Privacy-Preserving Support Vector Machine Training Over Blockchain-Based Encrypted IoT Data in Smart Cities
Machine learning (ML) techniques have been widely used in many smart city sectors, where a huge amount of data is gathered from various (IoT) devices. As a typical ML model, support vector machine (SVM) enables efficient data classification and thereby finds its applications in real-world scenarios,...
Gespeichert in:
| Veröffentlicht in: | IEEE internet of things journal Jg. 6; H. 5; S. 7702 - 7712 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Piscataway
IEEE
01.10.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Schlagworte: | |
| ISSN: | 2327-4662, 2327-4662 |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | Machine learning (ML) techniques have been widely used in many smart city sectors, where a huge amount of data is gathered from various (IoT) devices. As a typical ML model, support vector machine (SVM) enables efficient data classification and thereby finds its applications in real-world scenarios, such as disease diagnosis and anomaly detection. Training an SVM classifier usually requires a collection of labeled IoT data from multiple entities, raising great concerns about data privacy. Most of the existing solutions rely on an implicit assumption that the training data can be reliably collected from multiple data providers, which is often not the case in reality. To bridge the gap between ideal assumptions and realistic constraints, in this paper, we propose secureSVM, which is a privacy-preserving SVM training scheme over blockchain-based encrypted IoT data. We utilize the blockchain techniques to build a secure and reliable data sharing platform among multiple data providers, where IoT data is encrypted and then recorded on a distributed ledger. We design secure building blocks, such as secure polynomial multiplication and secure comparison, by employing a homomorphic cryptosystem, Paillier, and construct a secure SVM training algorithm, which requires only two interactions in a single iteration, with no need for a trusted third-party. Rigorous security analysis prove that the proposed scheme ensures the confidentiality of the sensitive data for each data provider as well as the SVM model parameters for data analysts. Extensive experiments demonstrates the efficiency of the proposed scheme. |
|---|---|
| AbstractList | Machine learning (ML) techniques have been widely used in many smart city sectors, where a huge amount of data is gathered from various (IoT) devices. As a typical ML model, support vector machine (SVM) enables efficient data classification and thereby finds its applications in real-world scenarios, such as disease diagnosis and anomaly detection. Training an SVM classifier usually requires a collection of labeled IoT data from multiple entities, raising great concerns about data privacy. Most of the existing solutions rely on an implicit assumption that the training data can be reliably collected from multiple data providers, which is often not the case in reality. To bridge the gap between ideal assumptions and realistic constraints, in this paper, we propose secureSVM , which is a privacy-preserving SVM training scheme over blockchain-based encrypted