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Sinem Sav

Observed names: Sav, Sinem, SİNEM SAV
ORCID: 0000-0001-9096-8768
Observed ORCID: 0000-0001-9096-8768
OpenAlex ID: A5025665736
POSEIDON: Privacy-Preserving Federated Neural Network Learning
2021 · Sinem Sav, Apostolos Pyrgelis, et al. · Network and Distributed System Security Symposium · 200
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Scalable Privacy-Preserving Distributed Learning
2021 · David Froelicher, Juan R. Troncoso-Pastoriza, et al. · Proceedings on Privacy Enhancing Technologies · 83
Privacy-preserving federated neural network learning for disease-associated cell classification
2022 · Sinem Sav, Jean-Philippe Bossuat, et al. · Patterns · 47
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Privacy-Preserving Federated Recurrent Neural Networks
2023 · Sinem Sav, Abdulrahman Diaa, et al. · Proceedings on Privacy Enhancing Technologies · 17
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CURE: Privacy-Preserving Split Learning Done Right
2026 · Halil Ibrahim Kanpak, Aqsa Shabbir, et al. · Proceedings on Privacy Enhancing Technologies · 10
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Privacy-Preserving Hyperparameter Tuning for Federated Learning
2025 · Natalija Mitic, Apostolos Pyrgelis, et al. · IEEE Transactions on Privacy · 8
Generated Data with Fake Privacy: Hidden Dangers of Fine-tuning Large Language Models on Generated Data
2024 · Akkus, Atilla, Aghdam, Masoud Poorghaffar, et al. · arXiv (Cornell University) · 8
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Beacon Reconstruction Attack: Reconstruction of genomes in genomic data-sharing beacons using summary statistics
2025 · Kousar Saleem, A Ercument Cicek, et al. · Bioinformatics · 6
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A Taxonomy of Attacks and Defenses in Split Learning
2025 · Shabbir, Aqsa, Kanpak, Halil İbrahim, et al. · arXiv (Cornell University) · 6
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Inclusive Federated Learning Through Compliance-Weighted Noise Allocation in Healthcare AI
2025 · Parampottupadam, Santhosh, Coşğun, Melih, et al. · arXiv (Cornell University) · 5
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slytHErin: An Agile Framework for Encrypted Deep Neural Network Inference
2023 · Francesco Intoci, Sinem Sav, et al. · Lecture notes in computer science · 5
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A reinforcement learning-based approach for dynamic privacy protection in genomic data sharing beacons
2025 · Masoud Poorghaffar Aghdam, Sobhan Shukueian Tabrizi, et al. · Genome biology · 3
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Client Security Alone Fails in Federated Learning: 2D and 3D Attack Insights
2025 · Santhosh Parampottupadam, Ralf Floca, et al. · Communications in computer and information science · 2
SoK: A Taxonomy of Attacks and Defenses in Split Learning
2026 · Aqsa Shabbir, Halil Ibrahim Kanpak, et al. · Lecture notes in computer science · 1
SERSEM: Selective Entropy-Weighted Scoring for Membership Inference in Code Language Models
2026 · Dikici, Kıvanç Kuzey, Kara, Serdar, et al. · arXiv (Cornell University) · 1
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A joint optimization-based novel attack for genomic beacon reconstruction
2026 · KOUSAR SALEEM, SİNEM SAV · TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES · 1
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XposedMIA: Exploiting Explainable Artificial Intelligence (XAI) for One-Shot Membership Inference Attacks
2026 · Hamdache, Omar, Kara, Serdar, et al. · arXiv (Cornell University)
SNAPRAG: Cost-Efficient Knowledge Extraction Attack on RAG Systems via Adversarial Perturbations
2026 · Coşğun, Melih, Gürsoy, Mehmet Emre, et al. · arXiv (Cornell University)
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BrainwashedLLM: Jailbreaking via Automated Adversarial Chain of Thoughts Discovery
2026 · Aghdam, Masoud Poorghaffar, Yıldırım, Göktuğ Serdar, et al. · arXiv (Cornell University)
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HE-OFT: Privacy-Preserving One-Shot Federated Fine-Tuning under Homomorphic Encryption
2026 · Kanpak, Halil İbrahim, Sav, Sinem, et al. · arXiv (Cornell University)
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Visual distinctiveness drives memorization beyond rarity in fine-tuned medical imaging models
2026 · Santhosh Parampottupadam, Sinem Sav, et al. · Research Square
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Privacy Leakage in Federated Learning in Radiology Reports: Comparative Evaluation of Tokenizer and Batch-Size Privacy Risks
2026 · Santhosh Parampottupadam, Andrés Martínez Mora, et al. · JMIR Medical Informatics
SERSEM: Selective Entropy-Weighted Scoring for Membership Inference in Code Language Models
2026 · Kıvanç Kuzey Dikici, Serdar Kara, et al. · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE)
HADES: Privacy-Preserving Federated Learning via Selective Feature Encryption and Hybrid Model Fusion
2026 · Kaynak, Ergün Batuhan, Bayramoglu, Kerem, et al. · arXiv (Cornell University)
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Bridging Local and Federated Data Normalization in Federated Learning: A Privacy-Preserving Approach
2026 · Melih Cosgun, Mert Gencturk, et al. · IEEE Transactions on Big Data
Works count: 30
Citation count: 403
H-index: 7
I10-index: 5
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