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Wang, Meng, Chow, Joe H., Hao, Yingshuai, Zhang, Shuai, Li, Wenting, Wang, Ren, Gao, Pengzhi, Lackner, Christopher, Farantatos, Evangelos, Patel, Mahendra.  2019.  A Low-Rank Framework of PMU Data Recovery and Event Identification. 2019 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA). :1–9.

The large amounts of synchrophasor data obtained by Phasor Measurement Units (PMUs) provide dynamic visibility into power systems. Extracting reliable information from the data can enhance power system situational awareness. The data quality often suffers from data losses, bad data, and cyber data attacks. Data privacy is also an increasing concern. In this paper, we discuss our recently proposed framework of data recovery, error correction, data privacy enhancement, and event identification methods by exploiting the intrinsic low-dimensional structures in the high-dimensional spatial-temporal blocks of PMU data. Our data-driven approaches are computationally efficient with provable analytical guarantees. The data recovery method can recover the ground-truth data even if simultaneous and consecutive data losses and errors happen across all PMU channels for some time. We can identify PMU channels that are under false data injection attacks by locating abnormal dynamics in the data. The data recovery method for the operator can extract the information accurately by collectively processing the privacy-preserving data from many PMUs. A cyber intruder with access to partial measurements cannot recover the data correctly even using the same approach. A real-time event identification method is also proposed, based on the new idea of characterizing an event by the low-dimensional subspace spanned by the dominant singular vectors of the data matrix.

Li, Wenting, Sforzin, Alessandro, Fedorov, Sergey, Karame, Ghassan O..  2017.  Towards Scalable and Private Industrial Blockchains. Proceedings of the ACM Workshop on Blockchain, Cryptocurrencies and Contracts. :9–14.

The blockchain emerges as an innovative tool that has the potential to positively impact the way we design a number of online applications today. In many ways, the blockchain technology is, however, still not mature enough to cater for industrial standards. Namely, existing Byzantine tolerant permission-based blockchain deployments can only scale to a limited number of nodes. These systems typically require that all transactions (and their order of execution) are publicly available to all nodes in the system, which comes at odds with common data sharing practices in the industry, and prevents a centralized regulator from overseeing the full blockchain system. In this paper, we propose a novel blockchain architecture devised specifically to meet industrial standards. Our proposal leverages the notion of satellite chains that can privately run different consensus protocols in parallel - thereby considerably boosting the scalability premises of the system. Our solution also accounts for a hands-off regulator that oversees the entire network, enforces specific policies by means of smart contracts, etc. We implemented our solution and integrated it with Hyperledger Fabric v0.6.