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2020 – today
- 2025
[j28]A. K. M. Mubashwir Alam, Keke Chen
:
TEE-MR: Developer-friendly data oblivious programming for trusted execution environments. Comput. Secur. 148: 104119 (2025)- 2024
- [j27]A. K. M. Mubashwir Alam, Keke Chen:
TEE-Graph: efficient privacy and ownership protection for cloud-based graph spectral analysis. Frontiers Big Data 6 (2024) - [j26]Sujuan Fan, Keke Chen, Junfeng Tian:
A novel image encryption algorithm based on coupled map lattices model. Multim. Tools Appl. 83(4): 11557-11572 (2024) - [c53]Yuechun Gu, Jiajie He, Keke Chen:
Demo: FT-PrivacyScore: Personalized Privacy Scoring Service for Machine Learning Participation. CCS 2024: 5075-5077 - [c52]Keke Chen, Zhewei Tu, Xiangbo Shu:
Leveraging Multimodal Knowledge for Spatio-Temporal Action Localization. ICME Workshops 2024: 1-5 - [i17]Mrinal Kanti Dhar, Chuanbo Wang, Yash Patel, Taiyu Zhang, Jeffrey A. Niezgoda, Sandeep Gopalakrishnan, Keke Chen, Zeyun Yu:
Wound Tissue Segmentation in Diabetic Foot Ulcer Images Using Deep Learning: A Pilot Study. CoRR abs/2406.16012 (2024) - [i16]Yuechun Gu, Jiajie He, Keke Chen:
FT-PrivacyScore: Personalized Privacy Scoring Service for Machine Learning Participation. CoRR abs/2410.22651 (2024) - [i15]Yuechun Gu, Keke Chen:
Calibrating Practical Privacy Risks for Differentially Private Machine Learning. CoRR abs/2410.22673 (2024) - 2023
- [j25]Keke Chen:
Confidential High-Performance Computing in the Public Cloud. IEEE Internet Comput. 27(1): 24-32 (2023) - [j24]Keke Chen, Yuechun Gu, Sagar Sharma:
DisguisedNets: Secure Image Outsourcing for Confidential Model Training in Clouds. ACM Trans. Internet Techn. 23(3): 47:1-47:26 (2023) - [c51]A. K. M. Mubashwir Alam, Keke Chen:
Making Your Program Oblivious: A Comparative Study for Side-channel-Safe Confidential Computing. CLOUD 2023: 282-289 - [c50]Yuechun Gu, Keke Chen:
GAN-Based Domain Inference Attack. AAAI 2023: 14214-14222 - [c49]Yuechun Gu, Sagar Sharma, Keke Chen:
Demo: Image Disguising for Scalable GPU-accelerated Confidential Deep Learning. CCS 2023: 3679-3681 - [c48]A. K. M. Mubashwir Alam, Justin Boyce, Keke Chen:
Demo: SGX-MR-Prot: Efficient and Developer-Friendly Access-Pattern Protection in Trusted Execution Environments. ICDCS 2023: 1029-1032 - [c47]Zhi Cao, Weijing Zhang, Keke Chen, Di Zhao, Daoqiang Zhang, Hongen Liao, Fang Chen:
Thinking Like Sonographers: A Deep CNN Model for Diagnosing Gout from Musculoskeletal Ultrasound. MICCAI (6) 2023: 159-168 - [c46]Keke Chen, Xiangbo Shu, Guo-Sen Xie, Rui Yan, Jinhui Tang:
Foreground/Background-Masked Interaction Learning for Spatio-temporal Action Detection. ACM Multimedia 2023: 2381-2390 - [i14]Sagar Sharma, Yuechun Gu, Keke Chen:
A Comparative Study of Image Disguising Methods for Confidential Outsourced Learning. CoRR abs/2301.00252 (2023) - [i13]A. K. M. Mubashwir Alam, Keke Chen:
Making Your Program Oblivious: a Comparative Study for Side-channel-safe Confidential Computing. CoRR abs/2308.06442 (2023) - [i12]A. K. M. Mubashwir Alam, Justin Boyce, Keke Chen:
SGX-MR-Prot: Efficient and Developer-Friendly Access-Pattern Protection in Trusted Execution Environments. CoRR abs/2308.06445 (2023) - [i11]Yuechun Gu, Keke Chen:
