國立虎尾科技大學 |

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

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Graph Analytics in Cyber Intelligence :/
Reminder of title:	Enhancing Security for Smart Seaports.
Author:	Mayo, Keith E.
Description:	1 online resource (123 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-06, Section: B.
Contained By:	Dissertations Abstracts International85-06B.
Subject:	Engineering. -
Online resource:	click for full text (PQDT)
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. - 1 online resource (123 pages)

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

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

Includes bibliographical references

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. 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.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798381109351Subjects--Topical Terms:

561152
Engineering.
Subjects--Index Terms:

Cyber intelligenceIndex Terms--Genre/Form:

554714
Electronic books.

Graph Analytics in Cyber Intelligence : = Enhancing Security for Smart Seaports.
LDR:04205ntm a22004097 4500 001 1143910
005 20240517105024.5
006 m o d
007 cr mn ---uuuuu
008 250605s2024 xx obm 000 0 eng d
020 $a 9798381109351
035 $a (MiAaPQ)AAI30815603
035 $a AAI30815603
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Mayo, Keith E. $3 1468720
245 1 0 $a Graph Analytics in Cyber Intelligence : $b Enhancing Security for Smart Seaports.
264 0 $c 2024
300 $a 1 online resource (123 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 85-06, Section: B.
500 $a Advisor: Sahlin, John.
502 $a Thesis (D.Engr.)--The George Washington University, 2024.
504 $a Includes bibliographical references
520 $a 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. 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.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Engineering. $3 561152
650 4 $a Ocean engineering. $3 857658
650 4 $a Computer science. $3 573171
650 4 $a Information technology. $3 559429
653 $a Cyber intelligence
653 $a Maritime industry
653 $a Data science
653 $a Potential infrastructure
653 $a Cyber networks
655 7 $a Electronic books. $2 local $3 554714
690 $a 0537
690 $a 0984
690 $a 0489
690 $a 0547
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a The George Washington University. $b Cybersecurity Analytics. $3 1467608
773 0 $t Dissertations Abstracts International $g 85-06B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30815603 $z click for full text (PQDT)