Blockchain and Machine Learning for Communications and Networking Systems
Recently, with the rapid development of information and communication technologies, the infrastructures, resources, end devices, and applications in communications and networking systems are becoming much more complex and heterogeneous. In addition, the large volume of data and massive end devices m...
Gespeichert in:
| Veröffentlicht in: | IEEE Communications surveys and tutorials Jg. 22; H. 2; S. 1392 - 1431 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
IEEE
01.01.2020
|
| Schlagworte: | |
| ISSN: | 2373-745X |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | Recently, with the rapid development of information and communication technologies, the infrastructures, resources, end devices, and applications in communications and networking systems are becoming much more complex and heterogeneous. In addition, the large volume of data and massive end devices may bring serious security, privacy, services provisioning, and network management challenges. In order to achieve decentralized, secure, intelligent, and efficient network operation and management, the joint consideration of blockchain and machine learning (ML) may bring significant benefits and have attracted great interests from both academia and industry. On one hand, blockchain can significantly facilitate training data and ML model sharing, decentralized intelligence, security, privacy, and trusted decision-making of ML. On the other hand, ML will have significant impacts on the development of blockchain in communications and networking systems, including energy and resource efficiency, scalability, security, privacy, and intelligent smart contracts. However, some essential open issues and challenges that remain to be addressed before the widespread deployment of the integration of blockchain and ML, including resource management, data processing, scalable operation, and security issues. In this paper, we present a survey on the existing works for blockchain and ML technologies. We identify several important aspects of integrating blockchain and ML, including overview, benefits, and applications. Then we discuss some open issues, challenges, and broader perspectives that need to be addressed to jointly consider blockchain and ML for communications and networking systems. |
|---|---|
| AbstractList | Recently, with the rapid development of information and communication technologies, the infrastructures, resources, end devices, and applications in communications and networking systems are becoming much more complex and heterogeneous. In addition, the large volume of data and massive end devices may bring serious security, privacy, services provisioning, and network management challenges. In order to achieve decentralized, secure, intelligent, and efficient network operation and management, the joint consideration of blockchain and machine learning (ML) may bring significant benefits and have attracted great interests from both academia and industry. On one hand, blockchain can significantly facilitate training data and ML model sharing, decentralized intelligence, security, privacy, and trusted decision-making of ML. On the other hand, ML will have significant impacts on the development of blockchain in communications and networking systems, including energy and resource efficiency, scalability, security, privacy, and intelligent smart contracts. However, some essential open issues and challenges that remain to be addressed before the widespread deployment of the integration of blockchain and ML, including resource management, data processing, scalable operation, and security issues. In this paper, we present a survey on the existing works for blockchain and ML technologies. We identify several important aspects of integrating blockchain and ML, including overview, benefits, and applications. Then we discuss some open issues, challenges, and broader perspectives that need to be addressed to jointly consider blockchain and ML for communications and networking systems. |