Adaptive Domain Inference Attack. CoRR abs/2312.15088 (2023) - 2022
- [i10]Keke Chen:
Confidential High-Performance Computing in the Public Cloud. CoRR abs/2212.02378 (2022) - [i9]Yuechun Gu, Keke Chen:
GAN-based Domain Inference Attack. CoRR abs/2212.11810 (2022) - 2021
- [j23]Sagar Sharma, Keke Chen:
Confidential machine learning on untrusted platforms: a survey. Cybersecur. 4(1): 30 (2021) - [j22]A. K. M. Mubashwir Alam, Sagar Sharma, Keke Chen:
SGX-MR: Regulating Dataflows for Protecting Access Patterns of Data-Intensive SGX Applications. Proc. Priv. Enhancing Technol. 2021(1): 5-20 (2021) - [j21]Jinchao Chen, Keke Chen, Chenglie Du, Yifan Liu:
Design and implementation of a virtual ARINC 653 simulation platform. Simul. 97(6) (2021) - [c45]Sagar Sharma, A. K. M. Mubashwir Alam, Keke Chen:
Image Disguising for Protecting Data and Model Confidentiality in Outsourced Deep Learning. CLOUD 2021: 71-77 - [c44]Prem Bhusal, A. K. M. Mubashwir Alam, Keke Chen, Ning Jiang, Jun Xiao:
Scalable Sequence Clustering for Large-Scale Immune Repertoire Analysis. IEEE BigData 2021: 1349-1358 - [c43]Patrick P. K. Chan, Keke Chen, Linyi Xu, Xiaoman Hu, Daniel S. Yeung:
Weakly Supervised Semantic Segmentation with Patch-Based Metric Learning Enhancement. ICANN (3) 2021: 471-482 - [c42]Keke Chen, Patrick P. K. Chan, Tianyi Xiang, Natasha Kees, Daniel S. Yeung:
Class-Specific Affinity based Weakly Supervised Semantic Segmentation with Neutral Region Exploration. IJCNN 2021: 1-8 - 2020
- [i8]A. K. M. Mubashwir Alam, Sagar Sharma, Keke Chen:
SGX-MR: Regulating Dataflows for Protecting Access Patterns of Data-Intensive SGX Applications. CoRR abs/2009.03518 (2020) - [i7]Sagar Sharma, Keke Chen:
Confidential Machine Learning on Untrusted Platforms: A Survey. CoRR abs/2012.08156 (2020)
2010 – 2019
- 2019
- [j20]Keke Chen, Patrick P. K. Chan, Fei Zhang, Qiaoqiao Li:
Shilling attack based on item popularity and rated item correlation against collaborative filtering. Int. J. Mach. Learn. Cybern. 10(7): 1833-1845 (2019) - [j19]Sagar Sharma, James Powers, Keke Chen:
PrivateGraph: Privacy-Preserving Spectral Analysis of Encrypted Graphs in the Cloud. IEEE Trans. Knowl. Data Eng. 31(5): 981-995 (2019) - [c41]Sagar Sharma, Keke Chen:
Confidential Boosting with Random Linear Classifiers for Outsourced User-Generated Data. ESORICS (1) 2019: 41-65 - [c40]Shreyansh P. Bhatt, Keke Chen, Valerie L. Shalin, Amit P. Sheth, Brandon S. Minnery:
Who Should Be the Captain This Week?Leveraging Inferred Diversity-Enhanced Crowd Wisdom for a Fantasy Premier League Captain Prediction. ICWSM 2019: 103-113 - [c39]Jinchao Chen, Chenglie Du, Xu Lu, Keke Chen:
Multi-region Coverage Path Planning for Heterogeneous Unmanned Aerial Vehicles Systems. SOSE 2019 - [c38]Shreyansh P. Bhatt, Swati Padhee, Amit P. Sheth, Keke Chen, Valerie L. Shalin, Derek Doran, Brandon S. Minnery:
Knowledge Graph Enhanced Community Detection and Characterization. WSDM 2019: 51-59 - [e1]Keke Chen, Sangeetha Seshadri, Liang-Jie Zhang:
Big Data - BigData 2019 - 8th International Congress, Held as Part of the Services Conference Federation, SCF 2019, San Diego, CA, USA, June 25-30, 2019, Proceedings. Lecture Notes in Computer Science 11514, Springer 2019, ISBN 978-3-030-23550-5 [contents] - [i6]Sagar Sharma, Keke Chen:
