Challenges and Remedies to Privacy and Security in AIGC: Exploring the Potential of Privacy Computing, Blockchain, and Beyond

Artificial Intelligence Generated Content (AIGC) is one of the latest achievements in AI development. The content generated by related applications, such as text, images and audio, has sparked a heated discussion. Various derived AIGC applications are also gradually entering all walks of life, bringing unimaginable impact to people's daily lives. However, the rapid development of such generative tools has also raised concerns about privacy and security issues, and even copyright issues in AIGC. We note that advanced technologies such as blockchain and privacy computing can be combined with AIGC tools, but no work has yet been done to investigate their relevance and prospect in a systematic and detailed way. Therefore it is necessary to investigate how they can be used to protect the privacy and security of data in AIGC by fully exploring the aforementioned technologies. In this paper, we first systematically review the concept, classification and underlying technologies of AIGC. Then, we discuss the privacy and security challenges faced by AIGC from multiple perspectives and purposefully list the countermeasures that currently exist. We hope our survey will help researchers and industry to build a more secure and robust AIGC system.Comment: 43 pages, 10 figure

The scheme of wind-storage combined system capacity configuration based on random fuzzy chance constrained bi-level programming

A random fuzzy chance constrained bilevel programming scheme for distributed wind-storage combined system is proposed. The random fuzzy simulation is used to describe the uncertainty of distributed wind power output. The reliability of randomness and ambiguity is taken as the index to evaluate the capacity allocation scheme of the distributed wind-storage combined system. Considering system power balance, opportunity measurement constraint of static security index and active management (AM) measures, the random fuzzy expectation value of maximum annual profit is set as the upper optimization goal, and the minimum random fuzzy expectation value of the distributed wind power active reduction is set as the lower optimization target. The scheme is constructed by judging whether the static security index of the upper goal satisfies the confidence level of the random fuzzy chance constraint and the coordination of the upper and lower goals. Finally, the random fuzzy simulation, the forward pushback power flow calculation and the genetic algorithm (GA) are applied to solve the model. The simulation result of IEEE 14-bus example shows the effectiveness and superiority of the model and scheme

The scheme of wind-storage combined system capacity configuration based on random fuzzy chance constrained bi-level programming

A random fuzzy chance constrained bilevel programming scheme for distributed wind-storage combined system is proposed. The random fuzzy simulation is used to describe the uncertainty of distributed wind power output. The reliability of randomness and ambiguity is taken as the index to evaluate the capacity allocation scheme of the distributed wind-storage combined system. Considering system power balance, opportunity measurement constraint of static security index and active management (AM) measures, the random fuzzy expectation value of maximum annual profit is set as the upper optimization goal, and the minimum random fuzzy expectation value of the distributed wind power active reduction is set as the lower optimization target. The scheme is constructed by judging whether the static security index of the upper goal satisfies the confidence level of the random fuzzy chance constraint and the coordination of the upper and lower goals. Finally, the random fuzzy simulation, the forward pushback power flow calculation and the genetic algorithm (GA) are applied to solve the model. The simulation result of IEEE 14-bus example shows the effectiveness and superiority of the model and scheme

Effect of transition metal ions on the thermal degradation of chitosan

<p>Chitosan–transition metal compounds with Mn²⁺, Co²⁺, Ni²⁺, Zn²⁺, and Cd²⁺ were obtained containing 0–4.0% weight fraction of metal ions. The microstructure of these compounds was determined, and the effect of the metal ions on the thermal degradation of chitosan in nitrogen was studied. The results showed that the second thermal degradation of chitosan was significantly affected by the metal ion species. The temperature of maximal weight loss rate was dependent on the content of the metal ion, with a higher metallic ion concentration sample presenting a lower temperature, and also the metal ion species, which decreased in the order Cd²⁺ > Ni²⁺ > Mn²⁺ > Co²⁺ > Zn²⁺. However, the weight loss, which decreased with an increasing weight fraction of the metal ion, was not proportional to the initial metal concentration in the compound. The activation energies of the second thermal degradation of the compounds were calculated and compared.</p

DataSheet_1_Epithelial-mesenchymal transition classification of circulating tumor cells predicts clinical outcomes in progressive nasopharyngeal carcinoma.pdf

BackgroundLiquid biopsy facilitates the enrichment and isolation of circulating tumor cells (CTCs) in various human cancers, including nasopharyngeal carcinoma (NPC). Characterizing CTCs allows observation of the evolutionary process of single tumor cells undergoing blood-borne dissemination, such as epithelial-mesenchymal transition. However, the prognostic value of phenotypic classification of CTCs in predicting the clinical outcomes of NPC remains poorly understood.Patients and methodsA total of 92 patients who met the inclusion criteria were enrolled in the present study. The CanPatrol™ CTC technology platform was employed to isolate CTCs, and an RNA in situ hybridization-based system was used for phenotypic classification. Kaplan–Meier survival curves were used for univariate survival analysis, and the log-rank test was performed for between-group comparisons of the survival curves.ResultsCTCs were detected in 88.0% (81/92) of the enrolled patients with NPC. The total CTC number did not vary between the T and N stages or between Epstein–Barr virus DNA-positive and -negative cases. The numbers of total CTCs and epithelial/mesenchymal (E/M) hybrid CTCs decreased significantly at 3 months post concurrent chemoradiotherapy (P=0.008 and P=0.023, respectively), whereas the numbers of epithelial or mesenchymal CTCs did not decrease. E/M hybrid-predominant cases had lower disease-free survival (P=0.043) and distant metastasis-free survival (P=0.046) rates than non-E/M hybrid-predominant cases.ConclusionCTC classification enables a better understanding of the cellular phenotypic alterations responsible for locoregional invasion and distant metastasis in NPC. E/M hybrid-predominant CTC distribution predicts unfavorable clinical outcomes in patients with progressive NPC.</p