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Silicon Valley Cybersecurity Conference : Second Conference, SVCC 2021, San Jose, CA, USA, December 2-3, 2021, Revised Selected Papers / edited by Sang-Yoon Chang, Luis Bathen, Fabio Di Troia, Thomas H. Austin, Alex J. Nelson.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Communications in computer and information science 1865-0937 ; 1536
- Communications in Computer and Information Science, 1865-0937 ; 1536
- Language:
- English
- Subjects (All):
- Data protection.
- Computer engineering.
- Computer networks.
- Education-Data processing.
- Social sciences-Data processing.
- Machine learning.
- Data and Information Security.
- Computer Engineering and Networks.
- Computers and Education.
- Computer Application in Social and Behavioral Sciences.
- Machine Learning.
- Local Subjects:
- Data and Information Security.
- Computer Engineering and Networks.
- Computers and Education.
- Computer Application in Social and Behavioral Sciences.
- Machine Learning.
- Physical Description:
- 1 online resource (XII, 155 pages) : 31 illustrations, 19 illustrations in color.
- Edition:
- 1st ed. 2022.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2022.
- System Details:
- text file PDF
- Summary:
- This book constitutes selected and revised papers from the Second Silicon Valley Cybersecurity Conference, held in San Jose, USA, in December 2021. Due to the COVID-19 pandemic the conference was held in a virtual format. The 9 full papers and one shoprt paper presented in this volume were thoroughly reviewed and selected from 15 submissions. They present most recent research on dependability, reliability, and security to address cyber-attacks, vulnerabilities, faults, and errors in networks and systems. Chapters 1, 4, 5, 6, and 8-10 are published open access under a CC BY license (Creative Commons Attribution 4.0 International License).
- Contents:
- Machine Learning for Security
- Encryption
- Miscellaneous Security.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-96057-5
- 9783030960575
- Access Restriction:
- Restricted for use by site license.
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