Influence Through Cyber Capacity Building: Network Analysis of Assistance, Cooperation, and Agreements Among ASEAN Plus Three Countries

Kim, Yu‐Kyung; Go, Myong-Hyun; Lee, Kyung-Ho

doi:10.1007/978-3-031-25659-2_24

Cited by 2 publications

(1 citation statement)

References 11 publications

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“…According to Table 1, Japan shows a strong centrality of the network. Unlike previous studies [38], South Korea reveals low centrality among countries in Northeast Asia. This could be because previous studies had considered the relationship between ICT development and cooperation.…”

Section: Agreement Relationship Of Cybersecuritycontrasting

confidence: 99%

Evaluating Cybersecurity Capacity Building of ASEAN Plus Three through Social Network Analysis

Kim¹,

Go²,

Kim³

et al. 2023

Journal of Internet Technology

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The strategic rivalry between the United States and China is out in full swing in Southeast Asia. As the result, ASEAN is emerging both as a key player as well as a playground for pivotal global and regional actors. South Korea, Japan, and China known as ASEAN Plus Three, have strong economic, political, and technological ties with the region, and have leveraged their cyber capabilities to compete for influence in the region. This study evaluates the relative performances of the Plus Three’ cyber outreach efforts to the region by visualizing the complex web of actors and cyber cooperation and assistance activities with network analysis tools and open-source databases. We quantitatively analyze national cyber security cooperation of ASEAN including South Korea, Japan, and China through capacity building indicators and social network methodology. This study (1) analyzes cybersecurity cooperation in ASEAN Plus Three, (2) explores factors that influence cooperation, and (3) lays out a quantitative basis for establishing national information policy and cybersecurity strategy. We find that the Plus Three, despite the outward similarity in their respective regional strategies, are a study of contrasts, with one of them emerging as an influential yet silent power in the regional cyber diplomacy domain.

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Section: Agreement Relationship Of Cybersecuritycontrasting

confidence: 99%

Evaluating Cybersecurity Capacity Building of ASEAN Plus Three through Social Network Analysis

Kim¹,

Go²,

Kim³

et al. 2023

Journal of Internet Technology

View full text Add to dashboard Cite

show abstract

DecentralDC: Assessing data contribution under decentralized sharing and exchange blockchain

Ke,

Liu,

Wang

et al. 2024

PLoS ONE

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The issue of data quality has emerged as a critical concern, as low-quality data can impede data sharing, diminish intrinsic value, and result in economic losses. Current research on data quality assessment primarily focuses on four dimensions: intrinsic, contextual, presentational, and accessibility quality, with intrinsic and presentational quality mainly centered on data content, and contextual quality reflecting data usage scenarios. However, existing approaches lack consideration for the behavior of data within specific application scenarios, which encompasses the degree of participation and support of data within a given scenario, offering valuable insights for optimizing resource deployment and business processes. In response, this paper proposes a data contribution assessment method based on maximal sequential patterns of behavior paradigms (DecentralDC). DecentralDC is composed of three steps: (1) mining the maximal sequential patterns of sharing and exchange behavior paradigms; (2) determining the weights of these paradigms; (3) calculating the contribution of sharing and exchange databases combined with data volume. To validate our approach, two sharing and exchange scenarios of different scales are established. The experimental results in two scenarios validate the effectiveness of our method and demonstrate a significant reduction in cumulative regret and regret rate in data pricing due to the introduction of data contribution. Specifically, compared to the most competitive baseline, the improvements of mean average precision in two scenarios are 6% and 8%. The code and simulation scenarios have been open-sourced and are available at https://github.com/seukgcode/DecentralDC.

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Influence Through Cyber Capacity Building: Network Analysis of Assistance, Cooperation, and Agreements Among ASEAN Plus Three Countries

Cited by 2 publications

References 11 publications

Evaluating Cybersecurity Capacity Building of ASEAN Plus Three through Social Network Analysis

Evaluating Cybersecurity Capacity Building of ASEAN Plus Three through Social Network Analysis

DecentralDC: Assessing data contribution under decentralized sharing and exchange blockchain

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