Disguised-Nets: Image Disguising for Privacy-preserving Deep Learning. CoRR abs/1902.01878 (2019) - 2018
- [j18]Keke Chen, Bharath Avusherla, Sarah Allison, Vincent Schmidt:
SPIN: cleaning, monitoring, and querying image streams generated by ground-based telescopes for space situational awareness. Int. J. Data Sci. Anal. 5(2-3): 155-167 (2018) - [j17]Sagar Sharma, Keke Chen, Amit P. Sheth:
Toward Practical Privacy-Preserving Analytics for IoT and Cloud-Based Healthcare Systems. IEEE Internet Comput. 22(2): 42-51 (2018) - [j16]Keke Chen, Shumin Guo:
RASP-Boost: Confidential Boosting-Model Learning with Perturbed Data in the Cloud. IEEE Trans. Cloud Comput. 6(2): 584-597 (2018) - [c37]Sagar Sharma, Keke Chen:
Image Disguising for Privacy-preserving Deep Learning. CCS 2018: 2291-2293 - [c36]Sagar Sharma, Keke Chen:
Privacy-Preserving Boosting with Random Linear Classifiers. CCS 2018: 2294-2296 - [c35]Keke Chen, Patrick P. K. Chan, Daniel S. Yeung:
Unsupervised Shilling Attack Detection Model Based on Rated Item Correlation Analysis. ICMLC 2018: 667-672 - [c34]Keke Chen, Patrick P. K. Chan, Daniel S. Yeung:
Shilling Attack Detection Using Rated Item Correlation for Collaborative Filtering. SMC 2018: 3553-3558 - [i5]Sagar Sharma, Keke Chen:
Privacy-Preserving Boosting with Random Linear Classifiers for Learning from User-Generated Data. CoRR abs/1802.08288 (2018) - [i4]Sagar Sharma, Keke Chen, Amit P. Sheth:
Towards Practical Privacy-Preserving Analytics for IoT and Cloud Based Healthcare Systems. CoRR abs/1804.04250 (2018) - 2017
- [c33]Sagar Sharma, Keke Chen:
PrivateGraph: A Cloud-Centric System for Spectral Analysis of Large Encrypted Graphs. ICDCS 2017: 2507-2510 - [c32]Wenbo Wang, Lu Chen, Keke Chen, Krishnaprasad Thirunarayan, Amit P. Sheth:
Adaptive training instance selection for cross-domain emotion identification. WI 2017: 525-532 - 2016
- [c31]Keke Chen, Venkata Sai Abhishek Gogu, Di Wu, Jiang Ning:
COLT: COnstrained Lineage Tree Generation from sequence data. BIBM 2016: 102-106 - [c30]Sagar Sharma, James Powers, Keke Chen:
Privacy-Preserving Spectral Analysis of Large Graphs in Public Clouds. AsiaCCS 2016: 71-82 - [c29]Shen Yan, Shiran Pan, Wen Tao Zhu, Keke Chen:
DynaEgo: Privacy-Preserving Collaborative Filtering Recommender System Based on Social-Aware Differential Privacy. ICICS 2016: 347-357 - [c28]Lu Zhou, Wenbo Wang, Keke Chen:
Tweet Properly: Analyzing Deleted Tweets to Understand and Identify Regrettable Ones. WWW 2016: 603-612 - 2015
- [c27]Zohreh Alavi, Sagar Sharma, Lu Zhou, Keke Chen:
Scalable Euclidean Embedding for Big Data. CLOUD 2015: 773-780 - [c26]Lu Zhou, Wenbo Wang, Keke Chen:
Identifying Regrettable Messages from Tweets. WWW (Companion Volume) 2015: 145-146 - 2014
- [j15]Keke Chen:
Optimizing star-coordinate visualization models for effective interactive cluster exploration on big data. Intell. Data Anal. 18(2): 117-136 (2014) - [j14]Zohreh Alavi, Lu Zhou, James Powers, Keke Chen:
RASP-QS: Efficient and Confidential Query Services in the Cloud. Proc. VLDB Endow. 7(13): 1685-1688 (2014) - [j13]Huiqi Xu, Shumin Guo, Keke Chen:
