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Graph Analytics in Cyber Intelligenc...

Mayo, Keith E.

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Graph Analytics in Cyber Intelligence: Enhancing Security for Smart Seaports.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Graph Analytics in Cyber Intelligence: Enhancing Security for Smart Seaports./
作者:	Mayo, Keith E.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2024,
面頁冊數:	123 p.
附註:	Source: Dissertations Abstracts International, Volume: 85-06, Section: B.
Contained By:	Dissertations Abstracts International85-06B.
標題:	Engineering. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30815603
ISBN:	9798381109351

Graph Analytics in Cyber Intelligence: Enhancing Security for Smart Seaports.
Mayo, Keith E.

Graph Analytics in Cyber Intelligence: Enhancing Security for Smart Seaports. - Ann Arbor : ProQuest Dissertations & Theses, 2024 - 123 p.

Source: Dissertations Abstracts International, Volume: 85-06, Section: B.

Thesis (D.Engr.)--The George Washington University, 2024.

This item must not be sold to any third party vendors.

As the maritime industry witnesses unparalleled digital advancements, smart seaports-critical nodes in global trade-rely increasingly on intricate cyber networks for operations and security. These sophisticated systems, while essential, render seaports susceptible to multifaceted cyber threats. Existing cyber intelligence methodologies, instrumental in general scenarios, often remain inadequate for the unique challenges intrinsic to smart seaports. This research bridges this gap, emphasizing the pressing need for a specialized, quantitative, and structured cyber intelligence methodology tailored exclusively for these ports.Integrating principles from data science, Intelligence Preparation of the Cyber Environment (IPCE), and graph analytics, this research unveils a holistic view of the cyber threat landscape. Utilizing graph analytics' core tenets, the methodology identifies pivotal nodes and pathways, thereby offering insights into targeted interventions, network efficiency, and potential vulnerabilities. Employing the Power Grid Network as a proxy, this study highlights key nodes and connections, revealing underlying susceptibilities while suggesting preemptive countermeasures. The findings undergo rigorous statistical validations to ensure their relevance and accuracy.Outlined systematically, the research approach encompasses:1. Statistical Assessment of Centrality Measures: This step discerns "highly central" nodes through centrality distributions, facilitating targeted protective actions.2. Graph Topological Analysis: Insights derived from the graph's inherent structure inform strategic interventions, with community clusters hinting at potential localized vulnerabilities.3. Connectivity Analytics Utilization: Through targeted simulations, this phase pinpoints potential infrastructure weak points, guiding resilience enhancement measures.4. Impact Assessment on Centrality Measures: This dynamic evaluation assists in real-time cyber threat monitoring and strategizing.{A0}While the proposed methodology furnishes smart seaports with a nuanced understanding of their cyber milieu and response mechanisms, it also underscores the significance of continuous exploration. Future endeavors may encompass a deeper dive into more intricate datasets, exploring alternative graph analytical techniques, or potentially merging with other emerging cyber intelligence frameworks to enhance the depth and breadth of the insights.In summation, this praxis equips smart seaports with a multifaceted toolkit, granting them a profound understanding of their cyber environment, equipping them with robust response mechanisms, and charting avenues for future research-thereby safeguarding not just the ports but also the broader realms of global commerce and national security.

ISBN: 9798381109351Subjects--Topical Terms:

586835
Engineering.
Subjects--Index Terms:

Cyber intelligence

Graph Analytics in Cyber Intelligence: Enhancing Security for Smart Seaports.
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