1 option
Cyber Security, Cryptology, and Machine Learning : 9th International Symposium, CSCML 2025, Be'er Sheva, Israel, December 4–5, 2025, Proceedings / edited by Adi Akavia, Shlomi Dolev, Anna Lysyanskaya, Rami Puzis.
Springer Nature - Springer Computer Science eBooks 2026 English International Available online
View online- Format:
- Book
- Author/Creator:
- Akavia, Adi.
- Series:
- Lecture Notes in Computer Science, 1611-3349 ; 16244
- Language:
- English
- Subjects (All):
- Data protection.
- Application software.
- Computer networks.
- Machine learning.
- Cryptography.
- Data encryption (Computer science).
- Data and Information Security.
- Computer and Information Systems Applications.
- Computer Communication Networks.
- Machine Learning.
- Cryptology.
- Local Subjects:
- Data and Information Security.
- Computer and Information Systems Applications.
- Computer Communication Networks.
- Machine Learning.
- Cryptology.
- Physical Description:
- 1 online resource (631 pages)
- Edition:
- 1st ed. 2026.
- Place of Publication:
- Cham : Springer Nature Switzerland : Imprint: Springer, 2026.
- Summary:
- This volume constitutes the proceedings of 9th International Symposium on Cyber Security, Cryptology, and Machine Learning, CSCML 2025, in Be'er Sheva, Israel, during December 4–5, 2025. The 17 regular papers and 9 short papers presented here were carefully reviewed and selected from 43 submissions. These papers focus on Cyber security design; secure software development methodologies; formal methods, semantics, and verification of secure systems; fault tolerance, reliability, and availability of distributed secure systems; game-theoretic approaches to secure computing; automatic recovery, self-stabilizing, and self-organizing systems; communication, authentication, and identification security; cyber security for mobile systems and the Internet of Things; and much more. .
- Notes:
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 3-032-10759-8
- 9783032107596
- OCLC:
- 1561173115
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.