A Secure and Efficient Framework for Privacy Preserving Social Recommendation. - Shushu Liu; An Liu 002; Guanfeng Liu 001; Zhixu Li; Jiajie Xu 001; Pengpeng Zhao 001; Lei Zhao 001 (APWeb, 2015)

Efficient Query Processing with Mutual Privacy Protection for Location-Based Services. - Shushu Liu; An Liu 002; Lei Zhao 001; Guanfeng Liu 001; Zhixu Li; Pengpeng Zhao 001; Kai Zheng 001; Lu Qin 001 (DASFAA (2), 2016)

Privacy-Preserving Collaborative Web Services QoS Prediction via Differential Privacy. - Shushu Liu; An Liu 002; Zhixu Li; Guanfeng Liu 001; Jiajie Xu 001; Lei Zhao 001; Kai Zheng 001 (APWeb/WAIM (1), 2017)

Predict Pairwise Trust Based on Machine Learning in Online Social Networks: A Survey. - Shushu Liu; Lifang Zhang; Zheng Yan 002 (IEEE Access, 2018)

Sensing Mechanism and Real-Time Computing for Granular Materials. - Shushu Liu; Hai Huang; Tong Qiu; Shihui Shen (J. Comput. Civ. Eng., 2018)

Efficient LBS queries with mutual privacy preservation in IoV. - Shushu Liu; An Liu 002; Zheng Yan 002; Wei Feng 010 (Veh. Commun., 2019)

Verifiable Edge Computing for Indoor Positioning. - Shushu Liu; Zheng Yan 002 (ICC, 2020)

Spatial and Temporal Pricing Approach for Tasks in Spatial Crowdsourcing. - Jing Qian; Shushu Liu; An Liu 002 (WISE (1), 2020)

Privacy protection in mobile crowd sensing: a survey. - Yongfeng Wang; Zheng Yan 002; Wei Feng 010; Shushu Liu (World Wide Web, 2020)

Incentive-aware Task Location in Spatial Crowdsourcing. - Fei Zhu; Shushu Liu; Junhua Fang; An Liu 002 (DASFAA (1), 2021)

Privacy-preserving D2D Cooperative Location Verification. - Shushu Liu; Zheng Yan 002; Raimo Kantola (GLOBECOM, 2021)

Incentive Mechanism for Spatial Crowdsourcing Cooperation: A Fair Revenue Allocation Method. - Xiaowei Wang; An Liu 002; Shushu Liu; Junhua Fang; Jiajie Xu 001 (ICSOC, 2021)

Privacy-Preserving Worker Recruitment Under Variety Requirement in Spatial Crowdsourcing. - Zhixiang Zhang; An Liu 002; Shushu Liu; Zhixu Li; Lei Zhao 001 (ICSOC, 2021)

Locally Random Sampling for Practical Privacy Protection in Federated Learning. - Weiqi Wang; Shushu Liu; An Liu 002; Christy Jie Liang; Shui Yu 001 (GLOBECOM, 2022)

Secure 5G Positioning With Truth Discovery, Attack Detection, and Tracing. - Yilin Li; Shushu Liu; Zheng Yan 002; Robert H. Deng (IEEE Internet Things J., 2022)

Efficient Privacy Protection Protocols for 5G-Enabled Positioning in Industrial IoT. - Shushu Liu; Zheng Yan 002 (IEEE Internet Things J., 2022)

Privacy Protection in 5G Positioning and Location-based Services Based on SGX. - Zheng Yan 002; Xinren Qian; Shushu Liu; Robert H. Deng (ACM Trans. Sens. Networks, 2022)

Securing 5G Positioning and its Services with Privacy Preservation. - Shushu Liu (2022)

CP-FL: Practical Gradient Leakage Defense in Federated Learning with Compressive Privacy. - Weiqi Wang; Shushu Liu; Chenhan Zhang; Mingjian Tang 002; Feng Wu; Shui Yu 001 (GLOBECOM, 2023)

FedMC: Federated Learning with Mode Connectivity Against Distributed Backdoor Attacks. - Weiqi Wang; Chenhan Zhang; Shushu Liu; Mingjian Tang 002; An Liu 002; Shui Yu 001 (ICC, 2023)

Designing Trustworthy Decentralized Cross-Chain Marketplaces: A 6G Network of Networks Perspective. - Lalita Jagadeesan; Shushu Liu; Lizette Velázquez (CSR, 2024)

Granular-ball-based Fast Spectral Embedding Clustering Algorithm for Large-Scale Data. - Shushu Liu; Dongdong Cheng; Jiang Xie 002 (ICMLC, 2024)

Granular-ball computing-based manifold clustering algorithms for ultra-scalable data. - Dongdong Cheng; Shushu Liu; Shuyin Xia; Guoyin Wang 001 (Expert Syst. Appl., 2024)

CRFU: Compressive Representation Forgetting Against Privacy Leakage on Machine Unlearning. - Weiqi Wang; Chenhan Zhang; Zhiyi Tian; Shushu Liu; Shui Yu 001 (IEEE Trans. Dependable Secur. Comput., 2025)