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Artificial Intelligence Security and Privacy Second International Conference, AIS&P 2024, Guangzhou, China, December 6-7, 2024, Proceedings /

This book constitutes the refereed proceedings of the Second International Conference on Artificial Intelligence Security and Privacy, AIS&P 2024, held in Guangzhou, China, during December 6-7, 2024. The 14 full papers included in this book were carefully reviewed and selected from 47 submission...

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Detalles Bibliográficos
Autor Corporativo: SpringerLink (Online service)
Outros autores: Zhang, Fangguo (Editor), Lin, Weiwei (Editor), Yan, Hongyang (Editor)
Formato: Electrónico eBook
Idioma:inglés
Publicado: Singapore : Springer Nature Singapore : Imprint: Springer, 2025.
Edición:1st ed. 2025.
Series:Lecture Notes in Computer Science, 15399
Subjects:
Artificial intelligence.
Security systems.
Data protection > Law and legislation.
Cryptography.
Data encryption (Computer science).
Data protection.
Artificial Intelligence.
Security Science and Technology.
Privacy.
Cryptology.
Security Services.
Acceso en liña:https://doi.org/10.1007/978-981-96-1148-5
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Table of Contents:
  • -- BadHAR: Backdoor Attacks in Federated Human Activity Recognition Systems.
  • Fully Automated Generation Mechanism of Rootfs for Specified Operating Systems under Linux.
  • Anti-Side-Channel Attack Mechanisms in Blockchain Payment Channels.
  • F2L: A Lightweight Focus Layer against Backdoor Attack in Federated Learning.
  • Intelligent backpack based on ireless mobile technology.
  • Tourism Industry Upgrading and Public Opinion Prevention Methods Based on BERTopic: A Case Study of Hotel Management.
  • Privacy-Preserving Covert Channels in VoLTE via Inter-Frame Delay Modulation.
  • Enhancing Adversarial Robustness in Object Detection via Multi-Task Learning and Class-Aware Adversarial Training.
  • FedHKD: A Hierarchical Federated Learning Approach Integrating lustering and Knowledge Distillation for Non-IID Data.
  • Application of Ensemble Learning Based on High-Dimensional Features in Financial Big Data.
  • Collaborative Framework for Dynamic Knowledge Updating and Transparent Reasoning with Large Language Models.
  • Zero-Shot Dense Retrieval based on Query Expansion.
  • Lightweight Attention-CycleGAN for Nighttime-Daytime Image ransformation.
  • Generative Image Steganography Based on Latent Space Vector Coding and Diffusion Model.

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