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024 7 _a10.1007/978-3-031-57452-8
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050 4 _aJC596-596.2
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072 7 _aCOM060040
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082 0 4 _a005.8
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082 0 4 _a323.448
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245 1 0 _aArtificial Intelligence for Security
_h[electronic resource] :
_bEnhancing Protection in a Changing World /
_cedited by Tuomo Sipola, Janne Alatalo, Monika Wolfmayr, Tero Kokkonen.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXVIII, 366 p. 83 illus., 51 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
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505 0 _aPart I Methodological Fundamentals of Artificial Intelligence -- Chapter.1.Safeguarding the Future of Artificial Intelligence: An AI Blueprint -- Chapter.2.Cybersecurity and the AI Silver Bullet.-Chapter.3.Artificial Intelligence and Differential Privacy - Review of Protection Estimate Models -- Chapter.4.To Know What You Do Not Know: Challenges for Explainable AI for Security and Threat Intelligence -- Chapter.5.Securing the Future: The Role of Knowledge Discovery Frameworks -- Chapter.6.Who Guards the Guardians? On Robustness of Deep Neural Networks.-Part II Artificial Intelligence for Critical Infrastructure Protection -- Chapter.7.Opportunities and Challenges of Using Artificial Intelligence in Securing Cyber-Physical System -- Chapter.8.Artificial Intelligence Working to Secure Small Enterprises -- Chapter.9.On the Cyber Security of Logistics in the Age of Artificial Intelligence.-Chapter.10.Fuzzy Machine Learning for Smart Grid Instability Detection -- Chapter.11.On Protection of the Next-Generation Mobile Networks against Adversarial Examples -- Chapter.12.Designing and Implementing an Interactive Cloud Platform for Teaching Machine Learning with Medical Data -- Part III Artificial Intelligence for Anomaly Detection -- Chapter.13.Machine Learning and Anomaly Detection for an Automated Monitoring of Log Data -- Chapter.14.Detecting Web Application DAST Attacks in Large-scale Event.-Chapter15.Enhancing IoT Intrusion Detection Using Hybrid DAIDS-RNN Mode.
520 _aThis book discusses the use of artificial intelligence (AI) for security purposes. It is divided into three parts: methodological fundamentals of AI, use of AI for critical infrastructure protection and anomaly detection. The first section describes the latest knowledge for creating safe AIs and using them to enhance protection. This book also presents various domains and examples of AI-driven security. The chapters describe potential methods, demonstrate use cases and discuss the challenges of the evolving field. This includes topics such as defensive use of AI to detect threats. It discusses the offensive use of AI to better understand the future threat landscape, the use of AI for automation in critical infrastructure and overall challenges of AI usage for critical tasks. As new threats emerge, the use of AI technologies to protect the world one lives in is topical. New technologies in this space have advanced rapidly, and subsequently, their use in enhancing protection is an evident development. To this effect, this book brings together a group of international researchers and professionals who present their views on how to create security through AI. This book targets postgraduate students, researchers and professionals who want to understand the use of AI for security. Understanding latest advancements in this field will also be useful to those who want to comprehend modern cybersecurity in detail and who want to follow research and latest trends. .
650 0 _aData protection
_xLaw and legislation.
_923450
650 0 _aArtificial intelligence.
_93407
650 0 _aComputer networks
_xSecurity measures.
_93969
650 1 4 _aPrivacy.
_935098
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aMobile and Network Security.
_933624
700 1 _aSipola, Tuomo.
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700 1 _aAlatalo, Janne.
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700 1 _aWolfmayr, Monika.
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_9104610
700 1 _aKokkonen, Tero.
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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856 4 0 _uhttps://doi.org/10.1007/978-3-031-57452-8
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