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Information Security and Privacy 30th Australasian Conference, ACISP 2025, Wollongong, NSW, Australia, July 14–16, 2025, Proceedings, Part III /

This three-volume set in LNCS constitutes the refereed proceedings of the 30th Australasian Conference on Information Security and Privacy, ACISP 2025, held in Wollongong, NSW, Australia, during July 14–16, 2025. The 54 full papers, 6 short papers and 1 invited paper included in this book were caref...

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Bibliografski detalji
Autor kompanije: SpringerLink (Online service)
Daljnji autori: Susilo, Willy (Urednik), Pieprzyk, Josef (Urednik)
Format: Elektronički e-knjiga
Jezik:engleski
Izdano: Singapore : Springer Nature Singapore : Imprint: Springer, 2025.
Izdanje:1st ed. 2025.
Serija:Lecture Notes in Computer Science, 15660
Teme:
Data protection.
Computer security.
Cryptography.
Data encryption (Computer science).
Data protection > Law and legislation.
Computer networks > Security measures.
Blockchains (Databases).
Data and Information Security.
Principles and Models of Security.
Cryptology.
Privacy.
Mobile and Network Security.
Blockchain.
Online pristup:https://doi.org/10.1007/978-981-96-9101-2
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Sadržaj:
  • -- Privacy Enhancing Technologies.
  • Comparing and Improving Frequency Estimation Perturbation Mechanisms under Local Differential Privacy.
  • Strong Federated Authentication With Password-based Credential Against Identity Server Corruption.
  • Anonymous Credentials with Credential Redaction and Its Application to SSI-based Plug Charge for Shared Vehicles.
  • Direction-Oriented Smooth Sensitivity and Its Application to Genomic Statistical Analysis.
  • Sentence Embedding Generation Method for Differential Privacy Protection. .-KD-IBMRKE-PPFL: A Privacy-Preserving Federated Learning Framework Integrating Knowledge Distillation and Identity-Based Multi-Receiver Key Encapsulation.
  • AI Security and Privacy.
  • Identifying the Truth of Global Model: A Generic Solution to Defend Against Byzantine and Backdoor Attacks in Federated Learning. .-RAGLeak: Membership Inference Attacks on RAG-Based Large Language Models.
  • DeGain: Detecting GAN-based Data Inversion in Collaborative Deep Learning.
  • FRFL: Fair and Robust Federated Learning Incentive Model Based on Game Theory.
  • DPFedSub: A Differentially Private Federated Learning with Randomized Subspace Descend.
  • MG-Det: Deepfake Detection with Multi-Granularity.
  • LPIA: Label Preference Inference Attack against Federated Graph Learning.
  • DARA: Enhancing Vulnerability Alignment via Adaptive Reconstruction and Dual-Level Attention.
  • Zeroth-Order Federated Private Tuning for Pretrained Large Language Models.
  • Understanding the Robustness of Machine-Unlearning Models.
  • System Security.
  • Mitigating the Unprivileged User Namespaces based Privilege Escalation Attacks with Linux Capabilities.
  • SoK: From Systematization to Best Practices in Fuzz Driver Generation.
  • Facial Authentication Security Evaluation against Deepfake Attacks in Mobile Apps.
  • Short Papers.
  • EAPIR: Efficient and Authenticated Private Information Retrieval with Fast Server Processing.
  • Ransomware Encryption Detection: Adaptive File System Analysis Against Evasive Encryption Tactics.
  • Receiver-initiated Updatable Public Key Encryption: Construction, Security and Application.
  • Robust and Privacy-Preserving Dynamic Average Consensus with Individual Weight.
  • Improving RSA Cryptanalysis: Combining Continued Fractions and Coppersmith’s Techniques.
  • Shortest Printable Shellcode Encoding Algorithm Based on Dynamic Bitwidth Selection.
  • Position Paper.
  • Bridging Clone Detection and Industrial Compliance: A Practical Pipeline for Enterprise Codebases.

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