IoT data. We utilize the blockchain techniques to build a secure and reliable data sharing platform among multiple data providers, where IoT data is encrypted and then recorded on a distributed ledger. We design secure building blocks, such as secure polynomial multiplication and secure comparison, by employing a homomorphic cryptosystem, Paillier, and construct a secure SVM training algorithm, which requires only two interactions in a single iteration, with no need for a trusted third-party. Rigorous security analysis prove that the proposed scheme ensures the confidentiality of the sensitive data for each data provider as well as the SVM model parameters for data analysts. Extensive experiments demonstrates the efficiency of the proposed scheme. |
| Author | Guizani, Mohsen Du, Xiaojiang Shen, Meng Tang, Xiangyun Zhu, Liehuang |
| Author_xml | – sequence: 1 givenname: Meng orcidid: 0000-0002-1867-0972 surname: Shen fullname: Shen, Meng email: shenmeng@bit.edu.cn organization: School of Computer Science, Beijing Institute of Technology, Beijing – sequence: 2 givenname: Xiangyun surname: Tang fullname: Tang, Xiangyun email: tangguotxy@163.com organization: School of Computer Science, Beijing Institute of Technology, Beijing – sequence: 3 givenname: Liehuang orcidid: 0000-0003-3277-3887 surname: Zhu fullname: Zhu, Liehuang email: liehuangz@bit.edu.cn organization: School of Computer Science, Beijing Institute of Technology, Beijing – sequence: 4 givenname: Xiaojiang orcidid: 0000-0003-4235-9671 surname: Du fullname: Du, Xiaojiang email: dxj@ieee.org organization: Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA – sequence: 5 givenname: Mohsen orcidid: 0000-0002-8972-8094 surname: Guizani fullname: Guizani, Mohsen email: mguizani@ieee.org organization: Department of Computer Science and Engineering, Qatar University, Doha, Qatar |
| BookMark | eNp9kE1PAjEQhhujiaj8AOOliefFfux2t0dBVIwGE9DrppRZLWC7toWEf28JxhgPnmYy8z7z8Z6gQ-ssIHROSY9SIq8eRuNpjxEqe0wSWuXkAHUYZ2WWC8EOf-XHqBvCghCSsIJK0UHLZ282Sm-zZw8B_MbYNzxZt63zEb-Cjs7jJ6XfjQU89crYXX-8AY_7K6eX-j2Vsr4KMMdDq_22jSkbuSm-UVFhY_HkQ6VJAxMNhDN01KhVgO53PEUvt8Pp4D57HN-NBtePmeaFjBmfSwUaxLzRBVcCKGjKWEn1nNGqEFRJ1ShdlWUuGyWLGZnNOBeac-BC5OWMn6LL_dzWu881hFgv3NrbtLJmnHBZcZ6LpCr3Ku1dCB6aWpuoonE2pkdXNSX1ztx6Z269M7f-NjeR9A_ZepP-3P7LXOwZAwA_-koU6XTGvwCF1Ydr |
| CODEN | IITJAU |
| CitedBy_id | crossref_primary_10_1109_ACCESS_2023_3260182 crossref_primary_10_1109_TII_2020_3032147 crossref_primary_10_1109_ACCESS_2021_3069737 crossref_primary_10_1109_TIFS_2023_3283104 crossref_primary_10_1109_ACCESS_2020_2983994 crossref_primary_10_1155_2022_5295801 crossref_primary_10_3390_s24103111 crossref_primary_10_1109_JIOT_2020_3030821 crossref_primary_10_3390_s23010519 crossref_primary_10_1007_s11135_021_01251_2 crossref_primary_10_1016_j_jss_2022_111475 crossref_primary_10_1016_j_iot_2024_101187 crossref_primary_10_1109_COMST_2020_3011561 crossref_primary_10_1109_JIOT_2019_2957400 crossref_primary_10_1016_j_comnet_2022_109365 crossref_primary_10_1109_TVT_2019_2957425 crossref_primary_10_1109_MNET_001_1900140 crossref_primary_10_1109_TIFS_2023_3347895 crossref_primary_10_1109_JIOT_2023_3293165 crossref_primary_10_3390_s20030758 crossref_primary_10_1109_JIOT_2020_3015772 