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Scalable Differentially Private Clustering via Hierarchically Separated Trees [article]

Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi, Vahab Mirrokni, Andres Munoz, David Saulpic, Chris Schwiegelshohn, Sergei Vassilvitskii
2022 arXiv   pre-print
We study the private k-median and k-means clustering problem in d dimensional Euclidean space.  ...  By leveraging tree embeddings, we give an efficient and easy to implement algorithm, that is empirically competitive with state of the art non private methods.  ...  Our starting point is an embedding of the input points into a tree using a randomly-shifted quadtree (sometimes called HST for Hierarchically Separated Tree) 2 .  ... 
arXiv:2206.08646v1 fatcat:7vdh52qezvgtzdsdpz72r64xba

ICDE conference 2015 detailed author index

2015 2015 IEEE 31st International Conference on Data Engineering  
Record Linkage Scheme: Separating Differentially Private Synopses from Matching Records Cao, Xin 255 Temporal Spatial-Keyword Top-k Publish/Subscribe Cao, Yang 161 Making Pattern Queries Bounded  ...  Record Linkage Scheme: Separating Differentially Private Synopses from Matching Records Kaoudi, Zoi 771 CliqueSquare: Kargar, Mehdi 411 Meaningful Keyword Search in Relational Databases with  ... 
doi:10.1109/icde.2015.7113260 fatcat:ep7pomkm55f45j33tkpoc5asim

ICDE conference 2015 table of contents

2015 2015 IEEE 31st International Conference on Data Engineering  
Telang, Prasad Deshpande, Sriram Raghavan) Research Session 22: Data Privacy and Security 2 1011 A Hybrid Private Record Linkage Scheme: Separating Differentially Private Synopses from Matching Records  ...  Personalized Differential Privacy (Zach Jorgensen, Ting Yu, Graham Cormode) 1035 Differentially Private Frequent Sequence Mining via Sampling-Based Candidate Pruning (Shengzhi Xu, Sen Su, Xiang Cheng  ... 
doi:10.1109/icde.2015.7113258 fatcat:yvim4gc5rfhevoehwfvl35nqji

A general scalable and accurate decentralized level monitoring method for large-scale dynamic service provision in hybrid clouds

Yongquan Fu, Yijie Wang, Ernst Biersack
2013 Future generations computer systems  
For each kind of network metric, HPM represents the degree of pairwise closeness with discrete level values inspired by the hierarchical clustering tree.  ...  Furthermore, HPM computes the pairwise levels with decentralized coordinates for scalability.  ...  Let the maximum layer number in the hierarchical clustering tree be L max cluster . 3.  ... 
doi:10.1016/j.future.2012.11.001 fatcat:bxp6wvoqu5attmwcnf32lbghfa

k-Median Clustering via Metric Embedding: Towards Better Initialization with Differential Privacy [article]

Chenglin Fan, Ping Li, Xiaoyun Li
2022 arXiv   pre-print
The HST initialization can also be extended to the setting of differential privacy (DP) to generate private initial centers.  ...  When designing clustering algorithms, the choice of initial centers is crucial for the quality of the learned clusters.  ...  Initialization via Hierarchically Well-Separated Tree (HST) In this section, we propose our novel initialization scheme for k-median clustering, and provide our analysis in the non-private case solving  ... 
arXiv:2206.12895v2 fatcat:vojakryxbbhlbcar3x7o3upwli

Private Two-Party Cluster Analysis Made Formal Scalable [article]

Xianrui Meng, Dimitrios Papadopoulos, Alina Oprea, Nikos Triandopoulos
2019 arXiv   pre-print
In this work, we present the first comprehensive study for privacy-preserving collaborative hierarchical clustering, overall featuring scalable cryptographic protocols that allow two parties to safely  ...  Specifically, we extend our core protocol to obtain two secure variants that significantly improve performance, an optimized variant for single-linkage clustering and a scalable approximate variant.  ...  To the best of our knowledge, ours is the first work to compose secure cryptographic protocols with efficient approximation algorithms for scalable private hierarchical clustering.  ... 
arXiv:1904.04475v2 fatcat:mss4mujjgngbheypvv6rurb7im

A framework for object-oriented on-line analytic processing

Jan W. Buzydlowski, Il-Yeol Song, Lewis Hassell
1998 Proceedings of the 1st ACM international workshop on Data warehousing and OLAP - DOLAP '98  
Although data warehouses are viewed as organized, summarized repositories of time-oriented data conceptually, the physical implementation determines the speed, efficiency, scalability, and extensibility  ...  , such as clustering by the time grain.  ...  The dimension itself is mapped to a class where it serves as the root of a hierarchical tree with links to the first level below and to a special parent, TOP, which represents null.  ... 
doi:10.1145/294260.294264 dblp:conf/dolap/BuzydlowskiSH98 fatcat:syun6zfilrhxnm5q7i3iljmmca

Secure Aggregated Routing Protocol in WSN - A Review

Anuradha MP, Gopinath Ganapathy
2014 International Journal of Computer Applications  
This survey covers a wide range of key issues in routing protocols based on its own evaluation metrics such as throughput, Packet delivery ratio, network lifetime, energy conservation, complexity, scalability  ...  Therefore, differential aggregation has greater possibility to decrease the amount of data to be broadcasted from sensor nodes to cluster heads.  ...  Each sensor node consists of separate id and aggregation tree contains parent node, the path length, which defines the number of hops from the sink.  ... 
doi:10.5120/17608-8117 fatcat:ehot45z3avcsdhjoxj2a7mgu2m

