• Neu
Chen / Hu / Wang | Data Security and Privacy Protection | E-Book | www.sack.de
E-Book

E-Book, Englisch, 527 Seiten

Reihe: Computer Science (R0)

Chen / Hu / Wang Data Security and Privacy Protection

Third International Conference, DSPP 2025, Xi'an, China, October 16–18, 2025, Proceedings, Part I
Erscheinungsjahr 2025
ISBN: 978-981-953182-0
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark

Third International Conference, DSPP 2025, Xi'an, China, October 16–18, 2025, Proceedings, Part I

E-Book, Englisch, 527 Seiten

Reihe: Computer Science (R0)

ISBN: 978-981-953182-0
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark



This book constitutes the proceedings of the 3rd International Conference on Data Security and Privacy Protection, DSPP 2025, held in Xi'an, China, during October 16–18, 2025.

The 36 full papers and 11 short papers presented in these two volumes were carefully reviewed and selected from 105 submissions.

The papers are organized in the following topical sections:

Part I:AI and System Security; Blockchain and Related Technologies; Privacy Preserving/Enhancing Technologies; Cryptographic Primitives; Privacy-Aware Federated Learning; AI-based Security Applications and Technologies.

Part II: AI-based Security Applications and Technologies; Cryptographic Protocols Design and Analysis; Model Security and Copyright Protection.

Chen / Hu / Wang Data Security and Privacy Protection jetzt bestellen!

Zielgruppe


Research

Weitere Infos & Material


.- AI and System Security.

.- Boosting Transferability of Adversarial Attacks On Vision Transformer .

.- DMD: Boosting Adversarial Transferability via Dynamic Momentum
Decay.

.- Ghosts in DBMS: Revealing the Security Impacts of Silent Fixes.

.- PerTrajTree-DP: A Personalized Privacy-Preserving Trajectory
Publishing Framework for Trustworthy AI Systems.

.- A Code Vulnerability Detection Method Integrating Pre-trained Model
and Graph Neural Network.

.- Blockchain and Related Technologies.

.- Covert Channels in Bitcoin: Concealing Senders via Transaction
Behavior Mimicry.

.- Hash Time-Locked Contract Scheme Based on Enclave-Based Agent
and Stealth Addresses.

.- Smart Contract Ponzi Detection via Contract Transaction Graph.

.- Evading AI-Based Detectors: A Hybrid Covert Communication Method
Based on Ethereum Transaction Amount and Address.

.- Hierarchical Byzantine Consensus for Election Security.

.- Towards Blockchain-Enabled Cybersecurity Risk Assessment for
Cyber-ship Systems.

.- Spectrum Resources Privacy-preserving Allocation and Certificate
Management Technology based on blockchain.

.- A Blockchain-Based Framework for UAVs in an Asynchronous Network
Environment.

.- BCDAC: Efficient Blockchain-based Cross Domain Access Control Scheme.

.- Privacy Preserving/Enhancing Technologies.

.- An Efficient Private Signaling with Function Secret Sharing.

.- Secure and Efficient Multi-Dimensional Task Matching in Spatial
Crowdsourcing.

.- PB-TPR: A Smart Grid Privacy Protection Framework for Secure Data
Sharing and Efficient Aggregation.

.- Efficient Ranking, Order Statistics, and Sorting under (2, 2)-Threshold
Paillier.

.- Personalized Secure Anonymous Traceability Mechanism with
Pseudo-Random Hopping of Dynamic ID.

.- A Fully Homomorphic Encryption-Based KNN Classification Scheme
for Electric Vehicles Data.

.- A High-Precision and Scalable Location Privacy Query System Based
on FHE.

.- Cryptographic Primitives.

.- Secure Non-Interactive Decision Tree Evaluation via Fully
Homomorphic Encryption.

.- Strong Designated-Verifier zk-SNARKs.

.- Short Lattice-Based Linearly Homomorphic Signatures in the Standard
Model.

.- Kleptographic Fountain- Leakage via a Binary Erasure Channel .

.- Efficient Implementation of NTRU-based Key Encapsulation
Mechanism on Embedded Platform.

.- An Efficient Designated-Server Public-Key Encryption Scheme with
Keyword Search based on Lattices.

.- Privacy-Aware Federated Learning.

.- Personalized Federated Learning with Adaptive Weight Clustering.

.- FedVoD: A Robust Federated Learning Defense Strategy in Hybrid
Byzantine Attacks.

.- A Lightweight Data Leakage Defense Mechanism for Federated
Learning based on Stochastic Gradient Masking.

.- PHV-FL:A Personalized Hierarchical Verifiable Federated Learning
Scheme for Maritime Target Detection.

.- AI-based Security Applications and Technologies.

.- Chaos: Robust Spatio-Temporal Fusion for Generalizable APT
Provenance Tracing.



Ihre Fragen, Wünsche oder Anmerkungen
Vorname*
Nachname*
Ihre E-Mail-Adresse*
Kundennr.
Ihre Nachricht*
Lediglich mit * gekennzeichnete Felder sind Pflichtfelder.
Wenn Sie die im Kontaktformular eingegebenen Daten durch Klick auf den nachfolgenden Button übersenden, erklären Sie sich damit einverstanden, dass wir Ihr Angaben für die Beantwortung Ihrer Anfrage verwenden. Selbstverständlich werden Ihre Daten vertraulich behandelt und nicht an Dritte weitergegeben. Sie können der Verwendung Ihrer Daten jederzeit widersprechen. Das Datenhandling bei Sack Fachmedien erklären wir Ihnen in unserer Datenschutzerklärung.