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Advanced Intelligent Computing Technology and Applications 21st International Conference, ICIC 2025, Ningbo, China, July 26–29, 2025, Proceedings, Part IV /

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This 20-volume set LNCS 15842-15861 constitutes - in conjunction with the 4-volume set LNAI 15862-15865 and the 4-volume set LNBI 15866-15869 - the refereed proceedings of the 21st International Conference on Intelligent Computing, ICIC 2025, held in Ningbo, China, during July 26-29, 2025. The total...

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محفوظ في:
التفاصيل البيبلوغرافية
مؤلف مشترك: SpringerLink (Online service)
مؤلفون آخرون: Huang, De-Shuang (المحرر), Chen, Wei (المحرر), Pan, Yijie (المحرر), Chen, Haiming (المحرر)
التنسيق: الكتروني كتاب الكتروني
اللغة:الإنجليزية
منشور في: Singapore : Springer Nature Singapore : Imprint: Springer, 2025.
الطبعة:1st ed. 2025.
سلاسل:Lecture Notes in Computer Science, 15845
الموضوعات:
Computational intelligence.
Computer networks .
Machine learning.
Application software.
Computational Intelligence.
Computer Communication Networks.
Machine Learning.
Computer and Information Systems Applications.
الوصول للمادة أونلاين:https://doi.org/10.1007/978-981-96-9872-1
الوسوم: إضافة وسم
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جدول المحتويات:
  • -- Information Security
  • DDos Attack Identification Based on Temporal Features.
  • An Intonation-Based Black-Box Generative Adversarial Attack Method for Audio.
  • RanHunter: Advancing Ransomware Detection with Channel Attention and Multi-Head Attention.
  • Cellular-Snooper: A General and Real-Time Mobile Application Fingerprinting Attack in LTE Networks.
  • True or False? Dually Perceiving Relevance of Source Post and Comment Flow for Rumor Detection.
  • Explanation-Inspired Transferable Adversarial Attacks with Layer-Wise Increment Decomposition.
  • CNN-DST-IDS: CNN and D-S Evidence Theory Based Intrusion Detection System.
  • PPAGAN: A Privacy-Preserving Self-Attention GAN Framework for Image Synthesis.
  • ADPF: Adversarial Sample Detection Based on Prediction Feature.
  • MvSMIA: Multi-View Source Membership Inference Attack in Federated Learning.
  • RDP-FedAB: A Federated Learning Framework Balancing Privacy Protection and Model Performance.
  • Transferable Adversarial Attacks via Diffusion-Based Keyword Embedding and Latent Optimization.
  • Optimization of IoUT Systems: A Hierarchical Federated Transfer Learning Approach Based on UAV Computation Offloading.
  • Malicious Encrypted Traffic Detection with Transformer and Dual-Layer Meta-Update Incremental Learning.
  • ElevPatch: An Adversarial Patch Attack Scheme Based on YOLO11 Object Detector.
  • MetaSSL-ETD: Robust Detection of Malicious Encrypted Traffic Based on Semi-Supervised Meta-Learning.
  • A Steganalysis Framework for Enhancing Model Generalization Performance.
  • Frequency-Aware Purification: A Black-box Defense against Backdoor Attacks.
  • Stealthy Backdoors in Vertical Federated Learning.
  • CTI-Shapley: An ATT&CK-Guided Enhanced Shapley Value Mechanism for Benefit Distribution in Cyber Threat Intelligence Sharing.
  • Distributed Cumulative Gradient Backdoor Attack Against Federated Learning.
  • MSIAA: Multi-Scale Inversion Adversarial Attack on Face Recognition.
  • Leveraging Fine-Tuned Large Language Models for Device Fingerprint Extraction in IoT Security.
  • MICD: Deepfake Detection with Masked Identity Consistency Detector.
  • PGAE: A Perturbed Graph Autoencoder Integrating Explicit and Implicit Features for APT Detection.
  • Durability-Optimized Model Poisoning Attack against Federated Learning Systems.
  • Explainable Machine Learning Models for Phishing Website Detection: Enhancing Transparency and Accuracy in Cybersecurity.
  • FRIFL: A Fair and Robust Incentive Mechanism for Heterogeneous Federated Learning.
  • Reversible Data Hiding for 3D Mesh Models in Encrypted Domain Based on Adaptive MSB and Difference Prediction.
  • FedFIP: A Personalized Federated Learning Optimization Method with Differential Privacy Protection.
  • ProAnalyzer: Inferring Network Service's Fuzzing Format with Grey-box Metric.
  • Research on Differential Privacy in Personalized Heterogeneous Federated Learning Based on Fisher Information Matrix.
  • APFedEmb: An Adaptive and Personalized Federated Knowledge Graph Embedding Framework for Link Prediction.
  • Federated Knowledge Collaborative Recommendation System with Privacy Preserving.
  • Towards Reliable Detection of Malicious DNS-over-HTTPS (DoH) Tunneling Traffic under Low-quality Training Data.
  • Ensemble Partitioning: A Defense Mechanism Against Membership Inference Attacks in ML Models.
  • A Trusted Computing Power Network Scheduling Algorithm Based on Federated Learning.
  • Secure Outsourced Matrix Multiplication of Floating Point Numbers.
  • Research on Synthetic Trajectory Data Publication Resisting Location Inference Attacks Based on Differential Privacy.
  • Alias6: An IPv6 Alias Resolution Technology Based on Multiple Fingerprint Features.
  • Update Recovery Attacks on Two-Dimensional Encrypted Databases: Exploiting Volume Pattern Leakage in Range Queries.
  • VulPelican: an LLM and Interactive Static Analysis Tool Based Vulnerability Detection Framework.
  • Energy-aware Task Scheduling Using DVFS and On/Off Switching in Data Center.

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