crossref_primary_10_3390_fi16120452 crossref_primary_10_1016_j_icte_2025_04_001 crossref_primary_10_1016_j_comnet_2023_109634 crossref_primary_10_1145_3417987 crossref_primary_10_1109_JIOT_2021_3060764 crossref_primary_10_1007_s12083_023_01554_1 crossref_primary_10_1109_TIFS_2023_3283910 crossref_primary_10_1109_ACCESS_2021_3129697 crossref_primary_10_1109_TVT_2022_3194008 crossref_primary_10_1016_j_comcom_2019_10_031 crossref_primary_10_1109_ACCESS_2023_3296482 crossref_primary_10_1109_JIOT_2020_3033543 crossref_primary_10_1109_MNET_001_1900153 crossref_primary_10_1007_s41635_019_00079_5 crossref_primary_10_1109_ACCESS_2019_2946202 crossref_primary_10_1108_K_07_2020_0449 crossref_primary_10_1109_ACCESS_2023_3250235 crossref_primary_10_1038_s41598_023_44101_x crossref_primary_10_1016_j_ijleo_2022_170420 crossref_primary_10_1109_JIOT_2019_2958079 crossref_primary_10_1109_JIOT_2019_2958077 crossref_primary_10_3390_bdcc4020009 crossref_primary_10_1109_JIOT_2019_2957421 crossref_primary_10_1109_ACCESS_2020_3009160 crossref_primary_10_32604_cmc_2022_020833 crossref_primary_10_1016_j_future_2021_05_007 crossref_primary_10_1109_JIOT_2025_3587023 crossref_primary_10_3390_s23167262 crossref_primary_10_1002_cpe_6264 crossref_primary_10_4018_JOEUC_318478 crossref_primary_10_3390_fi17060256 crossref_primary_10_3390_s23229033 crossref_primary_10_1109_COMST_2020_2975911 crossref_primary_10_1016_j_bspc_2024_107411 crossref_primary_10_1109_JIOT_2019_2963767 crossref_primary_10_1109_JIOT_2022_3181734 crossref_primary_10_1109_TII_2019_2957140 crossref_primary_10_3390_su16010171 crossref_primary_10_1109_JIOT_2023_3285206 crossref_primary_10_1016_j_comcom_2021_07_009 crossref_primary_10_1109_ACCESS_2022_3203568 crossref_primary_10_3390_fi14070216 crossref_primary_10_1016_j_jisa_2024_103725 crossref_primary_10_1007_s10586_021_03260_0 crossref_primary_10_1080_10447318_2021_2012381 crossref_primary_10_1007_s10207_023_00808_6 crossref_primary_10_1016_j_cities_2025_105883 crossref_primary_10_1109_MNET_001_1900225 crossref_primary_10_1109_JSAC_2020_2986619 crossref_primary_10_1016_j_comcom_2021_10_028 crossref_primary_10_1016_j_jksuci_2024_102039 crossref_primary_10_1016_j_future_2022_02_012 crossref_primary_10_1016_j_scs_2022_103678 crossref_primary_10_3390_su151612516 crossref_primary_10_1109_ACCESS_2020_3037474 crossref_primary_10_1016_j_jpdc_2021_04_003 crossref_primary_10_1109_JIOT_2021_3085004 crossref_primary_10_1016_j_joitmc_2023_100068 crossref_primary_10_1016_j_jnca_2020_102886 crossref_primary_10_1109_JIOT_2019_2951619 crossref_primary_10_3390_s23218958 crossref_primary_10_3390_app13021079 crossref_primary_10_1002_dac_70259 crossref_primary_10_1109_TCSS_2020_2990103 crossref_primary_10_1109_JIOT_2024_3507746 crossref_primary_10_2478_amns_2024_3122 crossref_primary_10_1145_3539734 crossref_primary_10_1007_s41060_023_00436_2 crossref_primary_10_1016_j_compeleceng_2025_110146 crossref_primary_10_1109_ACCESS_2023_3323932 crossref_primary_10_1007_s13042_025_02698_7 crossref_primary_10_1016_j_iot_2020_100227 crossref_primary_10_1109_JIOT_2020_3030080 crossref_primary_10_1016_j_future_2019_12_017 crossref_primary_10_1007_s00500_021_05866_3 crossref_primary_10_1002_ett_70130 crossref_primary_10_1007_s11277_023_10664_1 