A Security Analysis of Chinese Robot Supply Chain Based on Open-Source Intelligence

Zhao, Yue; Shen, Yang; Qi, Yuanbo

doi:10.1109/dtpi52967.2021.9540101

Cited by 4 publications

(4 citation statements)

References 9 publications

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“…NLP algorithm: The accuracy and recall rate of existing language models are updated through the use of self-supervised learning cognition of artificial intelligence models such as BERT, LSTM, and CRF, as well as through the construction of large-scale machine learning datasets and manually labelling sample data (Qi, 2020a;Qi et al, 2022;Zhao et al, 2021). As a result, significant heterogeneous text data processing and risk information mining are made visible (Di Marco et al, 2020;Dias & Diniz, 2012;Ding et al, 2021).…”

Section: Methodsmentioning

confidence: 99%

“…Risk identification model: By integrating the learning of several sub-models, this combined model for risk identification not only has the final classification effect but also evaluates various aspects of the online blended learning effect influencing factors for international students (Zhao et al, 2021). The time-series heat model, the Bert language model, the topic word popularity model, the communication models, etc.…”

Section: Methodsmentioning

confidence: 99%

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An Open-Source Intelligence-Driven Analysis of International Students’ Blended Learning in China

Qi¹,

Meng²,

Luo³

et al. 2023

ChnStd

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This paper examines the management of international students' online blended learning based on a comprehensive analysis through open-source intelligence and data mining of associated discourses. This work reconstructs the assessment model of the online blended learning effect for overseas students and rebalances the process of this educational experience, leading to the forecast of China's strategic manoeuvres through the lenses of the newsboy model and game theory. This study concludes with three suggestions: boosting the entire experience via scaled growth, enhancing and preventing resilience, and reaching out to a third party for skills reinforcement.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

An Open-Source Intelligence-Driven Analysis of International Students’ Blended Learning in China

Qi¹,

Meng²,

Luo³

et al. 2023

ChnStd

Self Cite

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show abstract

“…China may be interested in areas where the US has long been chastised by the international community, such as fighting conflicts in the Middle East and Afghanistan. China may employ specialised material to establish a defensive position and rationalise the inevitable conflict by spreading the notion that the US is prone to falling into the Thucydides trap, undermining the moral foundation of the discourse on the US (Wu et al, 2019;Zhao et al, 2021).…”

Section: International Hostile Cultivationmentioning

confidence: 99%

Towards a Long-Term Sino-US Relationship: Implications and Potential Solutions of the Future Chinese Media Strategy for Global Speech Power

Qi¹,

Meng²,

Hua³

2023

OJPS

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This paper focuses on the US-China public opinion confrontation primarily from the standpoint of how China might manage its image-building and global discourse intervention given its ongoing quest for global speech dominance. From the Chinese perspective, there are problems to be solved, including the inconsistency of the content of the world's media, the focus on one ideology over others, the hostile nature of diplomatic responses, and the fragility of the state-owned media platform. In light of China's comparative weakness with the US in the war for hearts and minds, this essay explores China's potential remedies. It concludes that China may aim to increase the weight and proportion of global discourse while also carefully utilising foreign culture and propaganda language. China may simultaneously intensify unfavourable public perceptions of its rivals based on algorithms learned from global platforms, while also working with mainstream media to advance its global coverage and conform to its overall policy objective.

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“…Model evaluation, on the other hand, is a quantitative measure of model performance, which is performed by calculating various performance metrics, such as accuracy, recall, F1 score, the area under the ROC curve, etc. Accuracy tells the proportion of samples correctly predicted by the model to the total samples; recall reflects the ability of the model to detect real threats(Zhao , et al, 2021); and the F1 score is the summed average of accuracy and recall, which can be considered inaccuracy and recalls while giving a single performance metric; and the ROC curve and AUC-ROC can give the overall performance of the model while considering different threshold settings. More attention is paid to recall in early warning models, with the hope of finding as many potential threats as possible, even if this may result in some false positives.…”

mentioning

confidence: 99%

Big Data-Driven Threat Intelligence Analysis and Early Warning Model Construction

Zhang

2023

GHSS

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With the development of big data technology, its application in various fields is becoming increasingly widespread, especially in the field of threat intelligence analysis and early warning. By using the processing power of big data and data mining technology, patterns and laws of threats can be discovered from the massive and multifaceted data, thus realizing effective early warning of threats. However, big data-driven threat intelligence analysis and early warning model construction is a challenging process, which involves various aspects such as understanding and processing of big data, methods, and tools for threat intelligence analysis, design and implementation of early warning models, and validation and evaluation of early warning models. This paper aims to comprehensively describe this process to provide guidance and reference for big data-driven threat intelligence analysis and early warning.

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A Security Analysis of Chinese Robot Supply Chain Based on Open-Source Intelligence

Cited by 4 publications

References 9 publications

An Open-Source Intelligence-Driven Analysis of International Students’ Blended Learning in China

An Open-Source Intelligence-Driven Analysis of International Students’ Blended Learning in China

Towards a Long-Term Sino-US Relationship: Implications and Potential Solutions of the Future Chinese Media Strategy for Global Speech Power

Big Data-Driven Threat Intelligence Analysis and Early Warning Model Construction

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