Applied cryptography and network sec...
ACNS (Conference) (2025 :)

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  • Applied cryptography and network security = 23rd International Conference, ACNS 2025, Munich, Germany, June 23-26, 2025 : proceedings.. Part III /
  • Record Type: Electronic resources : Monograph/item
    Title/Author: Applied cryptography and network security/ edited by Marc Fischlin, Veelasha Moonsamy.
    Reminder of title: 23rd International Conference, ACNS 2025, Munich, Germany, June 23-26, 2025 : proceedings.
    remainder title: ACNS 2025
    other author: Fischlin, Marc.
    corporate name: ACNS (Conference)
    Published: Cham :Springer Nature Switzerland : : 2025.,
    Description: xii, 417 p. :ill. (some col.), digital ;24 cm.
    [NT 15003449]: 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.
    Contained By: Springer Nature eBook
    Subject: Data encryption (Computer science) - Congresses. -
    Online resource: https://doi.org/10.1007/978-3-031-95767-3
    ISBN: 9783031957673
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W9518792 電子資源 11.線上閱覽_V 電子書 EB QA76.9.A25 A36 2025 一般使用(Normal) On shelf 0
  • 1 records • Pages 1 •
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