Hugendubel.info - Die B2B Online-Buchhandlung 

Merkliste
Die Merkliste ist leer.
Bitte warten - die Druckansicht der Seite wird vorbereitet.
Der Druckdialog öffnet sich, sobald die Seite vollständig geladen wurde.
Sollte die Druckvorschau unvollständig sein, bitte schliessen und "Erneut drucken" wählen.

Artificial Intelligence Security and Privacy

First International Conference on Artificial Intelligence Security and Privacy, AIS&P 2023, Guangzhou, China, December 3-5, 2023, Proceedings, Part I
BuchKartoniert, Paperback
595 Seiten
Englisch
Springererschienen am04.02.20241st ed. 2024
This two-volume set LNCS 14509-14510, constitutes the refereed proceedings of the First International Conference on Artificial Intelligence Security and Privacy, AIS&P 2023, held in Guangzhou, China, during December 3-5, 2023.The 40 regular papers and 23 workshop papers presented in this  two-volume set were carefully reviewed and selected from 115 submissions.Topics of interest include, e.g., attacks and defence on AI systems; adversarial learning; privacy-preserving data mining; differential privacy; trustworthy AI; AI fairness; AI interpretability; cryptography for AI; security applications.mehr
Verfügbare Formate
BuchKartoniert, Paperback
EUR87,73
BuchKartoniert, Paperback
EUR62,05
E-BookPDF1 - PDF WatermarkE-Book
EUR85,59

Produkt

KlappentextThis two-volume set LNCS 14509-14510, constitutes the refereed proceedings of the First International Conference on Artificial Intelligence Security and Privacy, AIS&P 2023, held in Guangzhou, China, during December 3-5, 2023.The 40 regular papers and 23 workshop papers presented in this  two-volume set were carefully reviewed and selected from 115 submissions.Topics of interest include, e.g., attacks and defence on AI systems; adversarial learning; privacy-preserving data mining; differential privacy; trustworthy AI; AI fairness; AI interpretability; cryptography for AI; security applications.
Details
ISBN/GTIN978-981-99-9784-8
ProduktartBuch
EinbandartKartoniert, Paperback
Verlag
Erscheinungsjahr2024
Erscheinungsdatum04.02.2024
Auflage1st ed. 2024
ReiheLecture Notes in Computer Science
Seiten595 Seiten
SpracheEnglisch
IllustrationenXV, 595 p. 167 illus., 147 illus. in color.
Artikel-Nr.55733187

Inhalt/Kritik

Inhaltsverzeichnis
Fine-grained Searchable Encryption Scheme.- Fine-grained Authorized Secure Deduplication with Dynamic Policy.- Deep Multi-Image Hiding with Random Key.- Member Inference Attacks in Federated Contrastive Learning.- A network traffic anomaly detection method based on shapelet and KNN.- DFaP: Data Filtering and Purification Against Backdoor Attacks.- A Survey of Privacy Preserving Subgraph Matching Method.- The Analysis of Schnorr Multi-Signatures and the Application to AI.- Active Defense against Image Steganography.- Strict Differentially Private Support Vector Machines with Dimensionality Reduction.- Converging Blockchain and Deep Learning in UAV Network Defense Strategy: Ensuring Data Security During Flight.- Towards Heterogeneous Federated Learning: Analysis, Solutions, and Future Directions.- From Passive Defense to Proactive Defence: Strategies and Technologies.- Research on Surface Defect Detection System of Chip Inductors Based on Machine Vision.- Multimodal fatigue detectionin drivers via physiological and visual signals.- Protecting Bilateral Privacy in Machine Learning-as-a-Service: A Differential Privacy Based Defense.- FedCMK: An Efficient Privacy-Preserving Federated Learning Framework.- An embedded cost learning framework based on cumulative gradient.- An Assurance Case Practice of AI-enabled Systems on Maritime Inspection.- Research and Implementation of EXFAT File System Reconstruction Algorithm Based on Cluster Size Assumption and Computational Verification.- A Verifiable Dynamic Multi-Secret Sharing Obfuscation Scheme Applied to Data LakeHouse.- DZIP: A Data Deduplication-Compatible Enhanced Version of Gzip.- Efficient Wildcard Searchable Symmetric Encryption with Forward and Backward Security.- Adversarial Attacks against Object Detection in Remote Sensing Images.- Hardware Implementation and Optimization of Critical Modules of SM9 Digital Signature Algorithm.- Post-quantum Dropout-resilient Aggregation for Federated Learning via Lattice-basedPRF.- Practical and Privacy-Preserving Decision Tree Evaluation with One Round Communication.- IoT-Inspired Education 4.0 Framework for Higher Education and Industry Needs.- Multi-agent Reinforcement Learning Based User-Centric Demand Response with Non-Intrusive Load Monitoring.- Decision Poisson: From universal gravitation to offline reinforcement learning.- SSL-ABD:An Adversarial Defense MethodAgainst Backdoor Attacks in Self-supervised Learning.- Personalized Differential Privacy in the Shuffle Model.- MKD: Mutual Knowledge Distillation for Membership Privacy Protection.- Fuzzing Drone Control System Configurations Based on Quality-Diversity Enhanced Genetic Algorithm.- KEP: Keystroke Evoked Potential for EEG-based User Authentication.- Verifiable Secure Aggregation Protocol under Federated Learning.- Electronic voting privacy protection scheme based on double signature in Consortium Blockchain.- Securing 5G Positioning via Zero Trust Architecture.- Email Reading Behavior-informed Machine Learning Model to Predict Phishing Susceptibility.mehr

Schlagworte

Autor