crossref_primary_10_2478_emj_2021_0017 crossref_primary_10_1016_j_health_2023_100221 crossref_primary_10_3390_s23177474 crossref_primary_10_4018_JGIM_332815 crossref_primary_10_1109_JIOT_2019_2959124 crossref_primary_10_1109_JIOT_2024_3505554 crossref_primary_10_1016_j_jisa_2020_102683 crossref_primary_10_1109_TCOMM_2020_2990686 crossref_primary_10_3390_s22124645 crossref_primary_10_1109_JIOT_2020_3028110 crossref_primary_10_1007_s43538_023_00202_9 crossref_primary_10_1109_JIOT_2023_3264611 crossref_primary_10_3390_electronics12040858 crossref_primary_10_1109_JIOT_2022_3185289 crossref_primary_10_1016_j_eswa_2023_121180 crossref_primary_10_1109_JIOT_2023_3347492 crossref_primary_10_1109_MNET_011_2000400 crossref_primary_10_1109_TSC_2022_3177438 crossref_primary_10_1109_ACCESS_2022_3159798 crossref_primary_10_3390_math11092073 crossref_primary_10_1109_JIOT_2019_2962070 crossref_primary_10_1109_TVT_2019_2943118 crossref_primary_10_1109_TPDS_2023_3240883 crossref_primary_10_1109_JSEN_2025_3526807 crossref_primary_10_3390_su15043317 crossref_primary_10_1109_ACCESS_2020_2973178 crossref_primary_10_1109_JIOT_2020_3015716 crossref_primary_10_1002_ett_4329 crossref_primary_10_1146_annurev_chembioeng_092120_022935 crossref_primary_10_3390_agriculture12010040 crossref_primary_10_1016_j_scs_2021_103083 crossref_primary_10_1109_ACCESS_2021_3065412 crossref_primary_10_1002_joe_22242 crossref_primary_10_1109_JIOT_2020_3033131 crossref_primary_10_1007_s11277_020_07389_w crossref_primary_10_1109_TII_2020_3040171 crossref_primary_10_1016_j_patrec_2021_01_019 crossref_primary_10_3390_app12125893 crossref_primary_10_1109_TCSI_2024_3427681 crossref_primary_10_1109_TSC_2022_3194121 crossref_primary_10_3390_electronics9050773 crossref_primary_10_3390_math12101480 crossref_primary_10_1088_2631_8695_ad5d51 crossref_primary_10_1016_j_comcom_2022_07_035 crossref_primary_10_1109_JIOT_2019_2963701 crossref_primary_10_1109_TITS_2022_3157447 crossref_primary_10_1109_COMST_2024_3353265 crossref_primary_10_1109_JIOT_2021_3108527 crossref_primary_10_1155_2021_6672482 crossref_primary_10_1007_s11390_020_9638_7 crossref_primary_10_1016_j_heliyon_2023_e19380 crossref_primary_10_1016_j_sysarc_2023_102961 crossref_primary_10_1016_j_inhs_2025_100011 crossref_primary_10_1109_JSEN_2020_3035846 crossref_primary_10_1016_j_future_2023_03_036 crossref_primary_10_1016_j_iotcps_2022_05_006 crossref_primary_10_1109_ACCESS_2024_3364078 crossref_primary_10_1002_cjs_11623 crossref_primary_10_3390_s21010028 crossref_primary_10_1007_s41060_024_00633_7 crossref_primary_10_1016_j_jnca_2019_102481 crossref_primary_10_1109_JIOT_2019_2960526 crossref_primary_10_1007_s42979_024_03383_2 crossref_primary_10_1109_JIOT_2021_3103855 crossref_primary_10_1016_j_future_2022_05_025 crossref_primary_10_1109_TDSC_2021_3119897 crossref_primary_10_1109_TTE_2023_3334826 crossref_primary_10_1111_exsy_12753 crossref_primary_10_1016_j_iot_2023_100780 crossref_primary_10_1109_TNSM_2023_3308331 crossref_primary_10_1109_ACCESS_2021_3051602 crossref_primary_10_1109_JIOT_2019_2963245 crossref_primary_10_1109_JIOT_2020_3004231 crossref_primary_10_3390_smartcities6020037 crossref_primary_10_1109_TNSE_2021_3050781 crossref_primary_10_1177_15501477211026804 crossref_primary_10_1007_s13198_024_02646_8 