Visible to the public Biblio

Filters: Keyword is Data traceability  [Clear All Filters]
2023-08-24
Sun, Jun, Li, Yang, Zhang, Ge, Dong, Liangyu, Yang, Zitao, Wang, Mufeng, Cai, Jiahe.  2022.  Data traceability scheme of industrial control system based on digital watermark. 2022 7th IEEE International Conference on Data Science in Cyberspace (DSC). :322–325.
The fourth industrial revolution has led to the rapid development of industrial control systems. While the large number of industrial system devices connected to the Internet provides convenience for production management, it also exposes industrial control systems to more attack surfaces. Under the influence of multiple attack surfaces, sensitive data leakage has a more serious and time-spanning negative impact on industrial production systems. How to quickly locate the source of information leakage plays a crucial role in reducing the loss from the attack, so there are new requirements for tracing sensitive data in industrial control information systems. In this paper, we propose a digital watermarking traceability scheme for sensitive data in industrial control systems to address the above problems. In this scheme, we enhance the granularity of traceability by classifying sensitive data types of industrial control systems into text, image and video data with differentiated processing, and achieve accurate positioning of data sources by combining technologies such as national secret asymmetric encryption and hash message authentication codes, and mitigate the impact of mainstream watermarking technologies such as obfuscation attacks and copy attacks on sensitive data. It also mitigates the attacks against the watermarking traceability such as obfuscation attacks and copy attacks. At the same time, this scheme designs a data flow watermark monitoring module on the post-node of the data source to monitor the unauthorized sensitive data access behavior caused by other attacks.
2022-09-09
Wei, Yihang.  2020.  Blockchain-based Data Traceability Platform Architecture for Supply Chain Management. :77—85.
{With the rapid development of economic globalization, cooperation between countries, between enterprises, has become a key factor whether country and enterprises can make great economic progress. In these cooperation processes, it is necessary to trace the source of business data or log data for auditing and accountability. However, multi-party enterprises participating in cooperation often do not trust each other, and the separate accounting of the enterprises leads to isolated islands of information, which makes it difficult to trace the entire life cycle of the data. Therefore, there is an urgent need for a mechanism that can establish distributed trustworthiness among multiparty organizations that do not trust each other, and provide a tamper-resistant data storage mechanism to achieve credible traceability of data. This work proposes a data traceability platform architecture design plan for supply chain management based on the multi-disciplinary knowledge and technology of the Fabric Alliance chain architecture, perceptual identification technology, and cryptographic knowledge. At the end of the paper, the characteristics and shortcomings of data traceability of this scheme are evaluated.