Ubiquitous Security Second International Conference, UbiSec 2022, Zhangjiajie, China, December 28–31, 2022, Revised Selected Papers /

This book constitutes the refereed proceedings of the Second International Conference, UbiSec 2022, held in Zhangjiajie, China, during December 28–31, 2022. The 34 full papers and 4 short papers included in this book were carefully reviewed and selected from 98 submissions. They were organized in to...

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Detalles Bibliográficos
Autor Corporativo: SpringerLink (Online service)
Outros autores: Wang, Guojun (Editor), Choo, Kim-Kwang Raymond (Editor), Wu, Jie (Editor), Damiani, Ernesto (Editor)
Formato: Electrónico eBook
Idioma:inglés
Publicado: Singapore : Springer Nature Singapore : Imprint: Springer, 2023.
Edición:1st ed. 2023.
Series:Communications in Computer and Information Science, 1768
Subjects:
Acceso en liña:https://doi.org/10.1007/978-981-99-0272-9
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Table of Contents:
  • Cyberspace Security
  • Support Tool Selection in Digital Forensics Training
  • Listen to the Music: Evaluating the Use of Music in Audio Based Authentication
  • A Hybrid Secure Two-party Protocol for Vertical Federated Learning
  • Detecting Unknown Vulnerabilities in Smart Contracts with Multi-Label lassification Model Using CNN-BiLSTM
  • CATS: A serious game in industry towards stronger cloud security
  • Automated Vulnerability Detection in Source Code Using Quantum Natural Language Processing
  • System Call Processing Using Lightweight NLP for IoT Behavioral Malware Detection
  • Vulnerability Detection with Representation Learning
  • Assessing Vulnerability from Its Description
  • Malware Traffic Classification Based on GAN and BP Neural Networks
  • Source Code Vulnerability Detection using Deep Learning Algorithms for Industrial Applications
  • Detecting Unknown Vulnerabilities in Smart Contracts with Binary Classification Model Using Machine Learning
  • Prototyping the IDS Security Components in the Context of Industry 4.0 - A Textile and Clothing Industry Case Study
  • An Aspect-Based Semi-Supervised Generative Model for Online Review Spam Detection
  • Hierarchical Policies of Subgoals for Safe Deep Reinforcement Learning
  • Improved DeepLabV3+ based Railway track extraction to Enhance Railway Transportation Safety
  • Analysis of Techniques for Detection and Removal of Zero-Day Attacks (ZDA)
  • Android Malware Detection: A Literature Review
  • Threat Modeling in Cloud Computing - A Literature Review
  • A New Signal Packing Algorithm for CAN-FD with Security Consideration
  • An Adversarial Sample Defense Method based on Saliency Information
  • BlockLearning: A Modular Framework for Blockchain-based Vertical Federated Learning
  • Cyberspace Privacy
  • An Interactive Query Differential Privacy Protection Model Based on Big Data Analysis
  • Decentralized Collaborative Filtering Algorithm with Privacy Preserving for Recommendation in Mobile Edge Computing
  • Encryption Proxies in a Confidential Computing Environment
  • FedTA:Locally-Differential Federated Learning with Top-k Mechanism and Adam Optimization
  • Differentially Private Clustering Algorithm for Mixed Data
  • Impact Of Reenactment Programs on Young Generation
  • Sensor Cloud Data Privacy Protection Model Based On Collaborative Deep Learning
  • Cyberspace Anonymity
  • An Improved Cuckoo Search Algorithm and Its Application in Function Optimization
  • Empirical Likelihood for PLSIM with Missing Response Variables and Error-prone Covariates
  • High-speed Anonymous Device Authentication without Asymmetric Cryptography in the Internet-of-Things
  • A-VMD: Adaptive Variational Mode Decomposition Scheme for Noise Reduction in Sensor-Cloud
  • A Thermal-Aware Scheduling Algorithm for Reducing Thermal Risks in DAG-based Applications in Cyber-Physical Systems
  • Short Papers
  • Garbage recognition algorithm based on self-attention mechanism and deep sorting
  • Approaches for Zero Trust Adoption Based Upon Organization Security Level
  • Multi-Mobile Agent Security by Design Itinerary Planning Approach in Wireless Sensor Network
  • On the Variability in the Application and Measurement of Supervised Machine Learning in Cyber Security.