El. knyga: Artificial Intelligence Security and Privacy: First International Conference on Artificial Intelligence Security and Privacy, AIS&P 2023, Guangzhou, China, December 3-5, 2023, Proceedings, Part I

Fine-grained Searchable Encryption Scheme.- Fine-grained Authorized
Secure Deduplication with Dynamic Policy.- Deep Multi-Image Hiding with
Random Key.- Member Inference Attacks in Federated Contrastive Learning.- A
network traffic anomaly detection method based on shapelet and KNN.- DFaP:
Data Filtering and Purification Against Backdoor Attacks.- A Survey of
Privacy Preserving Subgraph Matching Method.- The Analysis of Schnorr
Multi-Signatures and the Application to AI.- Active Defense against Image
Steganography.- Strict Differentially Private Support Vector Machines with
Dimensionality Reduction.- Converging Blockchain and Deep Learning in UAV
Network Defense Strategy: Ensuring Data Security During Flight.- Towards
Heterogeneous Federated Learning: Analysis, Solutions, and Future
Directions.- From Passive Defense to Proactive Defence: Strategies and
Technologies.- Research on Surface Defect Detection System of Chip Inductors
Based on Machine Vision.- Multimodal fatigue detectionin drivers via
physiological and visual signals.- Protecting Bilateral Privacy in Machine
Learning-as-a-Service: A Differential Privacy Based Defense.- FedCMK: An
Efficient Privacy-Preserving Federated Learning Framework.- An embedded cost
learning framework based on cumulative gradient.- An Assurance Case Practice
of AI-enabled Systems on Maritime Inspection.- Research and Implementation of
EXFAT File System Reconstruction Algorithm Based on Cluster Size Assumption
and Computational Verification.- A Verifiable Dynamic Multi-Secret Sharing
Obfuscation Scheme Applied to Data LakeHouse.- DZIP: A Data
Deduplication-Compatible Enhanced Version of Gzip.- Efficient Wildcard
Searchable Symmetric Encryption with Forward and Backward Security.-
Adversarial Attacks against Object Detection in Remote Sensing Images.-
Hardware Implementation and Optimization of Critical Modules of SM9 Digital
Signature Algorithm.- Post-quantum Dropout-resilient Aggregation for
Federated Learning via Lattice-basedPRF.- Practical and Privacy-Preserving
Decision Tree Evaluation with One Round Communication.- IoT-Inspired
Education 4.0 Framework for Higher Education and Industry Needs.- Multi-agent
Reinforcement Learning Based User-Centric Demand Response with Non-Intrusive
Load Monitoring.- Decision Poisson: From universal gravitation to offline
reinforcement learning.- SSL-ABD:An Adversarial Defense MethodAgainst
Backdoor Attacks in Self-supervised Learning.- Personalized Differential
Privacy in the Shuffle Model.- MKD: Mutual Knowledge Distillation for
Membership Privacy Protection.- Fuzzing Drone Control System Configurations
Based on Quality-Diversity Enhanced Genetic Algorithm.- KEP: Keystroke Evoked
Potential for EEG-based User Authentication.- Verifiable Secure Aggregation
Protocol under Federated Learning.- Electronic voting privacy protection
scheme based on double signature in Consortium Blockchain.- Securing 5G
Positioning via Zero Trust Architecture.- Email Reading Behavior-informed
Machine Learning Model to Predict Phishing Susceptibility.