Artificial Intelligence Security and Privacy (eBook, PDF)

First International Conference on Artificial Intelligence Security and Privacy, AIS&P 2023, Guangzhou, China, December 3-5, 2023, Proceedings, Part II
Redaktion: Vaidya, Jaideep; Li, Jin; Gabbouj, Moncef

• Format: PDF

Produktbeschreibung

This two-volume set LNCS 14509-14510, constitutes the refereed proceedings of the First International Conference on Artificial Intelligence Security and Privacy, AIS&P 2023, held in Guangzhou, China, during December 3-5, 2023.

The 40 regular papers and 23 workshop papers presented in this two-volume set were carefully reviewed and selected from 115 submissions.

Topics of interest include, e.g., attacks and defence on AI systems; adversarial learning; privacy-preserving data mining; differential privacy; trustworthy AI; AI fairness; AI interpretability; cryptography for AI; security applications.

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Produktdetails

• Verlag: Springer Nature Singapore
• Seitenzahl: 279
• Erscheinungstermin: 3. Februar 2024
• Englisch
• ISBN-13: 9789819997886
• Artikelnr.: 69908321

Inhaltsangabe

Application of lattice-based unique ring signature in blockchain transactions.- Rethinking Distribution Alignment for Inter-class Fairness.- Online Learning Behavior Analysis and Achievement Prediction with Explainable Machine Learning.- A Privacy-Preserving Face Recognition Scheme Combining Homomorphic Encryption and Parallel Computing.- A graph-based vertical federation broad learning system.- EPoLORE: Efficient and Privacy Preserved Logistic Regression scheme.- Multi-dimensional Data Aggregation Scheme without a Trusted Third Party in Smart Grid.- Using Micro Videos to Optimize Premiere Software Course Teaching.- The Design and Implementation of Python Knowledge Graph for Programming Teaching.- An Improved Prototypical Network for Endoscopic Grading of Intestinal Metaplasia.- Secure Position-aware Graph Neural Networks for Session-based Recommendation.- Design of a Fast Recognition Method for College Students' Classroom Expression Images Based on Deep Learning.- Research on ALSTM-SVR based Traffic Flow prediction adaptive beacon message Joint control.- An Improved Hybrid Sampling Model for Network Intrusion Detection Based on Data Imbalance.- Using the SGE-CGAM Method to Address Class Imbalance Issues in Network Intrusion Detection.- A Study of Adaptive Algorithm for Dynamic Adjustment of Transmission Power and Contention Window.- Deep learning-based lung nodule segmentation and 3D reconstruction algorithm for CT images.- GridFormer: Grid foreign object detection also requires Transformer.- An Anomaly Detection and Localization Method Based on Feature Fusion and Attention.- Ensemble of Deep Convolutional Network for Citrus Disease Classification using Leaf Images.- PM2.5 Monitoring And Prediction Basing On IOT And RNN Neural Network.- An image zero watermark algorithm based on DINOv2 and multiple cycle transformation.- An image copyright authentication model based on blockchain and digital watermark.