國立虎尾科技大學 |

Towards Secure and Trustworthy Cyberspace : = Social Media Analytics on Hakcer Communities.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Towards Secure and Trustworthy Cyberspace :/
其他題名:	Social Media Analytics on Hakcer Communities.
作者:	Li, Weifeng.
面頁冊數:	1 online resource (198 pages)
附註:	Source: Dissertation Abstracts International, Volume: 79-03(E), Section: B.
Contained By:	Dissertation Abstracts International79-03B(E).
標題:	Information technology. -
電子資源:	click for full text (PQDT)
ISBN:	9780355263602

Towards Secure and Trustworthy Cyberspace : = Social Media Analytics on Hakcer Communities.
Li, Weifeng.

Towards Secure and Trustworthy Cyberspace :Social Media Analytics on Hakcer Communities. - 1 online resource (198 pages)

Source: Dissertation Abstracts International, Volume: 79-03(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

Social media analytics is a critical research area spawned by the increasing availability of rich and abundant online user-generated content. So far, social media analytics has had a profound impact on organizational decision making in many aspects, including product and service design, market segmentation, customer relationship management, and more. However, the cybersecurity sector is behind other sectors in benefiting from the business intelligence offered by social media analytics. Given the role of hacker communities in cybercrimes and the prevalence of hacker communities, there is an urgent need for developing hacker social media analytics capable of gathering cyber threat intelligence from hacker communities for exchanging hacking knowledge and tools.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355263602Subjects--Topical Terms:

559429
Information technology.
Index Terms--Genre/Form:

554714
Electronic books.

Towards Secure and Trustworthy Cyberspace : = Social Media Analytics on Hakcer Communities.
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500 $a Source: Dissertation Abstracts International, Volume: 79-03(E), Section: B.
500 $a Adviser: Hsinchun Chen.
502 $a Thesis (Ph.D.) $c The University of Arizona $d 2017.
504 $a Includes bibliographical references
520 $a Social media analytics is a critical research area spawned by the increasing availability of rich and abundant online user-generated content. So far, social media analytics has had a profound impact on organizational decision making in many aspects, including product and service design, market segmentation, customer relationship management, and more. However, the cybersecurity sector is behind other sectors in benefiting from the business intelligence offered by social media analytics. Given the role of hacker communities in cybercrimes and the prevalence of hacker communities, there is an urgent need for developing hacker social media analytics capable of gathering cyber threat intelligence from hacker communities for exchanging hacking knowledge and tools.
520 $a My dissertation addressed two broad research questions: (1) How do we help organizations gain cyber threat intelligence through social media analytics on hacker communities? And (2) how do we advance social media analytics research by developing innovative algorithms and models for hacker communities? Using cyber threat intelligence as a guiding principle, emphasis is placed on the two major components in hacker communities: threat actors and their cybercriminal assets. To these ends, the dissertation is arranged in two parts. The first part of the dissertation focuses on gathering cyber threat intelligence on threat actors. In the first essay, I identify and profile two types of key sellers in hacker communities: malware sellers and stolen data sellers, both of which are responsible for data breach incidents. In the second essay, I develop a method for recovering social interaction networks, which can be further used for detecting major hacker groups, and identifying their specialties and key members. The second part of the dissertation seeks to develop cyber threat intelligence on cybercriminal assets. In the third essay, a novel supervised topic model is proposed to further address the language complexities in hacker communities. In the fourth essay, I propose the development of an innovative emerging topic detection model. Models, frameworks, and design principles developed in this dissertation not only advance social media analytics research, but also broadly contribute to IS security application and design science research.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
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710 2 $a The University of Arizona. $b Management Information Systems. $3 1179532
773 0 $t Dissertation Abstracts International $g 79-03B(E).
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