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Security and Privacy in Communication Networks: 20th EAI International Conference, SecureComm 2024, Dubai, United Arab Emirates, October 2830, 2024, Proceedings, Part I [Pehme köide]

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Security and Privacy in Communication Networks: 20th EAI International Conference, SecureComm 2024, Dubai, United Arab Emirates, October 2830, 2024, Proceedings, Part ISuurem pilt
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Püsilink: https://www.kriso.ee/db/9783031944444.html
This four-volume set LNISCT 627-630 constitutes the proceedings of the 20th EAI International Conference on Security and Privacy in Communication Networks, SecureComm 2024, held in Dubai, United Arab Emirates during October 28 - 30, 2024.



The 81 full papers were carefully reviewed and selected from 225 submissions. The proceedings focus on



Privacy and Cryptography



AI for cybersecurity and Adversial models



Quantum Computing in Cybersecurity



Network Security



Blockchain and Cryptocurrencies



Fuzzing and IoT security



Malware and Attack Analysis



Web Security



Authentication



Large Language Model for Cybersecurity



Security Assessments
Privacy and Cryptography.- Byzantine Robust Federated Learning for
Unreliable Environments by Random-Matching Verification and Credibility
Table.- PPSA: Polynomial Private Stream Aggregation for Time Series Data
Analysis.- SPADE: Digging into Selective and PArtial DEcryption using
Functional Encryption.- Stuck in the SAND: When Your Neighbor Becomes
Your Enemy.- Optimized Privacy Preserving Clustering with Fully Homomorphic
Encryption.- Noya: An Efficient, Flexible and Secure CNN Inference Model
based on Homomorphic Encryption.- OCE PTree: An Online Communication
Efficient Privacy preserving Decision Tree Evaluation.- An Effective Multiple
Private Set Intersection.- BCPIR: More Efficient Keyword PIR via Block
Building Codewords.- Embedding optimized Steganography Based on Post-quantum
Encryption and BPNN.- AI for cybersecurity and Adversial models.- Enhancing
Runtime Application Self Protection with Unsupervised Deep Learning.- Optical
Lens Attack on Deep Learning Based Monocular Depth Estimation.- RootES: A
Method for Generating Text Adversarial Examples Using Root Embedding Space.-
Boosting GAN Performance: Feature Transformation for Heavy Tailed Malware
Data Generation.- SPC-GAN-Attack: Attacking Slide Puzzle CAPTCHAs by Human
Like Sliding Trajectories Based on Generative Adversarial Network.- Improving
Interpretability: Visual Analysis of Deep Learning Based Multi Channel
Attacks.- Deep Reinforcement Learning from Drifting Network Environments in
Anomaly Detection.- A Comparative Study on Source Code Attribution Using AI:
Datasets, Features, and Techniques.- Quantum Computing in Cybersecurity.-
Harnessing the Power of Quantum Computing for URL Classification: A
Comprehensive Study.- Comprehensive Classification and Analysis of
Cyber Attack Surface on Quantum Key Distribution Networks.- A Secure
Blockchain Network with Quantum Key Encryption and Authentication.