Muutke küpsiste eelistusi

Information Security and Cryptology: 21st International Conference, Inscrypt 2025, Xi'an, China, October 19-22, 2025, Revised Selected Papers, Part II [Pehme köide]

Edited by , Edited by , Edited by
  • Formaat: Paperback / softback, 488 pages, kõrgus x laius: 235x155 mm, 122 Illustrations, color; 19 Illustrations, black and white
  • Sari: Lecture Notes in Computer Science
  • Ilmumisaeg: 03-Jan-2026
  • Kirjastus: Springer Verlag, Singapore
  • ISBN-10: 9819562023
  • ISBN-13: 9789819562022
  • Pehme köide
  • Hind: 62,74 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Tavahind: 83,65 €
  • Säästad 25%
  • Raamatu kohalejõudmiseks kirjastusest kulub orienteeruvalt 3-4 nädalat
  • Kogus:
  • Lisa ostukorvi
  • Tasuta tarne
  • Tellimisaeg 2-4 nädalat
  • Lisa soovinimekirja
  • Formaat: Paperback / softback, 488 pages, kõrgus x laius: 235x155 mm, 122 Illustrations, color; 19 Illustrations, black and white
  • Sari: Lecture Notes in Computer Science
  • Ilmumisaeg: 03-Jan-2026
  • Kirjastus: Springer Verlag, Singapore
  • ISBN-10: 9819562023
  • ISBN-13: 9789819562022
The three-volume set constitutes revised selected papers of the 21st International Conference on Information Security and Cryptology, Inscrypt 2025, held in Xi'an, China, on October 19, 2025.



The 79 full papers presented in these proceedings were carefully reviewed and selected from 315 submissions. The papers were organized in the following topical sections:   Part I :  Post-Quantum Cryptography; Functional Encryption;  Cryptanalysis and Implementations I; Cryptanalysis and Implementations II.   Part II : Secure Multi-party Computation; Anomaly Detection Methodologies & Models;  Network Security & Traffic Analysis.   Part III : Privacy Preserving/Enhancing Technologies;  AI and Security I; AI and Security II.
.- Secure Multi-party Computation.
.- Quantum-Computation Classical-Communication Commitments
from SZK-Hardness.
.-  Concretely Efficient Constructions for Differentially Private Set
Intersection.
.-  MSFS: Maliciously Secure 3-Party Feature Selection via Mutual
Information.
.- Adaptive Batched K-out-of-N Oblivious Transfers Extension.
.-  Programming Equation Systems of Arithmetization-Oriented Primitives with
Constraints.
.- Anomaly Detection Methodologies & Models.
.-  Anomaly Detection for ADS-B Data Based on KAN-LSTM.
.- Network Intrusion Detection Method Based on Multi-Scale Feature Clustering
and Improved Honey Badger Algorithm.
.-  SAGE: Spatiotemporal Feature Fusion for Anomaly Detection in Multivariate
Time Series.
.-  MoE-CNN with Dynamic Feature Selection and CSAM for Network Anomaly
Detection.
.-  PP-MTAD: Privacy-Preserving and Efficient Multivariate Time Series
Anomaly Detection.
.-  LogWhisperer: Multi-Log Semantic Similarity Analysis based Intelligent
Vehicle Anomaly Detection without Log Template.
.-  An Early Detection of Risky Crowd Dynamics Scheme Based on Motion Entropy
and Scene Semantics.
.-  Enhancing Explainability in X-IDS through Counterfactuals.
.-  What Interferes with the Accurate Detection of Origin Hijacking
Anomalies?.
.-  Network Security & Traffic Analysis.
.-  Verifiable and Privacy-Preserving Deep Packet Inspection for Multiple
Rule Service Providers.
.- Towards Adaptive Network Defense: A Self-Evolving Threat
Detection Framework.
.-  Early Detection of Malicious Traffic based on Graph Modeling and
Spatio-Temporal Attention Approach.
.- Revealing the Frailty of Static Benchmarks: The DyNA-IDS Framework for
Concept Drift Adaptation in Time-Series Network Intrusion Detection.
.-  iSSH: Enabling In-Flight SSH Traffic Inspection without Key Escrow.
.-  Tracing Your Roots: Exploring the Security Issues of Root Certificates in
Android TLS Connections.
.- Exploring the Root Store Usage in TLS-based Applications.
.-  LSDBFT: A Loose DAG-based Asynchronous BFT Consensus Algorithm with Fair
Ordering.
.-  FRanCS: A Fair and Randomized Anonymous Network Circuit Selection
Mechanism with Blockchain.
.- Robust Training of Efficient Traffic Classifier with Noisy Labels.
.-  A Multimodal Asynchronous Federated Learning Approach for Encrypted
Traffic Classification.