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 / edited by Jaideep Vaidya, Moncef Gabbouj, Jin Li.

Format:

Book

Contributor:

Vaidya, Jaideep, editor.

Gabbouj, Moncef, editor.

Li, Jin, editor.

Series:

Lecture Notes in Computer Science, 1611-3349 ; 14509

Language:

English

Subjects (All):

Artificial intelligence.

Security systems.

Data protection--Law and legislation.

Data protection.

Cryptography.

Data encryption (Computer science).

Artificial Intelligence.

Security Science and Technology.

Privacy.

Cryptology.

Security Services.

Local Subjects:

Artificial Intelligence.

Security Science and Technology.

Privacy.

Cryptology.

Security Services.

Physical Description:

1 online resource (610 pages)

Edition:

1st ed. 2024.

Place of Publication:

Singapore : Springer Nature Singapore : Imprint: Springer, 2024.

Summary:

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. .

Contents:

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. .

Notes:

Includes bibliographical references and index.

Other Format:

Print version: Vaidya, Jaideep Artificial Intelligence Security and Privacy

ISBN:

981-9997-85-2

OCLC:

1420052305