Security and Privacy in New Computing Environments
Description
This book constitutes the refereed proceedings of the 6th International Conference on Security and Privacy in New Computing Environments, SPNCE 2023, held in Guangzhou, China, during November 25-26, 2023.
The 29 full papers were selected from 75 submissions and are grouped in these thematical parts: IoT, network security and privacy challenges; multi-party privacy preserving neural networks; security and privacy steganography and forensics.
More details
Other editions
Additional editions
Content
.- IoT, Network Security and Privacy Challenges .
.- HybridFL: Hybrid approach toward privacy-preserving Federated Learning.
.- The Design of a Multi-application micro-operating system platform in the context of big data.
.- Consortium Blockchain Storage Optimization Based on Fountain Codes.
.- An Incentive Mechanism and An Offline Trajectory Publishing Algorithm Considering Sensing Area Coverage Maximization and Participant Privacy Level.
.- Research on Face Recognition System Based on RLWE Homomorphic Encryption.
.- Feedback Feed-forward Iterative Learning Control for Non-affine Nonlinear discrete-time Systems with Varying Trail Lengths.
.- Open-Closed-Loop Iterative Learning Control Based on Differential Evolution Algorithm for Nonlinear System.
.- Overview of Vehicle Edge Computing and Its Security.
.- Multi-party Privacy Preserving Neural Networks .
.- ConFlow: Contrast Network Flow Improving Class Imbalanced Learning in Network Intrusion Detection.
.- Anomaly Detection of Unstable Log Data Based on Contrastive Learning.
.- An integration-enhanced ZNN approach for chaotic combined synchronization with external disturbances.
.- A lightweight anomaly detection method for industrial processes based on event correlation behavior.
.- A Novel Polar Code-Based Key Encapsulation Mechanism with Non-Permutation Equivalent Public Key.
.- Two-stage Multi-lingual Speech Emotion Recognition for Multi-lingual Emotional Speech Synthesis.
.- EncoderMU: Machine Unlearning In Contrastive Learning.
.- NoCrypto: A Web Mining Behavior Detection Method Based on RGB Images.
.- Security and PrivacyffSteganography and Forensics .
.- Image copy-move forgery detection in the social media based on a prior density clustering and the point density.
.- Detection of Speech Spoofing Based on Dense Convolutional Network.
.- Speech Emotion Recognition Based on Recurrent Neural Networks with Conformer for Emotional Speech Synthesis.
.- Route Privacy-Preserving Authentication Scheme based on PUF in VANETs.
.- Stable NICE Model-Based Image Generation for Generative Steganography.
.- Computer-generated Image Forensics Based on Vision Transformer with Forensic Feature Pre-processing Module.
.- VoIP steganalysis using shallow multiscale convolution and transformer.
