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082 0 4 _a620.00285
_223
100 1 _aKorytkowski, Marcin.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aAdvanced Techniques of Artificial Intelligence in IT Security Systems
_h[electronic resource] /
_cby Marcin Korytkowski.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aV, 91 p. 38 illus., 35 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Big Data,
_x2197-6511 ;
_v146
505 0 _aArtificial 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 _aThe 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.
541 _fUABC ;
_cPerpetuidad
650 0 _aEngineering
_xData processing.
650 0 _aComputational intelligence.
650 0 _aData protection.
650 0 _aArtificial intelligence.
650 0 _aBig data.
650 1 4 _aData Engineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aData and Information Security.
650 2 4 _aArtificial Intelligence.
650 2 4 _aBig Data.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031538537
776 0 8 _iPrinted edition:
_z9783031538551
776 0 8 _iPrinted edition:
_z9783031538568
830 0 _aStudies in Big Data,
_x2197-6511 ;
_v146
856 4 0 _zLibro electrónico
_uhttp://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-3-031-53854-4
912 _aZDB-2-INR
912 _aZDB-2-SXIT
942 _cLIBRO_ELEC
999 _c274227
_d274226