| Title | BlockTrail: A Service for Secure and Transparent Blockchain-Driven Audit Trails |
| Publication Type | Journal Article |
| Year of Publication | 2022 |
| Authors | Ahmad, Ashar, Saad, Muhammad, Al Ghamdi, Mohammed, Nyang, DaeHun, Mohaisen, David |
| Journal | IEEE Systems Journal |
| Volume | 16 |
| Pagination | 1367–1378 |
| ISSN | 1937-9234 |
| Keywords | audit logs, audit trails, bitcoin, blockchain, blockchains, Buildings, clean slate, Collaboration, Databases, Distributed Systems, e-government performance, Human Behavior, human factors, Metrics, policy governance, pubcrawl, resilience, Resiliency, Servers, Throughput, Urban areas |
| Abstract | Audit trails are critical components in enterprise business applications, typically used for storing, tracking, and auditing data. Entities in the audit trail applications have weak trust boundaries, which expose them to various security risks and attacks. To harden the security and develop secure by design applications, blockchain technology has been recently introduced in the audit trails. Blockchains take a consensus-driven clean slate approach to equip audit trails with secure and transparent data processing, without a trusted intermediary. On a downside, blockchains significantly increase the space-time complexity of the audit trails, leading to high storage costs and low transaction throughput. In this article, we introduce BlockTrail, a novel blockchain architecture that fragments the legacy blockchain systems into layers of codependent hierarchies, thereby reducing the space-time complexity and increasing the throughput. BlockTrail is prototyped on the "practical Byzantine fault tolerance" protocol with a custom-built blockchain. Experiments with BlockTrail show that compared to the conventional schemes, BlockTrail is secure and efficient, with low storage footprint. |
| Notes | Conference Name: IEEE Systems Journal |
| DOI | 10.1109/JSYST.2021.3097744 |
| Citation Key | ahmad_blocktrail_2022 |
BlockTrail: A Service for Secure and Transparent Blockchain-Driven Audit Trails