crossref_primary_10_1016_j_comnet_2021_108512 crossref_primary_10_1109_ACCESS_2021_3139176 crossref_primary_10_1007_s11265_020_01529_y crossref_primary_10_1016_j_cose_2024_103705 crossref_primary_10_1016_j_cose_2025_104473 crossref_primary_10_1109_TSMC_2023_3348449 crossref_primary_10_1109_JSAC_2020_2980916 crossref_primary_10_1109_JSEN_2020_3001382 crossref_primary_10_1002_int_22907 crossref_primary_10_1016_j_future_2020_06_025 crossref_primary_10_1016_j_jnca_2023_103696 crossref_primary_10_1016_j_jnca_2021_103050 crossref_primary_10_1007_s11235_023_01030_4 crossref_primary_10_1109_MNET_001_1800503 crossref_primary_10_3390_s25113341 crossref_primary_10_1109_COMST_2022_3175453 crossref_primary_10_1007_s11277_024_11050_1 crossref_primary_10_1109_TBDATA_2024_3403388 crossref_primary_10_3233_AIS_210601 crossref_primary_10_1016_j_pmcj_2020_101195 crossref_primary_10_1007_s10586_024_04509_0 crossref_primary_10_1109_ACCESS_2022_3181718 crossref_primary_10_1109_JIOT_2022_3191671 crossref_primary_10_1365_s43439_025_00145_5 crossref_primary_10_3390_s23031252 crossref_primary_10_1016_j_comcom_2023_04_020 crossref_primary_10_1109_JIOT_2023_3268705 crossref_primary_10_1016_j_icte_2023_03_006 crossref_primary_10_3390_electronics9122096 crossref_primary_10_1109_ACCESS_2023_3319083 crossref_primary_10_1007_s12083_022_01338_z crossref_primary_10_1007_s10489_021_02222_8 crossref_primary_10_1109_TII_2020_2968923 crossref_primary_10_3390_su16156669 crossref_primary_10_3390_urbansci9040132 crossref_primary_10_1109_ACCESS_2019_2936043 crossref_primary_10_3390_s22134730 crossref_primary_10_1016_j_future_2024_107564 crossref_primary_10_1016_j_cosrev_2025_100789 crossref_primary_10_1016_j_compeleceng_2023_108640 crossref_primary_10_1007_s12083_023_01592_9 crossref_primary_10_3390_foods11152262 crossref_primary_10_1109_JIOT_2021_3134755 crossref_primary_10_1007_s11708_022_0818_8 crossref_primary_10_1038_s41598_025_13831_5 crossref_primary_10_3390_su142316002 crossref_primary_10_1007_s42979_021_00841_z crossref_primary_10_3390_app15084562 crossref_primary_10_1002_dac_5669 crossref_primary_10_1007_s00354_021_00131_5 crossref_primary_10_1016_j_scs_2020_102360 crossref_primary_10_3390_a14080242 crossref_primary_10_1007_s11831_025_10309_5 crossref_primary_10_1016_j_scs_2020_102364 crossref_primary_10_1109_TDSC_2020_3026631 crossref_primary_10_3390_s24196377 crossref_primary_10_1109_COMST_2024_3430368 crossref_primary_10_1007_s10586_024_04387_6 crossref_primary_10_1109_TNET_2024_3436862 crossref_primary_10_1016_j_iot_2025_101752 crossref_primary_10_1016_j_jii_2023_100504 crossref_primary_10_3390_smartcities5040071 crossref_primary_10_1016_j_compeleceng_2023_109067 crossref_primary_10_1109_JIOT_2020_3008906 crossref_primary_10_1016_j_isatra_2021_09_007 crossref_primary_10_1109_JIOT_2020_3032797 crossref_primary_10_3390_s22239271 crossref_primary_10_1109_JIOT_2021_3097996 crossref_primary_10_1016_j_jii_2021_100261 crossref_primary_10_1145_3512893 crossref_primary_10_1016_j_iot_2022_100568 |
