國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Machine learning for authorship attr...

Debbabi, Mourad.

Machine learning for authorship attribution and cyber forensics

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Machine learning for authorship attribution and cyber forensicsby Farkhund Iqbal, Mourad Debbabi, Benjamin C. M. Fung.
作者:	Iqbal, Farkhund.
其他作者:	Debbabi, Mourad.
出版者:	Cham :Springer International Publishing :2020.
面頁冊數:	ix, 158 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Data mining.
電子資源:	https://doi.org/10.1007/978-3-030-61675-5
ISBN:	9783030616755$q(electronic bk.)

Machine learning for authorship attribution and cyber forensics
Iqbal, Farkhund.

Machine learning for authorship attribution and cyber forensics[electronic resource] /by Farkhund Iqbal, Mourad Debbabi, Benjamin C. M. Fung. - Cham :Springer International Publishing :2020. - ix, 158 p. :ill., digital ;24 cm. - International series on computer entertainment and media technology,2364-947X. - International series on computer entertainment and media technology..

1. Cybersecurity And Cybercrime Investigation -- 2. Machine Learning Framework For Messaging Forensics -- 3. Header-Level Investigation And Analyzing Network Information -- 4. Authorship Analysis Approaches -- 5. Authorship Analysis - Writeprint Mining For Authorship Attribution -- 6. Authorship Attribution With Few Training Samples -- 7. Authorship Characterization -- 8. Authorship Verification -- 9. Authorship Attribution Using Customized Associative Classification -- 10. Criminal Information Mining -- 11. Artificial Intelligence And Digital Forensics.

The book first explores the cybersecurity's landscape and the inherent susceptibility of online communication system such as e-mail, chat conversation and social media in cybercrimes. Common sources and resources of digital crimes, their causes and effects together with the emerging threats for society are illustrated in this book. This book not only explores the growing needs of cybersecurity and digital forensics but also investigates relevant technologies and methods to meet the said needs. Knowledge discovery, machine learning and data analytics are explored for collecting cyber-intelligence and forensics evidence on cybercrimes. Online communication documents, which are the main source of cybercrimes are investigated from two perspectives: the crime and the criminal. AI and machine learning methods are applied to detect illegal and criminal activities such as bot distribution, drug trafficking and child pornography. Authorship analysis is applied to identify the potential suspects and their social linguistics characteristics. Deep learning together with frequent pattern mining and link mining techniques are applied to trace the potential collaborators of the identified criminals. Finally, the aim of the book is not only to investigate the crimes and identify the potential suspects but, as well, to collect solid and precise forensics evidence to prosecute the suspects in the court of law.

ISBN: 9783030616755$q(electronic bk.)

Standard No.: 10.1007/978-3-030-61675-5doiSubjects--Topical Terms:

184440
Data mining.

LC Class. No.: QA76.9.D343 / I633 2020

Dewey Class. No.: 006.312

Machine learning for authorship attribution and cyber forensics
LDR:03134nmm a2200349 a 4500 001 591525
003 DE-He213
005 20210322105021.0
006 m d
007 cr nn 008maaau
008 210629s2020 sz s 0 eng d
020 $a 9783030616755$q(electronic bk.)
020 $a 9783030616748$q(paper)
024 7 $a 10.1007/978-3-030-61675-5 $2 doi
035 $a 978-3-030-61675-5
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.D343 $b I633 2020
072 7 $a UNF $2 bicssc
072 7 $a COM021030 $2 bisacsh
072 7 $a UNF $2 thema
072 7 $a UYQE $2 thema
082 0 4 $a 006.312 $2 23
090 $a QA76.9.D343 $b I64 2020
100 1 $a Iqbal, Farkhund. $3 883079
245 1 0 $a Machine learning for authorship attribution and cyber forensics $h [electronic resource] / $c by Farkhund Iqbal, Mourad Debbabi, Benjamin C. M. Fung.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a ix, 158 p. : $b ill., digital ; $c 24 cm.
490 1 $a International series on computer entertainment and media technology, $x 2364-947X
505 0 $a 1. Cybersecurity And Cybercrime Investigation -- 2. Machine Learning Framework For Messaging Forensics -- 3. Header-Level Investigation And Analyzing Network Information -- 4. Authorship Analysis Approaches -- 5. Authorship Analysis - Writeprint Mining For Authorship Attribution -- 6. Authorship Attribution With Few Training Samples -- 7. Authorship Characterization -- 8. Authorship Verification -- 9. Authorship Attribution Using Customized Associative Classification -- 10. Criminal Information Mining -- 11. Artificial Intelligence And Digital Forensics.
520 $a The book first explores the cybersecurity's landscape and the inherent susceptibility of online communication system such as e-mail, chat conversation and social media in cybercrimes. Common sources and resources of digital crimes, their causes and effects together with the emerging threats for society are illustrated in this book. This book not only explores the growing needs of cybersecurity and digital forensics but also investigates relevant technologies and methods to meet the said needs. Knowledge discovery, machine learning and data analytics are explored for collecting cyber-intelligence and forensics evidence on cybercrimes. Online communication documents, which are the main source of cybercrimes are investigated from two perspectives: the crime and the criminal. AI and machine learning methods are applied to detect illegal and criminal activities such as bot distribution, drug trafficking and child pornography. Authorship analysis is applied to identify the potential suspects and their social linguistics characteristics. Deep learning together with frequent pattern mining and link mining techniques are applied to trace the potential collaborators of the identified criminals. Finally, the aim of the book is not only to investigate the crimes and identify the potential suspects but, as well, to collect solid and precise forensics evidence to prosecute the suspects in the court of law.
650 0 $a Data mining. $3 184440
650 0 $a Machine learning. $3 188639
650 0 $a Computer crimes. $3 245152
650 1 4 $a Data Mining and Knowledge Discovery. $3 275288
650 2 4 $a Machine Learning. $3 833608
650 2 4 $a Cybercrime. $3 748274
700 1 $a Debbabi, Mourad. $3 495524
700 1 $a Fung, Benjamin C. M. $3 487245
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a International series on computer entertainment and media technology. $3 729032
856 4 0 $u https://doi.org/10.1007/978-3-030-61675-5
950 $a Mathematics and Statistics (SpringerNature-11649)