Network and system security : 17th International Conference, NSS 2023, Canterbury, UK, August 14-16, 2023, Proceedings / edited by Shujun Li, Mark Manulis, Atsuko Miyaji.
International Conference on Network and System Security (17th : 2023 : Canterbury, England); Li, Shujun (Writer on computer security), editor.; Manulis, Mark, editor.; Miyaji, Atsuko, Professor, editor.
2023
QA76.9.A25 I58 2023eb
Available Online

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Title Network and system security : 17th International Conference, NSS 2023, Canterbury, UK, August 14-16, 2023, Proceedings / edited by Shujun Li, Mark Manulis, Atsuko Miyaji.
Meeting Name International Conference on Network and System Security (17th : 2023 : Canterbury, England)
ISBN 9783031398285 (electronic bk.)
3031398289 (electronic bk.)
9783031398278
3031398270
DOI https://doi.org/10.1007/978-3-031-39828-5
Published Cham : Springer, 2023.
Language English
Description 1 online resource (xiii, 398 pages) : illustrations (some color).
Item Number 10.1007/978-3-031-39828-5 doi
Call Number QA76.9.A25 I58 2023eb
Dewey Decimal Classification 005.8
Summary This book constitutes the refereed proceedings of the 17th International Conference on Network and System Security, NSS 2023, held in Canterbury, UK, August 14-16, 2023. The 12 full and 9 short papers presented together with 2 invited talks in this book were carefully reviewed and selected from 64 submissions. They focus on Attacks and Malware, Blockchain, Security through Hardware, Machine learning and much more.
Note Includes author index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed August 17, 2023).
Added Author Li, Shujun (Writer on computer security), editor.
Manulis, Mark, editor.
Miyaji, Atsuko, Professor, editor.
Series Lecture notes in computer science ; 13983. 1611-3349
Available in Other Form Print version: 9783031398278
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
Attacks and Malware
Blockchain
Cryptography and Privacy
Machine Learning
Security through Hardware
Security in the Wild.

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