| Cites_doi | 10.1016/j.patcog.2017.06.016 10.1109/TIFS.2017.2774451 10.1016/j.comcom.2007.04.009 10.1201/b17668 10.1016/j.adhoc.2006.05.012 10.1016/0002-9149(89)90524-9 10.1007/s10916-018-0997-3 10.1109/JSAC.2018.2815442 10.1007/s11045-016-0408-1 10.1109/TIFS.2017.2692682 10.1145/2857705.2857731 10.1109/MNET.2012.6201210 10.1109/JBHI.2015.2407157 10.1145/2976749.2978318 10.1109/MNET.2018.1700269 10.1109/TDSC.2013.51 10.1587/transinf.2015INP0020 10.1109/JBHI.2016.2548248 10.1109/INFOCOM.2017.8056955 10.1109/ICCV.2017.97 10.1007/BF00994018 10.1109/TDSC.2013.43 10.1109/JIOT.2018.2871607 10.1109/TDSC.2017.2679189 10.1007/s001459910006 10.1109/TWC.2009.060598 |
| ContentType | Journal Article |
| Copyright | Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2019 |
| Copyright_xml | – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2019 |
| DBID | 97E RIA RIE AAYXX CITATION 7SC 8FD JQ2 L7M L~C L~D |
| DOI | 10.1109/JIOT.2019.2901840 |
| DatabaseName | IEEE All-Society Periodicals Package (ASPP) 2005–Present IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) CrossRef Computer and Information Systems Abstracts Technology Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional |
| DatabaseTitle | CrossRef Computer and Information Systems Abstracts Technology Research Database Computer and Information Systems Abstracts – Academic Advanced Technologies Database with Aerospace ProQuest Computer Science Collection Computer and Information Systems Abstracts Professional |
| DatabaseTitleList | Computer and Information Systems Abstracts |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| EISSN | 2327-4662 |
| EndPage | 7712 |
| ExternalDocumentID | 10_1109_JIOT_2019_2901840 8653362 |
| Genre | orig-research |
| GrantInformation_xml | – fundername: National Natural Science Foundation of China grantid: 61602039; 61872041 funderid: 10.13039/501100001809 – fundername: National Basic Research Program of China (973 Program); National Key Research and Development Program of China grantid: 2018YFB0803405 funderid: 10.13039/501100012166 – fundername: CCF-Tencent Open Fund WeBank Special Funding – fundername: Natural Science Foundation of Beijing Municipality grantid: 4192050 funderid: 10.13039/501100004826 |
| GroupedDBID | 0R~ 4.4 6IK 97E AAJGR AARMG AASAJ AAWTH ABAZT ABJNI ABQJQ ABVLG AGQYO AGSQL AHBIQ AKJIK AKQYR ALMA_UNASSIGNED_HOLDINGS ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ EBS EJD IFIPE IPLJI JAVBF M43 OCL PQQKQ RIA RIE AAYXX CITATION 7SC 8FD JQ2 L7M L~C L~D RIG |
| ID | FETCH-LOGICAL-c359t-3d9aece6dfc53a6e1ec12271cd218561a9afac87749fa95b0bb336c33e36647b3 |
| IEDL.DBID | RIE |
| ISICitedReferencesCount | 286 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000491295800031&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 2327-4662 |
| IngestDate | Mon Jun 30 13:16:07 EDT 2025 Tue Nov 18 22:49:30 EST 2025 Sat Nov 29 06:16:46 EST 2025 Wed Aug 27 08:33:24 EDT 2025 |
| IsPeerReviewed | false |
| IsScholarly | true |
| Issue | 5 |
| Language | English |
| License | https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html https://doi.org/10.15223/policy-029 https://doi.org/10.15223/policy-037 |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c359t-3d9aece6dfc53a6e1ec12271cd218561a9afac87749fa95b0bb336c33e36647b3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ORCID | 0000-0003-3277-3887 0000-0002-1867-0972 0000-0002-8972-8094 0000-0003-4235-9671 |
| PQID | 2303983346 |
| PQPubID | 2040421 |
