LEADER 06210nam 22007215 450 001 9910831010203321 005 20240203181235.0 010 $a981-9997-85-2 024 7 $a10.1007/978-981-99-9785-5 035 $a(MiAaPQ)EBC31106868 035 $a(Au-PeEL)EBL31106868 035 $a(MiAaPQ)EBC31132823 035 $a(Au-PeEL)EBL31132823 035 $a(OCoLC)1420052305 035 $a(DE-He213)978-981-99-9785-5 035 $a(EXLCZ)9930316541200041 100 $a20240203d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArtificial Intelligence Security and Privacy$b[electronic resource] $eFirst International Conference on Artificial Intelligence Security and Privacy, AIS&P 2023, Guangzhou, China, December 3?5, 2023, Proceedings, Part I /$fedited by Jaideep Vaidya, Moncef Gabbouj, Jin Li 205 $a1st ed. 2024. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2024. 215 $a1 online resource (610 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v14509 311 08$aPrint version: Vaidya, Jaideep Artificial Intelligence Security and Privacy Singapore : Springer Singapore Pte. Limited,c2024 9789819997848 327 $aFine-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. . 330 $aThis two-volume set LNCS 14509-14510, constitutes the refereed proceedings of the First International Conference on Artificial Intelligence Security and Privacy, AIS&P 2023, held in Guangzhou, China, during December 3?5, 2023. The 40 regular papers and 23 workshop papers presented in this two-volume set were carefully reviewed and selected from 115 submissions. Topics of interest include, e.g., attacks and defence on AI systems; adversarial learning; privacy-preserving data mining; differential privacy; trustworthy AI; AI fairness; AI interpretability; cryptography for AI; security applications. . 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v14509 606 $aArtificial intelligence 606 $aSecurity systems 606 $aData protection$xLaw and legislation 606 $aCryptography 606 $aData encryption (Computer science) 606 $aData protection 606 $aArtificial Intelligence 606 $aSecurity Science and Technology 606 $aPrivacy 606 $aCryptology 606 $aSecurity Services 615 0$aArtificial intelligence. 615 0$aSecurity systems. 615 0$aData protection$xLaw and legislation. 615 0$aCryptography. 615 0$aData encryption (Computer science). 615 0$aData protection. 615 14$aArtificial Intelligence. 615 24$aSecurity Science and Technology. 615 24$aPrivacy. 615 24$aCryptology. 615 24$aSecurity Services. 676 $a006.3 700 $aVaidya$b Jaideep$01276751 701 $aGabbouj$b Moncef$01631582 701 $aLi$b Jin$01263437 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910831010203321 997 $aUNINA