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Applied Cryptography and Network Security

23rd International Conference, ACNS 2025, Munich, Germany, June 23-26, 2025, Proceedings, Part III

This three-volume set LNCS 15825-15827 constitutes the proceedings of the 23rd International Conference on Applied Cryptography and Network Security, ACNS 2025, held in Munich, Germany, during June 23-26, 2025. The 55 full papers included in these proceedings were carefully reviewed and selected from 241 submissions. The papers cover all technical aspects of applied cryptography, network and computer security and privacy, representing both academic research work as well as developments in industrial and technical frontiers.

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Produktbeschreibung

This three-volume set LNCS 15825-15827 constitutes the proceedings of the 23rd International Conference on Applied Cryptography and Network Security, ACNS 2025, held in Munich, Germany, during June 23-26, 2025. The 55 full papers included in these proceedings were carefully reviewed and selected from 241 submissions. The papers cover all technical aspects of applied cryptography, network and computer security and privacy, representing both academic research work as well as developments in industrial and technical frontiers. 

Inhaltsverzeichnis

Quantum & Post-Quantum: Everlasting Fully Dynamic Group Signatures.- From
ElGamal to Lattice-Based: Enhancing the Helios Voting System with Quantum-Safe
Cryptography.- Post-Quantum Cryptography for Linux File System Integrity.
Biometrics & Authentication: SEBioID: Secure and Effcient Biometric
Identification with Two-Party Computation.- SoK: Continuous User Authentication
Beyond Error Rates: Reviewing General System Properties.- Cancelable Biometrics
based on Cosine Locality Sensitive Hashing and Grouped Inner Product
Transformation for Real-valued Features. Privacy: PARSAN-Mix: Packet-Aware
Routing and Shuffing with Additional Noise for Latency Optimization in Mix
Networks.- ProvDP: Differential Privacy for System Provenance Dataset.- A New
Quadratic Noisy Functional Encryption Scheme and Ist Application for Privacy
Preserving Machine Learning.- FNSA: An Adaptive Privacy Protection Model for
Trajectory Data.- SPPM: A Stackelberg Game-based Personalized Privacy-Preserving
Model in Mobile Crowdsensing Systems. Machine Learning: Homomorphic WiSARDs:
Effcient Weightless Neural Network training over encrypted data.- LaserGuider: A
Laser Based Physical Backdoor Attack against Deep Neural Networks.- Recovering
S-Box Design Structures and Quantifying Distances between S-Boxes using Deep
Learning.- Obfuscation for Deep Neural Networks against Model-based Extraction
Attacks: Taxonomy and Optimization. 

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Produktdetails

Medium: Buch
Format: Kartoniert
Seiten: 432
Sprache: Englisch
Erschienen: Juni 2025
Sonstiges: 978-3-031-95766-6
Maße: 235 x 155 mm
Gewicht: 651 g
ISBN-10: 3031957660
ISBN-13: 9783031957666

Bestell-Nr.: 40951494 
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KNO-SAMMLUNG: Lecture Notes in Computer Science 15827
KNOABBVERMERK: 2025. xii, 408 S. XII, 408 p. 99 illus. 235 mm
KNOSONSTTEXT: 978-3-031-95766-6
KNOMITARBEITER: Herausgegeben:Fischlin, Marc; Moonsamy, Veelasha
Einband: Kartoniert
Sprache: Englisch

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