Cyber-physical systems have been highly integrated into many contemporary infrastructures. As this integration deepens, the importance of protecting these systems from unauthorized access and data corruption increases. Nowadays, cyber-physical systems are not well protected against network attacks. One solution is to improve the security of a system by encrypting the transmitted data. In this paper, we consider the encryption of supervisors of discrete event systems modeled with deterministic finite-state automata. We propose an encryption framework of supervisory control systems based on the matrix notation of automata. The purpose of using matrix notation is to make it suitable for homomorphic encryption schemes over integers, which are emerging in the cryptography area. We calculate the entropy of the matrix notation and find that as the size of a system increases, it gets smaller and approaches zero. Owing to the low entropy of the matrix notation, we propose an algorithm to enhance its entropy. By applying the entropy-enhancing process, the distribution characteristics of entries in matrices or vectors can be hidden to avoid a brute force attack. Correspondingly, we propose an entropy restoration algorithm to ensure that the control action can be transmitted correctly.

Clear cell renal cell carcinoma (ccRCC), the most common malignant subtype of renal cell carcinoma, is characterized by the accumulation of lipid droplets in the cytoplasm. RNASET2 is a protein coding gene with a low expression level in ovarian cancers, but it is overexpressed in poorly differentiated neuroendocrine carcinomas. There is a correlation between RNASET2 upregulation and triglyceride expression levels in human serum but is unknown whether such an association is a factor contributing to lipid accumulation in ccRCC. Herein, we show that RNASET2 expression levels in ccRCC tissues and cell lines are significantly higher than those in both normal adjacent tissues and renal tubular epithelial cells. Furthermore, its upregulation is associated with increases in ccRCC malignancy and declines in patient survival. We also show that an association exists between increases in both cytoplasmic lipid accumulation and HIF‐2α transcription factor upregulation, and increases in both RNASET2 and triglyceride expression levels in ccRCC tissues. In addition, DGAT1 and DGAT2, two key enzymes involved in triglyceride synthesis, are highly expressed in ccRCC tissues. By contrast, RNASET2 knockdown inhibited their expression levels and lowered lipid droplet accumulation, as well as suppressing in vitro cell proliferation, cell invasion, and migration. In conclusion, our data suggest HIF2α upregulates RNASET2 transcription in ccRCC cells, which promotes both the synthesis of triglycerides and ccRCC migration. As such, RNASET2 may have the potential as a biomarker or target for the diagnosis and treatment of ccRCC.

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Fault-freeness is one of the necessary guarantees for healthy and stable operations of discrete event systems. Traditional diagnostic models may fail since sensors may suffer electronic component failures, communication failures, or atmospheric electromagnetic interference. Robust diagnosis problem has attracted more and more attention since it improves reliability of the diagnosis technology. When generating the Petri net reachability graph necessary for constructing a reachability diagnoser, one may face the state explosion problem. As a Petri net gets more complicated, the complexity of its reachability graph also increases exponentially. With the basis reachability graph, a lightweight diagnoser named a basis reachability diagnoser is developed, together with a robust basis reachability diagnoser obtained by dilating the basis reachability graph. Compared with reachability graphs, the advantages of basis reachability graphs in construction complexity are confirmed and the efficiency in robust diagnosability analysis is improved.