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024 7 _a10.1007/978-3-030-98795-4
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245 1 0 _aSecurity and Artificial Intelligence
_h[electronic resource] :
_bA Crossdisciplinary Approach /
_cedited by Lejla Batina, Thomas Bäck, Ileana Buhan, Stjepan Picek.
250 _a1st ed. 2022.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2022.
300 _aX, 361 p. 43 illus., 28 illus. in color.
_bonline resource.
336 _atext
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_2rdacontent
337 _acomputer
_bc
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338 _aonline resource
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490 1 _aLecture Notes in Computer Science,
_x1611-3349 ;
_v13049
505 0 _aAI for Cryptography -- Artificial Intelligence for the Design of Symmetric Cryptographic Primitives -- Traditional Machine Learning Methods for Side-Channel Analysis -- Deep Learning on Side-Channel Analysis -- Artificial Neural Networks and Fault Injection Attacks -- Physically Unclonable Functions and AI: Two Decades of Marriage -- AI for Authentication and Privacy -- Privacy-Preserving Machine Learning using Cryptography -- Machine Learning Meets Data Modification: the Potential of Pre-processing for Privacy Enhancement -- AI for Biometric Authentication Systems -- Machine Learning and Deep Learning for Hardware Fingerprinting. - AI for Intrusion Detection -- Intelligent Malware Defenses -- Open-World Network Intrusion Detection -- Security of AI -- Adversarial Machine Learning -- Deep Learning Backdoors. - On Implementation-level Security of Edge-based Machine Learning Models.
520 _aAI has become an emerging technology to assess security and privacy, with many challenges and potential solutions at the algorithm, architecture, and implementation levels. So far, research on AI and security has looked at subproblems in isolation but future solutions will require sharing of experience and best practice in these domains. The editors of this State-of-the-Art Survey invited a cross-disciplinary team of researchers to a Lorentz workshop in 2019 to improve collaboration in these areas. Some contributions were initiated at the event, others were developed since through further invitations, editing, and cross-reviewing. This contributed book contains 14 invited chapters that address side-channel attacks and fault injection, cryptographic primitives, adversarial machine learning, and intrusion detection. The chapters were evaluated based on their significance, technical quality, and relevance to the topics of security and AI, and each submission was reviewed in single-blindmode and revised. .
650 0 _aData protection.
_97245
650 0 _aArtificial intelligence.
_93407
650 0 _aComputer networks .
_931572
650 0 _aSocial sciences
_xData processing.
_983360
650 0 _aApplication software.
_9123628
650 1 4 _aData and Information Security.
_931990
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aComputer Communication Networks.
_9123629
650 2 4 _aComputer Application in Social and Behavioral Sciences.
_931815
650 2 4 _aComputer and Information Systems Applications.
_9123630
700 1 _aBatina, Lejla.
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700 1 _aBäck, Thomas.
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700 1 _aBuhan, Ileana.
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_9123633
700 1 _aPicek, Stjepan.
_eeditor.
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_9123634
710 2 _aSpringerLink (Online service)
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
_z9783030987961
830 0 _aLecture Notes in Computer Science,
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_923263
856 4 0 _uhttps://doi.org/10.1007/978-3-030-98795-4
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