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Artificial intelligence security and privacyfirst International Conference on Artificial Intelligence Security and Privacy, AIS&P 2023, Guangzhou, China, December 3-5, 2023 : proceedings.Part I /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Artificial intelligence security and privacyedited by Jaideep Vaidya, Moncef Gabbouj, Jin Li.
Reminder of title:	first International Conference on Artificial Intelligence Security and Privacy, AIS&P 2023, Guangzhou, China, December 3-5, 2023 : proceedings.
remainder title:	AIS&P 2023
other author:	Vaidya, Jaideep.
corporate name:
Published:	Singapore :Springer Nature Singapore :2024.
Description:	xv, 595 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Privacy.
Online resource:	https://doi.org/10.1007/978-981-99-9785-5
ISBN:	9789819997855$q(electronic bk.)

Artificial intelligence security and privacyfirst International Conference on Artificial Intelligence Security and Privacy, AIS&P 2023, Guangzhou, China, December 3-5, 2023 : proceedings.Part I /
Artificial intelligence security and privacyfirst International Conference on Artificial Intelligence Security and Privacy, AIS&P 2023, Guangzhou, China, December 3-5, 2023 : proceedings.Part I /[electronic resource] :AIS&P 2023edited by Jaideep Vaidya, Moncef Gabbouj, Jin Li. - Singapore :Springer Nature Singapore :2024. - xv, 595 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,145090302-9743 ;. - Lecture notes in computer science ;4891..

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 detection in 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-based PRF -- 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.

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.

ISBN: 9789819997855$q(electronic bk.)

Standard No.: 10.1007/978-981-99-9785-5doiSubjects--Topical Terms:

268519
Privacy.

LC Class. No.: Q334

Dewey Class. No.: 006.3

Artificial intelligence security and privacyfirst International Conference on Artificial Intelligence Security and Privacy, AIS&P 2023, Guangzhou, China, December 3-5, 2023 : proceedings.Part I /
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