| Author | Liu, Yiming Leung, Victor C. M. Ji, Hong Yu, F. Richard Li, Xi |
| Author_xml | – sequence: 1 givenname: Yiming orcidid: 0000-0001-8824-4007 surname: Liu fullname: Liu, Yiming email: liuyiming@bput.edu.cn organization: Ministry of Education, Key Laboratory of Universal Wireless Communications, Beijing – sequence: 2 givenname: F. Richard orcidid: 0000-0003-1006-7594 surname: Yu fullname: Yu, F. Richard email: richard.yu@carleton.ca organization: Department of Systems and Computer Engineering, Carleton University, Ottawa, Canada – sequence: 3 givenname: Xi orcidid: 0000-0003-0466-1933 surname: Li fullname: Li, Xi email: lixi@bupt.edu.cn organization: Ministry of Education, Key Laboratory of Universal Wireless Communications, Beijing – sequence: 4 givenname: Hong orcidid: 0000-0002-1640-2894 surname: Ji fullname: Ji, Hong email: jihong@bupt.edu.cn organization: Ministry of Education, Key Laboratory of Universal Wireless Communications, Beijing – sequence: 5 givenname: Victor C. M. orcidid: 0000-0003-3529-2640 surname: Leung fullname: Leung, Victor C. M. email: vleung@ieee.org organization: College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China |
| BookMark | eNotjslOwzAURS0EEm3hB2CTH0h4nuJ4CRFDpZQuWiR2lUdq2tgoDkL9e8qwOptzru4UncYUHUJXGCqMQd60y8VqXREgUBEpuMT4BE0IFbQUjL-eo2nO7wCMMAkTNL_bJ7MzWxVioaItFspsQ3RF59QQQ3wrfBqKNvX9ZwxGjSHF_Os9u_ErDbsfY3XIo-vzBTrzap_d5T9n6OXhft0-ld3ycd7edqUhko8lV5oapbEB0No6rE3dUO2cZdgIxa09XmukkFIY3PjGU2W9l1IfYw5M1XSGrv92g3Nu8zGEXg2HjQQQDGr6DanhTU8 |
| CitedBy_id | crossref_primary_10_3390_e27090933 crossref_primary_10_1109_COMST_2023_3315374 crossref_primary_10_1007_s11042_021_11604_6 crossref_primary_10_3233_JIFS_213482 crossref_primary_10_3390_s21093194 crossref_primary_10_1109_JIOT_2021_3135342 crossref_primary_10_1145_3659946 crossref_primary_10_32628_CSEIT241051055 crossref_primary_10_1109_ACCESS_2024_3384460 crossref_primary_10_1109_COMST_2023_3280465 crossref_primary_10_1109_JIOT_2020_3032162 crossref_primary_10_1109_ACCESS_2022_3210584 crossref_primary_10_3390_s24103111 crossref_primary_10_1109_ACCESS_2023_3344669 crossref_primary_10_1016_j_aei_2025_103616 crossref_primary_10_1109_COMST_2021_3115797 crossref_primary_10_1109_JIOT_2020_3027482 crossref_primary_10_1109_TCOMM_2023_3337376 crossref_primary_10_1007_s10660_024_09923_5 crossref_primary_10_1145_3700641 crossref_primary_10_1016_j_icte_2021_08_014 crossref_primary_10_1016_j_icte_2025_04_001 crossref_primary_10_1109_TQE_2024_3481280 crossref_primary_10_1016_j_jnca_2021_103245 crossref_primary_10_1155_2024_9979371 crossref_primary_10_3390_biomedicines11082225 crossref_primary_10_1109_JIOT_2022_3181556 crossref_primary_10_1109_JIOT_2023_3315673 crossref_primary_10_1080_23311975_2025_2474209 crossref_primary_10_1109_TGCN_2021_3132561 crossref_primary_10_1016_j_comnet_2023_110137 crossref_primary_10_1016_j_jclepro_2023_138466 crossref_primary_10_3390_fi16120449 crossref_primary_10_1109_ACCESS_2024_3482389 crossref_primary_10_1038_s41598_022_17671_5 crossref_primary_10_1109_ACCESS_2020_3007251 crossref_primary_10_1109_ACCESS_2024_3462735 crossref_primary_10_1109_JIOT_2022_3197989 crossref_primary_10_1002_spy2_344 crossref_primary_10_1109_ACCESS_2025_3562126 crossref_primary_10_3390_en16010528 crossref_primary_10_1080_19393555_2023_2218852 crossref_primary_10_1109_MNET_2024_3412161 crossref_primary_10_1007_s11276_024_03674_9 crossref_primary_10_1016_j_jnca_2020_102784 crossref_primary_10_3390_network3030017 crossref_primary_10_1002_ett_4133 crossref_primary_10_1016_j_cosrev_2022_100492 crossref_primary_10_1109_TII_2022_3179272 crossref_primary_10_1145_3441692 crossref_primary_10_1109_JAS_2023_123450 crossref_primary_10_1007_s13198_024_02596_1 crossref_primary_10_1109_MNET_115_2200014 crossref_primary_10_3390_computers12010006 crossref_primary_10_1007_s12083_023_01551_4 crossref_primary_10_1007_s10586_023_04108_5 crossref_primary_10_1016_j_jii_2022_100404 crossref_primary_10_1016_j_jksuci_2024_102207 