東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Security and artificial intelligence...

Batina, Lejla.

FindBook

Google Book

Amazon

博客來

Security and artificial intelligence = a crossdisciplinary approach /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Security and artificial intelligence/ edited by Lejla Batina ... [et al.].
其他題名:	a crossdisciplinary approach /
其他作者:	Batina, Lejla.
出版者:	Cham :Springer International Publishing : : 2022.,
面頁冊數:	x, 361 p. :ill. (some col.), digital ;24 cm.
內容註:	AI 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.
Contained By:	Springer Nature eBook
標題:	Artificial intelligence. -
電子資源:	https://doi.org/10.1007/978-3-030-98795-4
ISBN:	9783030987954

Security and artificial intelligence = a crossdisciplinary approach /
Security and artificial intelligencea crossdisciplinary approach /[electronic resource] :edited by Lejla Batina ... [et al.]. - Cham :Springer International Publishing :2022. - x, 361 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,130490302-9743 ;. - Lecture notes in computer science ;13049..

AI 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.

AI 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-blind mode and revised.

ISBN: 9783030987954

Standard No.: 10.1007/978-3-030-98795-4doiSubjects--Topical Terms:

516317
Artificial intelligence.

LC Class. No.: QA76.9.A25 / S43 2022

Dewey Class. No.: 006.3

Security and artificial intelligence = a crossdisciplinary approach /
LDR:03051nmm a2200361 a 4500 001 2299947
003 DE-He213
005 20220407190815.0
006 m d
007 cr nn 008maaau
008 230324s2022 sz s 0 eng d
020 $a 9783030987954 $q (electronic bk.)
020 $a 9783030987947 $q (paper)
024 7 $a 10.1007/978-3-030-98795-4 $2 doi
035 $a 978-3-030-98795-4
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.A25 $b S43 2022
072 7 $a UR $2 bicssc
072 7 $a UTN $2 bicssc
072 7 $a COM053000 $2 bisacsh
072 7 $a UR $2 thema
072 7 $a UTN $2 thema
082 0 4 $a 006.3 $2 23
090 $a QA76.9.A25 $b S446 2022
245 0 0 $a Security and artificial intelligence $h [electronic resource] : $b a crossdisciplinary approach / $c edited by Lejla Batina ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a x, 361 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 0302-9743 ; $v 13049
505 0 $a AI 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 $a AI 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-blind mode and revised.
650 0 $a Artificial intelligence. $3 516317
650 0 $a Computer security. $3 540555
650 1 4 $a Data and Information Security. $3 3538510
650 2 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Computer Communication Networks. $3 775497
650 2 4 $a Computer Application in Social and Behavioral Sciences. $3 3538516
650 2 4 $a Computer and Information Systems Applications. $3 3538505
700 1 $a Batina, Lejla. $3 2106877
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Lecture notes in computer science ; $v 13049. $3 3597891
856 4 0 $u https://doi.org/10.1007/978-3-030-98795-4
950 $a Computer Science (SpringerNature-11645)