Citadel: Protecting Data Privacy and Model Confidentiality for Collaborative Learning with SGX [article]

Chengliang Zhang, Junzhe Xia, Baichen Yang, Huancheng Puyang, Wei Wang, Ruichuan Chen, Istemi Ekin Akkus, Paarijaat Aditya, Feng Yan
2021 arXiv   pre-print
However, existing private ML solutions, such as federated learning and split learning, cannot meet the privacy requirements of both data and model owners at the same time.  ...  Citadel further establishes a strong information barrier between these enclaves by means of zero-sum masking and hierarchical aggregation to prevent data/model leakage during collaborative training.  ...  We first examine the scalability of Citadel with zero-sum masking in clusters of various sizes.  ... 
arXiv:2105.01281v2 fatcat:iuc2gbqh4rbpfou2bf7hf7j4em

A scalable multi-datacenter layer-2 network architecture

Chen Chen, Changbin Liu, Pingkai Liu, Boon Thau Loo, Ling Ding
2015 Proceedings of the 1st ACM SIGCOMM Symposium on Software Defined Networking Research - SOSR '15  
WL2 uses an SDNbased architecture [23] to achieve scalability in a wide-area L2 network. In each datacenter, WL2 deploys a centralized SDN controller cluster, and creates full-mesh virtual overlay  ...  The major scalability bottleneck lies at the broadcast nature of control traffic in a L2 network, such as Spanning Tree Protocol (STP), Dynamic Host Configuration Protocol (DHCP) and Address Resolution  ...  PortLand [30] designs a scalable L2 network in a single datacenter with a largely fixed topology (i.e., Fat-tree) of physical switches.  ... 
doi:10.1145/2774993.2775008 dblp:conf/sosr/ChenLLLD15 fatcat:xif7clzbxrb7vfnykbn6q3ohte

Detecting Communities under Differential Privacy

Hiep H. Nguyen, Abdessamad Imine, Michaël Rusinowitch
2016 Proceedings of the 2016 ACM on Workshop on Privacy in the Electronic Society - WPES'16  
However, the problem of doing this in a private manner is rarely considered. In this paper, we solve this problem under differential privacy, a prominent privacy concept for releasing private data.  ...  It comprises two phases: differentially private sampling a k-ary tree of depth maxL which uses the privacy budget ǫ1 and finding the best cut across the tree to get a good clustering of nodes which consumes  ...  The research community, therefore, expresses a strong interest in the problem of graph release via differential privacy.  ... 
doi:10.1145/2994620.2994624 fatcat:pl6ufsenpzf43psxcp24pgvb4e

Detecting Communities under Differential Privacy [article]

Hiep H. Nguyen, Abdessamad Imine, Michael Rusinowitch
2016 arXiv   pre-print
However, the problem of doing this in a private manner is rarely considered. In this paper, we solve this problem under differential privacy, a prominent privacy concept for releasing private data.  ...  It comprises two phases: differentially private sampling a k-ary tree of depth maxL which uses the privacy budget ǫ 1 and finding the best cut across the tree to get a good clustering of nodes which consumes  ...  We review the related work for community detection algorithms and graph release via differential privacy in Section II.  ... 
arXiv:1607.02060v1 fatcat:nsvxlgvbj5ffhfr5fqqpuz5q6e

Big Data Networking : Requirements, Architecture and Issues

Mohammed S. Al-kahtani
2016 International Journal of Wireless & Mobile Networks  
There are various advantages to fabric over the hierarchical tree based topology.  ...  If a network is to support different big data applications requirements and multiple tenants, then it needs to have the ability to differentiate, separate, and process the various workloads independently  ... 
doi:10.5121/ijwmn.2016.8604 fatcat:phueftwrjrfrtlg7sx43pgdsqa

Joint Alignment of Multiple Protein–Protein Interaction Networks via Convex Optimization

Somaye Hashemifar, Qixing Huang, Jinbo Xu
2016 Journal of Computational Biology  
Our method, denoted PrivSTRAT, uses a differentially private framework to protect private phenotype information (disease status) from being leaked while conducting GWAS.  ...  We test the resulting differentially private EIGENSTRAT statistic, PrivS-TRAT, on both simulated and real GWAS datasets to demonstrate its utility.  ...  The cluster containment problem (CCP) is related algorithmic problem that asks whether or not a subset of taxa is a cluster in a tree displayed by a network [2] .  ... 
doi:10.1089/cmb.2016.0025 pmid:27428933 fatcat:tr4e3u3hqjaoziavhhsklxkkmi

Differentially Private Online Task Assignment in Spatial Crowdsourcing: A Tree-based Approach

Qian Tao, Yongxin Tong, Zimu Zhou, Yexuan Shi, Lei Chen, Ke Xu
2020 2020 IEEE 36th International Conference on Data Engineering (ICDE)  
We design a novel privacy mechanism based on Hierarchically Well-Separated Trees (HSTs).  ...  Differentially private online task assignment in spatial crowdsourcing: A tree-based approach. (2020).  ...  To this end, we devise a novel tree-based privacy mechanism leveraging Hierarchically Well-Separated Trees (HSTs).  ... 
doi:10.1109/icde48307.2020.00051 dblp:conf/icde/TaoTZSC020 fatcat:nwsavfwwwjetzjbuerdjqod7c4
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