crossref_primary_10_3390_s22239074 crossref_primary_10_1007_s10845_024_02535_8 crossref_primary_10_3390_fi15060200 crossref_primary_10_1007_s10479_023_05761_0 crossref_primary_10_1109_COMST_2022_3199544 crossref_primary_10_1109_TNSM_2022_3212917 crossref_primary_10_1186_s13677_021_00247_5 crossref_primary_10_1016_j_comcom_2021_07_009 crossref_primary_10_1109_JIOT_2021_3063686 crossref_primary_10_1109_ACCESS_2022_3203568 crossref_primary_10_1051_e3sconf_202449102024 crossref_primary_10_1109_TVT_2023_3344934 crossref_primary_10_1016_j_dcan_2024_09_005 crossref_primary_10_1016_j_jpdc_2020_06_003 crossref_primary_10_1109_TSMC_2023_3348449 crossref_primary_10_1007_s11276_021_02748_2 crossref_primary_10_1016_j_compeleceng_2025_110559 crossref_primary_10_1007_s11042_024_19993_0 crossref_primary_10_1109_MNET_011_2000508 crossref_primary_10_1007_s10796_022_10279_0 crossref_primary_10_1016_j_comnet_2021_108594 crossref_primary_10_1109_JPROC_2024_3386257 crossref_primary_10_3390_s25154793 crossref_primary_10_1109_COMST_2022_3175453 crossref_primary_10_1051_itmconf_20246301009 crossref_primary_10_1109_ACCESS_2022_3198956 crossref_primary_10_1109_COMST_2020_3045136 crossref_primary_10_1002_asi_70009 crossref_primary_10_1109_JIOT_2023_3279830 crossref_primary_10_1016_j_cosrev_2023_100575 crossref_primary_10_1109_TCSS_2023_3268592 crossref_primary_10_3390_electronics13122295 crossref_primary_10_1016_j_iot_2024_101276 crossref_primary_10_1109_COMST_2022_3189962 crossref_primary_10_1109_TCC_2022_3201544 crossref_primary_10_2139_ssrn_5164958 crossref_primary_10_1109_JIOT_2020_3028368 crossref_primary_10_1109_JIOT_2022_3222521 crossref_primary_10_1109_JIOT_2023_3268705 crossref_primary_10_1007_s10773_022_05097_8 crossref_primary_10_1016_j_sysarc_2020_101877 crossref_primary_10_1109_ACCESS_2025_3560781 crossref_primary_10_1109_COMST_2022_3208196 crossref_primary_10_1109_ACCESS_2023_3319083 crossref_primary_10_1186_s40854_023_00525_y crossref_primary_10_3390_fi13020048 crossref_primary_10_1109_TNSM_2021_3122147 crossref_primary_10_1016_j_resglo_2025_100275 crossref_primary_10_1109_ACCESS_2020_3003894 crossref_primary_10_1007_s10207_022_00653_z crossref_primary_10_1016_j_jnca_2023_103677 crossref_primary_10_1016_j_icte_2022_10_005 crossref_primary_10_1109_TITS_2025_3553403 crossref_primary_10_7717_peerj_cs_2268 crossref_primary_10_1109_COMST_2021_3086014 crossref_primary_10_3390_su142316002 crossref_primary_10_1007_s11276_025_03999_z crossref_primary_10_1051_itmconf_20246301011 crossref_primary_10_1002_ett_5009 crossref_primary_10_1016_j_engappai_2022_105581 crossref_primary_10_1007_s10586_023_04257_7 crossref_primary_10_1109_TEM_2021_3053655 crossref_primary_10_1109_ACCESS_2024_3429285 crossref_primary_10_1002_ett_4692 crossref_primary_10_1016_j_cosrev_2023_100590 crossref_primary_10_1109_TVT_2022_3150793 crossref_primary_10_1145_3560816 crossref_primary_10_1109_JIOT_2023_3347492 crossref_primary_10_1016_j_scs_2020_102364 crossref_primary_10_1109_ACCESS_2022_3151150 crossref_primary_10_1016_j_procs_2023_11_037 crossref_primary_10_1109_TII_2021_3097131 crossref_primary_10_1109_JIOT_2020_3025916 crossref_primary_10_3389_fbloc_2023_1206330 crossref_primary_10_1109_COMST_2022_3204702 crossref_primary_10_1109_COMST_2023_3305312 crossref_primary_10_1109_TMC_2023_3325334 crossref_primary_10_3390_en15218304 crossref_primary_10_1016_j_apenergy_2023_121321 crossref_primary_10_1016_j_comnet_2025_111284 crossref_primary_10_3233_JIFS_212455 crossref_primary_10_1016_j_infsof_2023_107221 crossref_primary_10_1109_TITS_2021_3106545 crossref_primary_10_1002_dac_5675 crossref_primary_10_1109_TMC_2024_3382776 crossref_primary_10_1093_nsr_nwab069 crossref_primary_10_1109_COMST_2022_3217613 |
| ContentType | Journal Article |
| DBID | 97E RIA RIE |
| DOI | 10.1109/COMST.2020.2975911 |
| DatabaseName | IEEE All-Society Periodicals Package (ASPP) 2005-present IEEE All-Society Periodicals Package (ASPP) 1998-Present IEEE Electronic Library (IEL) |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering |
| EISSN | 2373-745X |
| EndPage | 1431 |
| ExternalDocumentID | 9007406 |
| Genre | orig-research |
| GrantInformation_xml | – fundername: National Natural Science Foundation of China grantid: 61671088; 61771070 funderid: 10.13039/501100001809 – fundername: Canadian Natural Sciences and Engineering Research Council funderid: 10.13039/501100000038 – fundername: Chinese National Engineering Laboratory for Big Data System Computing Technology |
| GroupedDBID | 0R~ 29I 2WC 4.4 5GY 5VS 6IK 97E AAJGR AARMG AASAJ AAWTH ABAZT ABQJQ ABVLG ACGFO ACIWK AENEX AETIX AGQYO AGSQL AHBIQ AIBXA AKJIK AKQYR ALLEH ALMA_UNASSIGNED_HOLDINGS ATWAV AZLTO BEFXN BFFAM BGNUA BKEBE BPEOZ CS3 EBS EJD HZ~ IES IFIPE IFJZH IPLJI JAVBF LAI O9- OCL P2P RIA RIE RNS |
| ID | FETCH-LOGICAL-c295t-5ab3cab1c00bbde1bc683beed41c7a5dd004897997c18f8f3adff99b295504a63 |
| IEDL.DBID | RIE |
| ISICitedReferencesCount | 217 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000538038400020&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| IngestDate | Wed Aug 27 02:37:42 EDT 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 2 |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c295t-5ab3cab1c00bbde1bc683beed41c7a5dd004897997c18f8f3adff99b295504a63 |
| ORCID | 0000-0001-8824-4007 0000-0003-3529-2640 0000-0003-1006-7594 0000-0002-1640-2894 0000-0003-0466-1933 |
| PageCount | 40 |
| ParticipantIDs | ieee_primary_9007406 |
| PublicationCentury | 2000 |
| PublicationDate | 2020-01-01 |
| PublicationDateYYYYMMDD | 2020-01-01 |
| PublicationDate_xml | – month: 01 year: 2020 text: 2020-01-01 day: 01 |
| PublicationDecade | 2020 |
| PublicationTitle | IEEE Communications surveys and tutorials |
| PublicationTitleAbbrev | COMST |
| PublicationYear | 2020 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| SSID | ssj0042490 |
| Score | 2.6467474 |
| Snippet | Recently, with the rapid development of information and communication technologies, the infrastructures, resources, end devices, and applications in... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 1392 |
| SubjectTerms | Blockchain Contracts Data models Data privacy distributed ledger technology (DLT) Machine learning machine learning (ML) wireless communications wireless networks |
| Title | Blockchain and Machine Learning for Communications and Networking Systems |
| URI | https://ieeexplore.ieee.org/document/9007406 |
| Volume | 22 |
| WOSCitedRecordID | wos000538038400020&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 | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LSwMxEB5q8aAHX1V8k4NHt80mm2xy1GLRQ6tghd5KXqsibKXd-vtNslup4MXbErJZmJCd-TLzfQNwxbWjglidcONUkuUhSWgCOUfKQudaMcxVbDaRj0ZiMpFPLbj-4cI452LxmeuGx5jLtzOzDFdlPRkcXtDX3vBr1lyt1V838zACr0gxWPb6j8PnsYd_BHcDd1SGDkFr7VOi9xjs_u-7e7DTRInopt7WfWi58gC217QDO_Bw693Qh3nzyB6p0qJhrIp0qBFMfUU-GkW_6B-LOG9U132HGY1a-SG8DO7G_fuk6YuQGCJZlTClqVE6NRhrbV2qDRdUe2eXpSZXzNpwLEO6LjepKERBlS0KKbV_meFMcXoE7XJWumNABkuPprkhnFofOBElmLDEeRSjCXc5O4FOMMf0s5a-mDaWOP17-Ay2gsXrG4pzaFfzpbuATfNVvS_ml3G_vgG3mJgB |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LS8NAEB5KFdSDryq-3YNH02422c3uUYulxTYKVuit7CtVhFT68Pe7m6RSwYu3EDYEZtmd-Wbm-wbghikbcWJUwLSVQZz4IqH25BwhMpUoSTGTxbCJJE35aCSea3D7w4Wx1hbNZ7bpH4tavpnqpU-VtYR3eF5fe4PGMQlLttbq3o0dkMArWgwWrfbT4GXoACDBTc8eFX5G0NoAlcJ_dPb-9-d92K3iRHRXbuwB1Gx-CDtr6oEN6N07R_Sh3xy2RzI3aFD0RVpUSaZOkItH0S8CyLxYl5ad335FpVd-BK-dh2G7G1STEQJNBF0EVKpISxVqjJUyNlSa8Ug5dxeHOpHUGH8wfcEu0SHPeBZJk2VCKPcxxbFk0THU82luTwBpLByeZpqwyLjQiUhOuSHW4RhFmE3oKTS8OcafpfjFuLLE2d-vr2GrOxz0x_1e-ngO2976Zb7iAuqL2dJewqb-WrzPZ1fF3n0D0BKbSA |
| 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=Blockchain+and+Machine+Learning+for+Communications+and+Networking+Systems&rft.jtitle=IEEE+Communications+surveys+and+tutorials&rft.au=Liu%2C+Yiming&rft.au=Yu%2C+F.+Richard&rft.au=Li%2C+Xi&rft.au=Ji%2C+Hong&rft.date=2020-01-01&rft.pub=IEEE&rft.eissn=2373-745X&rft.volume=22&rft.issue=2&rft.spage=1392&rft.epage=1431&rft_id=info:doi/10.1109%2FCOMST.2020.2975911&rft.externalDocID=9007406 |