Jo / Shin / Merlo Mobile Internet Security

The 8th International Conference, MobiSec 2024, Sapporo, Japan, December 17–19, 2024, Revised Selected Papers
Erscheinungsjahr 2025
ISBN: 978-981-950172-4
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 434 Seiten

Reihe: Computer Science

This book constitutes revised selected papers of the 8th International Conference on Mobile Internet Security, MobiSec 2024, held in Sapporo, Japan, during December 17–19, 2024.

The 28 full papers presented in this volume were carefully reviewed and selected from 93 submissions. 

They were grouped into the following topics: Cryptography; Cyber-Physical Systems / IoT Applications in Smart Environments; Identification and Authentication; Machine Learning-Based Security; Network Design and Security.

Zielgruppe

Research

Autoren/Hrsg.

Jo, Hyungrok

Shin, Seonghan

Merlo, Alessio

You, Ilsun

Inhaltsverzeichnis

.- Cryptography.

.- Analysis of Backdoored (Classic) McEliece in a Multi-User Setting.

.- PRNG-Oriented Side-Channel Security Evaluation for TI-AES.

.- A High-Security Image Steganography System Employing Multiple Edge Detectors.

.- Efficient and Secure CSIDH using Relation Lattices.

.- Utilizing LLM Chatbots for Formal Descriptions of Cryptographic Protocols.

.- A Study on Parallel Tuple Sieve Algorithm.

.- A Blockchain-Based Approach for Secure Email Encryption with Variable ECC Key Lengths 
Selection.

.- The Amplified Boomerang Attack on ChaCha.

.- Bidirectional Proxy Re-Encryption Based on Isogenies.

.- Cyber-Physical Systems / IoT Applications in Smart Environments.

.- Early Heavy Rain Warning System by Cloud based Micrometeorological Data and Geographical 
Conditions with Numerous IoT Sensors.

.- Identification and Authentication.

.- Administration of Environment Aware Deep Learning Based Access Contro.

.- Securing Authentication and Authorization in Computing Continuum.

.- Machine Learning-Based Security.

.- ADL: A Method of Attack Detection with LLM by Assigning Traffic Sequencing in 5G IoT.

.- CAFL: Contrastive Learning and Self-Attention in Federated Learning.

.- A DDoS Attack Detection Method Based on an Ensemble of Small Models for Multi-Layer 
Satellite Networks.

.- A Comprehensive Study of Machine Learning Techniques for Malicious URL Detection in
Cybersecurity.

.- A Color-Based Data Poisoning Backdoor Approach for Misleading Adversarial Privacy
Prediction.

.- FLARE: A Blockchain Strategy for Hierarchical Federated Learning Algorithms.

.- An Enhanced Payload Image Steganography Employing Hybrid Edge Detection Technique and 
MSB Cover Image.

.- Lightweight Object-detection Model on Edge Devices for Safety and Security Applications.

.- Network Design and Security.

.- QoE-Driven Spot Pricing Schemes For Edge User Allocation Across the Distributed Cloud-Edge 
Continuum.

.- A Three-Pronged Approach to Malicious APK: Combining Snort, Wireshark, and Wazuh for 
Advanced Threat Management.

.- Enhancing Security with Virtualization and Real-time Communications for Applications on 
Autonomous Vehicles.

.- Resilient Multi-Path Aggregation Transmission Mechanism for Bandwidth Enhancement.

.- Stepping-Stone Intrusion Detection and its Development Trend.

.- Toward Correctness by Construction for Network Security Configuration.

.- A Novel Framework for Route Recommendation in Cooperative Vehicle Systems: The SHAFA 
Model.

.- Evaluation of a Startup Program Identification for Efficient and Accurate IoT Security 
Investigations.