| PageCount | 11 |
| ParticipantIDs | proquest_journals_2303983346 ieee_primary_8653362 crossref_citationtrail_10_1109_JIOT_2019_2901840 crossref_primary_10_1109_JIOT_2019_2901840 |
| PublicationCentury | 2000 |
| PublicationDate | 2019-10-01 |
| PublicationDateYYYYMMDD | 2019-10-01 |
| PublicationDate_xml | – month: 10 year: 2019 text: 2019-10-01 day: 01 |
| PublicationDecade | 2010 |
| PublicationPlace | Piscataway |
| PublicationPlace_xml | – name: Piscataway |
| PublicationTitle | IEEE internet of things journal |
| PublicationTitleAbbrev | JIoT |
| PublicationYear | 2019 |
| Publisher | IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher_xml | – name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| References | graepel (ref13) 2012 ref15 ref14 ref11 ref32 ref2 ref1 ref17 ref16 ref19 ref18 goldreich (ref21) 2009 ref24 ref23 bost (ref5) 2014 ref26 ref25 ref20 ref22 ref28 ref27 ref29 ref8 ref7 ref9 ref4 ref3 dua (ref31) 2017 katz (ref10) 2014 de cock (ref12) 2015 ref6 platt (ref30) 1998 |
| References_xml | – year: 2017 ident: ref31 publication-title: UCI Machine Learning Repository – ident: ref11 doi: 10.1016/j.patcog.2017.06.016 – ident: ref4 doi: 10.1109/TIFS.2017.2774451 – ident: ref28 doi: 10.1016/j.comcom.2007.04.009 – year: 2014 ident: ref10 publication-title: Introduction to Modern Cryptography doi: 10.1201/b17668 – ident: ref29 doi: 10.1016/j.adhoc.2006.05.012 – year: 2012 ident: ref13 article-title: ML confidential: Machine learning on encrypted data publication-title: Information Security and Cryptology-ICISC – ident: ref32 doi: 10.1016/0002-9149(89)90524-9 – ident: ref9 doi: 10.1007/s10916-018-0997-3 – ident: ref26 doi: 10.1109/JSAC.2018.2815442 – ident: ref19 doi: 10.1007/s11045-016-0408-1 – ident: ref2 doi: 10.1109/TIFS.2017.2692682 – start-page: 1 year: 1998 ident: ref30 publication-title: Sequential minimal optimization A fast algorithm for training support vector machines – ident: ref17 doi: 10.1145/2857705.2857731 – ident: ref1 doi: 10.1109/MNET.2012.6201210 – ident: ref14 doi: 10.1109/JBHI.2015.2407157 – ident: ref6 doi: 10.1145/2976749.2978318 – start-page: 3 year: 2015 ident: ref12 article-title: Fast, privacy preserving linear regression over distributed datasets based on pre-distributed data publication-title: Proceedings of the 8th ACM Workshop on Artificial Intelligence and Security ACM – ident: ref24 doi: 10.1109/MNET.2018.1700269 – ident: ref8 doi: 10.1109/TDSC.2013.51 – start-page: 1 year: 2014 ident: ref5 article-title: Machine learning classification over encrypted data publication-title: Proc Symp Network and Distributed System Security – ident: ref16 doi: 10.1587/transinf.2015INP0020 – ident: ref20 doi: 10.1109/JBHI.2016.2548248 – ident: ref7 doi: 10.1109/INFOCOM.2017.8056955 – year: 2009 ident: ref21 publication-title: Foundations of Cryptography Volume 2 Basic Applications – ident: ref3 doi: 10.1109/ICCV.2017.97 – ident: ref23 doi: 10.1007/BF00994018 – ident: ref15 doi: 10.1109/TDSC.2013.43 – ident: ref25 doi: 10.1109/JIOT.2018.2871607 – ident: ref18 doi: 10.1109/TDSC.2017.2679189 – ident: ref22 doi: 10.1007/s001459910006 – ident: ref27 doi: 10.1109/TWC.2009.060598 |
| SSID | ssj0001105196 |
| Score | 2.6207457 |
