Emerging Information Security and Applications (eBook, PDF)

4th International Conference, EISA 2023, Hangzhou, China, December 6-7, 2023, Proceedings
Redaktion: Shao, Jun; Meng, Weizhi; Katsikas, Sokratis K.

• Format: PDF

Produktbeschreibung

This volume constitutes the proceedings presented at the 4th International Conference on Emerging Information Security and Applications, EISA 2023, held in Hangzhou, China, in December 2023.

The 11 full papers presented in this volume were thoroughly reviewed and selected from the 35 submissions. The topics of the book are related but not limited to cyber intelligence techniques, multimedia security, blockchain and distributed ledger technology, malware and unwanted software, vulnerability analysis and reverse engineering, usable security and privacy, intrusion detection and prevention, authentication and access control, anonymity and privacy, cryptographic protection, digital forensics, cyber physical systems security, adversarial learning, security measurement, security management and policies, hardware and physical security.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Springer Nature Singapore
• Seitenzahl: 185
• Erscheinungstermin: 3. Januar 2024
• Englisch
• ISBN-13: 9789819996148
• Artikelnr.: 69744783

Inhaltsangabe

PtbStolen: Pre-trained Encoder Stealing Through Perturbed Samples.- Towards Efficient Universal Adversarial Attack on Audio Classification Models: A Two-step Method.- Privacy-Preserving Authenticated Federated Learning Scheme for Smart Healthcare System.- A Systematic Method for Constructing ICT Supply Chain Security Requirements.- Pairing Compression on Some Elliptic Curves with Subgroups of Embedding Degree 6 and its Applications to Pairing-based Cryptography.- Enhancing Chinese Named Entity Recognition with Disentangled Expert Knowledge.- Deep Neural Network Model over Encrypted Data.- Privacy Protection Mechanism for Fair Federated Learning.- Chinese Named Entity Recognition within the Electric Power Domain.- Adversarial Sampling Attacks and Defense in DNS Data Exfiltration.- CONNECTION: COvert chaNnel NEtwork attaCk Through bIt-rate mOdulatioN.

Kundenbewertungen

Bewertung schreiben Bewertung schreiben

Information zu Bewertungen

Zur Abgabe einer Bewertung ist die Anmeldung in Ihrem Kundenkonto notwendig. Die Authentizität der Kundenbewertungen wird von uns nicht überprüft.

Bewertung schreiben Bewertung schreiben