Ubiquitous Security

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

AvGuojun Wang,Kim-Kwang Raymond Choo

Häftad, Engelska, 2023

Del i serien Communications in Computer and Information Science

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Beskrivning

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.

Produktinformation

Utgivningsdatum:2023-02-16
Mått:155 x 235 x 32 mm
Vikt:867 g
Format:Häftad
Språk:Engelska
Serie:Communications in Computer and Information Science
Antal sidor:558
Förlag:Springer Verlag, Singapore
ISBN:9789819902712

Utforska kategorier

Nätverk och kommunikation inom Data och IT
Artificiell intelligens inom Data och IT
Tillämpad datateknik inom Data och IT

Innehållsförteckning

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.