Publications
New algorithms for fully homomorphic matrix addition and multiplication
Shang Ci,Yihan Wang,Sen Hu,Donghai Guan,Çetin Kaya Koç
The Journal of Supercomputing 2025
JSC'25Optimized BFV-based fully homomorphic algorithms for packed matrix operations are proposed, improving efficiency over prior algorithms.
Privacy-preserving word vectors learning using partially homomorphic encryption
Shang Ci,Sen Hu,Donghai Guan,Çetin Kaya Koç
Journal of Information Security and Applications 2025
JISA'25A privacy-preserving scheme is proposed for training GloVe word vectors on encrypted data, enabling secure and efficient cloud-based learning without compromising user privacy.
SOCT: Secure Outsourcing Computation Toolkit Using Threshold ElGamal Algorithm
Sen Hu,Shang Ci,Donghai Guan,Çetin Kaya Koç
IEEE Transactions on Cloud Computing 2025
TCC'25A secure outsourcing computation framework (SOCT) is proposed based on threshold ElGamal homomorphic encryption, enabling efficient and privacy-preserving cloud computations with strong security guarantees.
Secure grid-based density peaks clustering on hybrid cloud for industrial IoT
Liping Sun,Shang Ci,Xiaoqing Liu,Liangmin Guo,Xiaoyao Zheng,Yonglong Luo
International Journal of Network Management 2021
IJNM'21A privacy-preserving grid-based density peaks clustering scheme is proposed for hybrid cloud environments, enabling efficient and accurate encrypted clustering for industrial IoT data with low client-side overhead.
A privacy-preserving density peak clustering algorithm in cloud computing
Liping Sun,Shang Ci,Xiaoqing Liu,Xiaoyao Zheng,Qingying Yu,Yonglong Luo
Concurrency and Computation: Practice and Experience 2020
CCPE'20A privacy-preserving density peak clustering algorithm is proposed for cloud environments, ensuring secure cluster center computation and participant assignment while resisting collusion attacks.
A Secure Density Peaks Clustering Algorithm on Cloud Computing
Shang Ci,Liping Sun,Xiaoqing Liu,Tingli Du,Xiaoyao Zheng
Cyberspace Safety and Security - 11th International Symposium 2019
CSS'19A grid-based privacy-preserving density peak clustering algorithm is proposed for hybrid cloud environments, enabling efficient encrypted clustering with low client-side computation and strong privacy protection.