An RDF triple based access authorization specification considering subsumption relationships. - Jaehoon Kim; Kangsoo Jung; Seog Park (ICDE Workshops, 2008)

An Introduction to Authorization Conflict Problem in RDF Access Control. - Jaehoon Kim; Kangsoo Jung; Seog Park (KES (2), 2008)

A Method of Pre-detecting Privacy Leak in Social Network Service Using Collaborative Filtering. - Chungha Kim; Kangsoo Jung; Seog Park (DASFAA Workshops, 2013)

Hiding a Needle in a Haystack: Privacy Preserving Apriori algorithm inMapReduce Framework. - Kangsoo Jung; Sehwa Park; Seog Park (PSBD@CIKM, 2014)

A Privacy Preserving Technique to Prevent Sensitive Behavior Exposure in Semantic Location-based Service. - Yuna Oh; Kangsoo Jung; Seog Park (KES, 2014)

A game theoretic approach for collaborative caching techniques in privacy preserving location-based services. - Kangsoo Jung; Seongyong Jo; Seog Park (BigComp, 2015)

A noise parameter configuration technique to mitigate detour inference attack on differential privacy. - Taebo Jung; Kangsoo Jung; Sehwa Park; Seog Park (BigComp, 2017)

Collaborative caching techniques for privacy-preserving location-based services in peer-to-peer environments. - Kangsoo Jung; Seog Park (IEEE BigData, 2017)

Grayscale access control: Applying differential privacy to access control for Internet of Thing environment. - Kangsoo Jung; Seog Park (ICTC, 2017)

DRAKO: Differentially pRivate Algorithm to meet K-anonymity for Online portal service. - Kangsoo Jung; Jaewon Kim; Youngjun Kim; Seog Park (IEEE BigData, 2018)

Privacy Bargaining with Fairness: Privacy-Price Negotiation System for Applying Differential Privacy in Data Market Environments. - Kangsoo Jung; Seog Park (IEEE BigData, 2019)

PRIVATA: Differentially Private Data Market Framework using Negotiation-based Pricing Mechanism. - Kangsoo Jung; Junkyu Lee 002; Kunyoung Park; Seog Park (CIKM, 2019)

Sparsity Reduction Technique Using Grouping Method for Matrix Factorization in Differentially Private Recommendation Systems. - Taewhan Kim; Kangsoo Jung; Seog Park (IEICE Trans. Inf. Syst., 2020)

Establishing the Price of Privacy in Federated Data Trading. - Kangsoo Jung; Sayan Biswas; Catuscia Palamidessi (Protocols, Strands, and Logic, 2021)

An Incentive Mechanism for Trading Personal Data in Data Markets. - Sayan Biswas; Kangsoo Jung; Catuscia Palamidessi (ICTAC, 2021)

Tight Differential Privacy Blanket for Shuffle Model. - Sayan Biswas; Kangsoo Jung; Catuscia Palamidessi (CoRR, 2022)

Tight Differential Privacy Guarantees for the Shuffle Model with k-Randomized Response. - Sayan Biswas; Kangsoo Jung; Catuscia Palamidessi (FPS (1), 2023)

Group Privacy for Personalized Federated Learning. - Filippo Galli; Sayan Biswas; Kangsoo Jung; Tommaso Cucinotta; Catuscia Palamidessi (ICISSP, 2023)

Privacy-Aware Document Visual Question Answering. - Rubèn Tito; Khanh Nguyen; Marlon Tobaben; Raouf Kerkouche; Mohamed Ali Souibgui; Kangsoo Jung; Lei Kang; Ernest Valveny; Antti Honkela; Mario Fritz; Dimosthenis Karatzas (CoRR, 2023)

Advancing Personalized Federated Learning: Group Privacy, Fairness, and Beyond. - Filippo Galli; Kangsoo Jung; Sayan Biswas; Catuscia Palamidessi; Tommaso Cucinotta (SN Comput. Sci., 2023)

Poster: Protection against Source Inference Attacks in Federated Learning using Unary Encoding and Shuffling. - Andreas Athanasiou; Kangsoo Jung; Catuscia Palamidessi (CCS, 2024)

Causal Discovery Under Local Privacy. - Ruta Binkyte; Carlos Pinzón; Szilvia Lestyan; Kangsoo Jung; Héber Hwang Arcolezi; Catuscia Palamidessi (CLeaR, 2024)

Privacy-Aware Document Visual Question Answering. - Rubèn Tito; Khanh Nguyen; Marlon Tobaben; Raouf Kerkouche; Mohamed Ali Souibgui; Kangsoo Jung; Joonas Jälkö; Vincent Poulain D'Andecy; Aurélie Joseph; Lei Kang; Ernest Valveny; Antti Honkela; et al. (ICDAR (6), 2024)

Protection against Source Inference Attacks in Federated Learning using Unary Encoding and Shuffling. - Andreas Athanasiou; Kangsoo Jung; Catuscia Palamidessi (CoRR, 2024)

NeurIPS 2023 Competition: Privacy Preserving Federated Learning Document VQA. - Marlon Tobaben; Mohamed Ali Souibgui; Rubèn Tito; Khanh Nguyen; Raouf Kerkouche; Kangsoo Jung; Joonas Jälkö; Lei Kang; Andrey Barsky; Vincent Poulain D'Andecy; Aurélie Joseph; Aashiq Muhamed; et al. (Trans. Mach. Learn. Res., 2025)

Metric Privacy in Federated Learning for Medical Imaging: Improving Convergence and Preventing Client Inference Attacks. - Judith Sáinz-Pardo Díaz; Andreas Athanasiou; Kangsoo Jung; Catuscia Palamidessi; Álvaro López García (CoRR, 2025)

Mitigating Membership Inference Vulnerability in Personalized Federated Learning. - Kangsoo Jung; Sayan Biswas; Catuscia Palamidessi (CoRR, 2025)

DocVXQA: Context-Aware Visual Explanations for Document Question Answering. - Mohamed Ali Souibgui; Changkyu Choi; Andrey Barsky; Kangsoo Jung; Ernest Valveny; Dimosthenis Karatzas (CoRR, 2025)