Building Confidential and Efficient Query Services in the Cloud with RASP Data Perturbation. IEEE Trans. Knowl. Data Eng. 26(2): 322-335 (2014) - [j12]Keke Chen, James Powers, Shumin Guo, Fengguang Tian:
CRESP: Towards Optimal Resource Provisioning for MapReduce Computing in Public Clouds. IEEE Trans. Parallel Distributed Syst. 25(6): 1403-1412 (2014) - [p2]Keke Chen, Shumin Guo, James Powers, Fengguang Tian:
Toward Optimal Resource Provisioning for Economical and Green MapReduce Computing in the Cloud. Large Scale and Big Data 2014: 535-556 - 2013
- [c25]James Powers, Keke Chen:
Secure Computation of Top-K Eigenvectors for Shared Matrices in the Cloud. IEEE CLOUD 2013: 155-162 - [c24]Keke Chen, Shumin Guo:
PerturBoost: Practical Confidential Classifier Learning in the Cloud. ICDM 2013: 991-996 - 2012
- [j11]Huiqi Xu, Zhen Li, Shumin Guo, Keke Chen:
CloudVista: Interactive and Economical Visual Cluster Analysis for Big Data in the Cloud. Proc. VLDB Endow. 5(12): 1886-1889 (2012) - [c23]Shumin Guo, Keke Chen:
Privacy preserving boosting in the cloud with secure half-space queries. CCS 2012: 1031-1033 - [c22]Shumin Guo, Keke Chen:
Mining Privacy Settings to Find Optimal Privacy-Utility Tradeoffs for Social Network Services. SocialCom/PASSAT 2012: 656-665 - [i3]James Powers, Keke Chen:
Secure MapReduce Power Iteration in the Cloud. CoRR abs/1211.3147 (2012) - [i2]Huiqi Xu, Shumin Guo, Keke Chen:
Building Confidential and Efficient Query Services in the Cloud with RASP Data Perturbation. CoRR abs/1212.0610 (2012) - 2011
- [j10]Keke Chen, Ling Liu:
Geometric data perturbation for privacy preserving outsourced data mining. Knowl. Inf. Syst. 29(3): 657-695 (2011) - [j9]Keke Chen, Jing Bai, Zhaohui Zheng:
Ranking function adaptation with boosting trees. ACM Trans. Inf. Syst. 29(4): 18:1-18:31 (2011) - [c21]Fengguang Tian, Keke Chen:
Towards Optimal Resource Provisioning for Running MapReduce Programs in Public Clouds. IEEE CLOUD 2011: 155-162 - [c20]Keke Chen, Ramakanth Kavuluru, Shumin Guo:
RASP: efficient multidimensional range query on attack-resilient encrypted databases. CODASPY 2011: 249-260 - [c19]Jinpeng Wei, Calton Pu, Keke Chen:
Flying under the radar: maintaining control of kernel without changing kernel code or persistent data structures. CSIIRW 2011: 69 - [c18]Keke Chen, Huiqi Xu, Fengguang Tian, Shumin Guo:
CloudVista: Visual Cluster Exploration for Extreme Scale Data in the Cloud. SSDBM 2011: 332-350 - [i1]Keke Chen:
On Security of the Utility Preserving RASP Encryption. IACR Cryptol. ePrint Arch. 2011: 614 (2011) - 2010
- [j8]Hua Yan, Keke Chen, Ling Liu, Zhang Yi:
SCALE: a scalable framework for efficiently clustering transactional data. Data Min. Knowl. Discov. 20(1): 1-27 (2010) - [c17]Jing Bai, Fernando Diaz, Yi Chang, Zhaohui Zheng, Keke Chen:
Cross-Market Model Adaptation with Pairwise Preference Data for Web Search Ranking. COLING (Posters) 2010: 18-26
2000 – 2009
- 2009
- [j7]Hua Yan, Keke Chen, Ling Liu, Joonsoo Bae:
Determining the best K. Data Knowl. Eng. 68(1): 28-48 (2009) - [j6]Keke Chen, Ling Liu:
"Best K": critical clustering structures in categorical datasets. Knowl. Inf. Syst. 20(1): 1-33 (2009) - [j5]Keke Chen, Ling Liu:
