award ID(s):
- 1633331
- PAR ID:
- 10073922
- Date Published:
- Journal Name:
- CODASPY '18 Proceedings of the Eighth ACM Conference on Data and Application Security and Privacy
- Page Range / eLocation ID:
- 35 to 42
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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