| Snippet | Machine learning (ML) techniques have been widely used in many smart city sectors, where a huge amount of data is gathered from various (IoT) devices. As a... |
| SourceID | proquest crossref ieee |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 7702 |
| SubjectTerms | Algorithms Anomalies Blockchain Computational modeling Cryptography Data models Data privacy Data retrieval Distributed ledger encrypted Internet of Things (IoT) data Encryption homomorphic cryptosystem (HC) Internet of Things Iterative methods Machine learning machine learning (ML) Multiplication Polynomials Privacy privacy protection Smart cities Support vector machines Training Trusted third parties |
| Title | Privacy-Preserving Support Vector Machine Training Over Blockchain-Based Encrypted IoT Data in Smart Cities |
| URI | https://ieeexplore.ieee.org/document/8653362 https://www.proquest.com/docview/2303983346 |
| Volume | 6 |
| WOSCitedRecordID | wos000491295800031&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVIEE databaseName: IEEE Electronic Library (IEL) customDbUrl: eissn: 2327-4662 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001105196 issn: 2327-4662 databaseCode: RIE dateStart: 20140101 isFulltext: true titleUrlDefault: https://ieeexplore.ieee.org/ providerName: IEEE |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LT8MwDI4AceDCGzEYKAdOiEK7rHkceQoQL4mBuFWp48A06NDYkPj3JFk2kEBI3Koqqdp-dvzFdmxCtiyTwijMkowZmzTzUial10erpAFtM7frCkVcL8TVlXx4UDcTZGd8FgYRQ_IZ7vrLEMs3XRh4V9me5I6c-AV3Ugg-PKv15U_JPBnhMXCZpWrv_Oy65XO31K6PFUrv3vhmekIvlR8LcLAqJ3P_e595MhvZI90fwr1AJrBaJHOjzgw0KuoS6dz02u8aPhKfYeFXg-qR-v6djmvT--Cnp5chixJpK_aIoNdOqOmBs20deHK3kgNn3ww9rqD38epoKT3rtuiR7mvarujti5M4ehiqsS6Tu5Pj1uFpEtsqJMBy1U-YURoBubGQM80xQ8gaDZGBcebe0SmttNUgHS9UVqu8TMvSfSUwhozzpijZCpmquhWuEgoSGiWyHATaJtNC5cBTjUYJi6htXiPp6I8XEGuO-9YXz0XYe6Sq8CAVHqQiglQj2-Mpr8OCG38NXvKojAdGQGqkPoK1iCr5Vri9FlOSsSZf-33WOpnxzx5m6tXJVL83wA0yDe_99ltvM0jbJ_Cw1UM |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3fT9swED4hhrS9wDY2UcY2P-xpWiCpm8R-BAaiWylIyybeIud83iogRaUg8d_jc91u0hASb1FkKz8-2_f57nwfwCcnVWk1ZUkmrUt6eaOShuej08qicZnfdYUiroNyOFRnZ_p0Cb4szsIQUUg-o22-DLF8O8YbdpXtqMKTE15wn7FyVjyt9dejkjEdKWLoMkv1zrf-ScXZW3qbo4WKHRz_GJ-gpvLfEhzsyuHa097oJaxG_ih2Z4C_giVqX8PaXJtBxKm6Duenk9GtwbuEcyx4PWh_C1bw9Gxb_AqeenEc8ihJVFElQpz4YS32vHU7xz_-VrLnLZwVBy1O7q48MRX9cSW-mqkRo1b8uPRjTuyHeqxv4OfhQbV_lERhhQRlrqeJtNoQUmEd5tIUlBFm3W6ZofUG3xMqo40zqDwz1M7ovEmbxn8lSkmyKHplI9_CcjtuaQMEKuw2JHMsyfWkKXWORWrI6tIRGZd3IJ3_8Rpj1XEWv7iow-4j1TWDVDNIdQSpA58XXa5mJTcea7zOqCwaRkA6sDWHtY6T8rr2uy2plZS9YvPhXh_h-VF1PKgH_eH3d_CCnzPL29uC5enkht7DCt5OR9eTD2Hk3QMx79iM |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Privacy-Preserving+Support+Vector+Machine+Training+Over+Blockchain-Based+Encrypted+IoT+Data+in+Smart+Cities&rft.jtitle=IEEE+internet+of+things+journal&rft.au=Shen%2C+Meng&rft.au=Tang%2C+Xiangyun&rft.au=Zhu%2C+Liehuang&rft.au=Du%2C+Xiaojiang&rft.date=2019-10-01&rft.pub=IEEE&rft.eissn=2327-4662&rft.volume=6&rft.issue=5&rft.spage=7702&rft.epage=7712&rft_id=info:doi/10.1109%2FJIOT.2019.2901840&rft.externalDocID=8653362 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2327-4662&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2327-4662&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2327-4662&client=summon |