Privacy-Preserving Multiparty Collaborative Mining with Geometric Data Perturbation. IEEE Trans. Parallel Distributed Syst. 20(12): 1764-1776 (2009) - [j4]Keke Chen, Ling Liu:
HE-Tree: a framework for detecting changes in clustering structure for categorical data streams. VLDB J. 18(6): 1241-1260 (2009) - [c16]Keke Chen, Jing Bai, Srihari Reddy, Belle L. Tseng:
On domain similarity and effectiveness of adapting-to-rank. CIKM 2009: 1601-1604 - [c15]Keke Chen, Fengguang Tian:
VisGBT: Visually analyzing evolving datasets for adaptive learning. CollaborateCom 2009: 1-10 - 2008
- [c14]Keke Chen, Rongqing Lu, C. K. Wong, Gordon Sun, Larry P. Heck, Belle L. Tseng:
Trada: tree based ranking function adaptation. CIKM 2008: 1143-1152 - [c13]Keke Chen, Ya Zhang, Zhaohui Zheng, Hongyuan Zha, Gordon Sun:
Adapting ranking functions to user preference. ICDE Workshops 2008: 580-587 - [p1]Keke Chen, Ling Liu:
A Survey of Multiplicative Perturbation for Privacy-Preserving Data Mining. Privacy-Preserving Data Mining 2008: 157-181 - 2007
- [j3]Yongjing Lin, Wenyuan Li, Keke Chen, Ying Liu:
Model Formulation: A Document Clustering and Ranking System for Exploring MEDLINE Citations. J. Am. Medical Informatics Assoc. 14(5): 651-661 (2007) - [c12]Zhaohui Zheng, Hongyuan Zha, Tong Zhang, Olivier Chapelle, Keke Chen, Gordon Sun:
A General Boosting Method and its Application to Learning Ranking Functions for Web Search. NIPS 2007: 1697-1704 - [c11]Keke Chen, Ling Liu:
Space adaptation: privacy-preserving multiparty collaborative mining with geometric perturbation. PODC 2007: 324-325 - [c10]Keke Chen, Gordon Sun, Ling Liu:
Towards Attack-Resilient Geometric Data Perturbation. SDM 2007: 78-89 - [c9]Zhaohui Zheng, Keke Chen, Gordon Sun, Hongyuan Zha:
A regression framework for learning ranking functions using relative relevance judgments. SIGIR 2007: 287-294 - 2006
- [b1]Keke Chen:
Geometric Methods for Mining Large and Possibly Private Datasets. Georgia Institute of Technology, Atlanta, GA, USA, 2006 - [j2]Keke Chen, Ling Liu:
iVIBRATE: Interactive visualization-based framework for clustering large datasets. ACM Trans. Inf. Syst. 24(2): 245-294 (2006) - [c8]Hua Yan, Keke Chen, Ling Liu:
Efficiently clustering transactional data with weighted coverage density. CIKM 2006: 367-376 - [c7]Keke Chen, Ling Liu:
Detecting the Change of Clustering Structure in Categorical Data Streams. SDM 2006: 504-508 - 2005
- [c6]Keke Chen, Ling Liu:
Privacy Preserving Data Classification with Rotation Perturbation. ICDM 2005: 589-592 - [c5]Keke Chen, Ling Liu:
The "Best K" for Entropy-based Categorical Data Clustering. SSDBM 2005: 253-262 - 2004
- [j1]Keke Chen, Ling Liu:
VISTA: validating and refining clusters via visualization. Inf. Vis. 3(4): 257-270 (2004) - [c4]Keke Chen, Ling Liu:
ClusterMap: labeling clusters in large datasets via visualization. CIKM 2004: 285-293 - 2003
- [c3]Keke Chen, Ling Liu:
Validating and Refining Clusters via Visual Rendering. ICDM 2003: 501-504 - [c2]Keke Chen, Ling Liu:
Cluster Rendering of Skewed Datasets via Visualization. SAC 2003: 909-916 - [c1]Keke Chen, Ling Liu:
A Visual Framework Invites Human into the Clustering Process. SSDBM 2003: 97-106
Coauthor Index
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