國立高雄大學圖資館 |

Advanced techniques of artificial intelligence in IT security systems

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Advanced techniques of artificial intelligence in IT security systemsby Marcin Korytkowski.
作者:	Korytkowski, Marcin.
出版者:	Cham :Springer Nature Switzerland :2024.
面頁冊數:	v, 91 p. :ill. (chiefly col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Computer security.
電子資源:	https://doi.org/10.1007/978-3-031-53854-4
ISBN:	9783031538544$q(electronic bk.)

Advanced techniques of artificial intelligence in IT security systems
Korytkowski, Marcin.

Advanced techniques of artificial intelligence in IT security systems[electronic resource] /by Marcin Korytkowski. - Cham :Springer Nature Switzerland :2024. - v, 91 p. :ill. (chiefly col.), digital ;24 cm. - Studies in big data,v. 1462197-6511 ;. - Studies in big data ;v.1..

Artificial neural networks -- Initialization of weights values in neural networks -- Convolution neural networks -- Application of artificial intelligence methods in profiling of computer network users -- Profiling users using the random forest algorithm -- Convolutional networks in user profiling -- User profiling using recurrent-convolutional networks -- Detection of network traffic anomalies using OC-NN.

The book explores how modern technologies, including artificial intelligence and neural networks, are being used to enhance cybersecurity. In today's world, the development of the Internet is nothing short of transformative, affecting every aspect of our lives. Ensuring the safety of its users is a paramount concern, and it requires a diverse set of disciplines to address. Researchers from various fields, including IT, mathematics, psychology, and medicine, are collectively working to tackle this interdisciplinary challenge. The significance of this issue has been magnified by the COVID-19 pandemic, which forced many aspects of our lives into the digital realm, from online payments to remote work and education. This shift brought new security challenges, with data privacy and system integrity taking center stage. It delves into the intricacies of Big Data by having to analyze an immense volume of network traffic data that can only be effectively analyzed with specialized tools. Real-time threat detection is critical, and the book sheds light on cutting-edge approaches to achieving this goal. The content of the book covers a broad spectrum of topics related to IT system security, from user and system profiling to preventing data leaks and defending against phishing attacks. Additionally, innovative concepts such as "glial networks" are introduced, offering new ways to interpret knowledge stored in convolutional networks. These solutions are not limited to security alone; they have applications across various domains. The book highlights the advantages of these cutting-edge approaches over existing methods, demonstrating their relevance to large corporations, public institutions, schools, small businesses, and households. In a world where security threats are constantly evolving, this book is a valuable resource for understanding the dynamic landscape of network security and the role of artificial intelligence in safeguarding our digital ecosystems.

ISBN: 9783031538544$q(electronic bk.)

Standard No.: 10.1007/978-3-031-53854-4doiSubjects--Topical Terms:

184416
Computer security.

LC Class. No.: QA76.9.A25

Dewey Class. No.: 005.8

Advanced techniques of artificial intelligence in IT security systems
LDR:03465nmm a2200337 a 4500 001 663295
003 DE-He213
005 20240219095053.0
006 m d
007 cr nn 008maaau
008 241203s2024 sz s 0 eng d
020 $a 9783031538544$q(electronic bk.)
020 $a 9783031538537$q(paper)
024 7 $a 10.1007/978-3-031-53854-4 $2 doi
035 $a 978-3-031-53854-4
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.A25
072 7 $a UN $2 bicssc
072 7 $a COM018000 $2 bisacsh
072 7 $a UN $2 thema
082 0 4 $a 005.8 $2 23
090 $a QA76.9.A25 $b K85 2024
100 1 $a Korytkowski, Marcin. $3 975524
245 1 0 $a Advanced techniques of artificial intelligence in IT security systems $h [electronic resource] / $c by Marcin Korytkowski.
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2024.
300 $a v, 91 p. : $b ill. (chiefly col.), digital ; $c 24 cm.
490 1 $a Studies in big data, $x 2197-6511 ; $v v. 146
505 0 $a Artificial neural networks -- Initialization of weights values in neural networks -- Convolution neural networks -- Application of artificial intelligence methods in profiling of computer network users -- Profiling users using the random forest algorithm -- Convolutional networks in user profiling -- User profiling using recurrent-convolutional networks -- Detection of network traffic anomalies using OC-NN.
520 $a The book explores how modern technologies, including artificial intelligence and neural networks, are being used to enhance cybersecurity. In today's world, the development of the Internet is nothing short of transformative, affecting every aspect of our lives. Ensuring the safety of its users is a paramount concern, and it requires a diverse set of disciplines to address. Researchers from various fields, including IT, mathematics, psychology, and medicine, are collectively working to tackle this interdisciplinary challenge. The significance of this issue has been magnified by the COVID-19 pandemic, which forced many aspects of our lives into the digital realm, from online payments to remote work and education. This shift brought new security challenges, with data privacy and system integrity taking center stage. It delves into the intricacies of Big Data by having to analyze an immense volume of network traffic data that can only be effectively analyzed with specialized tools. Real-time threat detection is critical, and the book sheds light on cutting-edge approaches to achieving this goal. The content of the book covers a broad spectrum of topics related to IT system security, from user and system profiling to preventing data leaks and defending against phishing attacks. Additionally, innovative concepts such as "glial networks" are introduced, offering new ways to interpret knowledge stored in convolutional networks. These solutions are not limited to security alone; they have applications across various domains. The book highlights the advantages of these cutting-edge approaches over existing methods, demonstrating their relevance to large corporations, public institutions, schools, small businesses, and households. In a world where security threats are constantly evolving, this book is a valuable resource for understanding the dynamic landscape of network security and the role of artificial intelligence in safeguarding our digital ecosystems.
650 0 $a Computer security. $3 184416
650 0 $a Artificial intelligence. $3 194058
650 1 4 $a Data Engineering. $3 839346
650 2 4 $a Computational Intelligence. $3 338479
650 2 4 $a Data and Information Security. $3 913130
650 2 4 $a Artificial Intelligence. $3 212515
650 2 4 $a Big Data. $3 760530
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Studies in big data ; $v v.1. $3 675357
856 4 0 $u https://doi.org/10.1007/978-3-031-53854-4
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)