Smart Evolution for Information Diffusion Over Social Networks

In social network, the existence of malicious users can create lots of detrimental consequences. To diminish their negative influences, it is necessary for rational users to identify and interact with each neighbor carefully to protect themselves from malicious ones. Therefore, it is crucial to esta...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on information forensics and security 2021, Vol.16, p.1203-1217
Hauptverfasser: Zhang, Hangjing, Li, Yuejiang, Chen, Yan, Zhao, H. Vicky
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 1217
container_issue
container_start_page 1203
container_title IEEE transactions on information forensics and security
container_volume 16
creator Zhang, Hangjing
Li, Yuejiang
Chen, Yan
Zhao, H. Vicky
description In social network, the existence of malicious users can create lots of detrimental consequences. To diminish their negative influences, it is necessary for rational users to identify and interact with each neighbor carefully to protect themselves from malicious ones. Therefore, it is crucial to establish a rule for users' interaction in order to mitigate malicious users' influences. In this paper, we propose a smart evolution model based on evolutionary game theory by introducing the reputation mechanism. The model takes into account both current reputation and instant incentives during users' decision-making process. On the basis of whether users share reputation values with others, we introduce schemes without reciprocity principle and with the indirect reciprocity principle respectively. With the social norm and reputation updating policy, we theoretically analyze the evolutionary dynamics and corresponding ESSs by explicitly considering the effects of malicious users. Finally, simulations based on synthetic networks and real-world data are conducted to validate the effectiveness of the proposed smart evolution model.
doi_str_mv 10.1109/TIFS.2020.3032039
format Article
fullrecord <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_crossref_primary_10_1109_TIFS_2020_3032039</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9229115</ieee_id><sourcerecordid>2460161883</sourcerecordid><originalsourceid>FETCH-LOGICAL-c293t-edee54e0f82721d00692ac55618688dc18509315e7d6c09f695be492715ecb283</originalsourceid><addsrcrecordid>eNo9UE1PAjEQbYwmIvoDjJdNPC_OtNvSXkwMgpIQOYDnZum2ySJQbHcx_nu7QrjMvJm8Nx-PkHuEASKop-V0shhQoDBgwCgwdUF6yLnIBVC8PGNk1-QmxjVAUaCQPfK82JahycYHv2mb2u8y50M23aW4Lf_r19q5NnZofrAhW3hTl5vswzY_PnzFW3Llyk20d6fcJ5-T8XL0ns_mb9PRyyw3VLEmt5W1vLDgJB1SrACEoqVJJ6EUUlYGJQfFkNthJQwoJxRf2ULRYWqZFZWsTx6Pc_fBf7c2Nnrt27BLKzUt0ltpkGSJhUeWCT7GYJ3ehzr996sRdGeT7mzSnU36ZFPSPBw1tbX2zFeUKkTO_gBL02Is</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2460161883</pqid></control><display><type>article</type><title>Smart Evolution for Information Diffusion Over Social Networks</title><source>IEEE Electronic Library (IEL)</source><creator>Zhang, Hangjing ; Li, Yuejiang ; Chen, Yan ; Zhao, H. Vicky</creator><creatorcontrib>Zhang, Hangjing ; Li, Yuejiang ; Chen, Yan ; Zhao, H. Vicky</creatorcontrib><description>In social network, the existence of malicious users can create lots of detrimental consequences. To diminish their negative influences, it is necessary for rational users to identify and interact with each neighbor carefully to protect themselves from malicious ones. Therefore, it is crucial to establish a rule for users' interaction in order to mitigate malicious users' influences. In this paper, we propose a smart evolution model based on evolutionary game theory by introducing the reputation mechanism. The model takes into account both current reputation and instant incentives during users' decision-making process. On the basis of whether users share reputation values with others, we introduce schemes without reciprocity principle and with the indirect reciprocity principle respectively. With the social norm and reputation updating policy, we theoretically analyze the evolutionary dynamics and corresponding ESSs by explicitly considering the effects of malicious users. Finally, simulations based on synthetic networks and real-world data are conducted to validate the effectiveness of the proposed smart evolution model.</description><identifier>ISSN: 1556-6013</identifier><identifier>EISSN: 1556-6021</identifier><identifier>DOI: 10.1109/TIFS.2020.3032039</identifier><identifier>CODEN: ITIFA6</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Data models ; Decision making ; Diffusion processes ; Evolution ; evolutionary game theory ; Game theory ; Games ; Incentives ; information diffusion ; Information dissemination ; malicious users ; Reciprocity ; Reputation ; Reputations ; Social networking (online) ; Social networks ; Sociology ; Statistics</subject><ispartof>IEEE transactions on information forensics and security, 2021, Vol.16, p.1203-1217</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c293t-edee54e0f82721d00692ac55618688dc18509315e7d6c09f695be492715ecb283</citedby><cites>FETCH-LOGICAL-c293t-edee54e0f82721d00692ac55618688dc18509315e7d6c09f695be492715ecb283</cites><orcidid>0000-0002-3690-9924 ; 0000-0002-3227-4562</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9229115$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,4010,27900,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9229115$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Zhang, Hangjing</creatorcontrib><creatorcontrib>Li, Yuejiang</creatorcontrib><creatorcontrib>Chen, Yan</creatorcontrib><creatorcontrib>Zhao, H. Vicky</creatorcontrib><title>Smart Evolution for Information Diffusion Over Social Networks</title><title>IEEE transactions on information forensics and security</title><addtitle>TIFS</addtitle><description>In social network, the existence of malicious users can create lots of detrimental consequences. To diminish their negative influences, it is necessary for rational users to identify and interact with each neighbor carefully to protect themselves from malicious ones. Therefore, it is crucial to establish a rule for users' interaction in order to mitigate malicious users' influences. In this paper, we propose a smart evolution model based on evolutionary game theory by introducing the reputation mechanism. The model takes into account both current reputation and instant incentives during users' decision-making process. On the basis of whether users share reputation values with others, we introduce schemes without reciprocity principle and with the indirect reciprocity principle respectively. With the social norm and reputation updating policy, we theoretically analyze the evolutionary dynamics and corresponding ESSs by explicitly considering the effects of malicious users. Finally, simulations based on synthetic networks and real-world data are conducted to validate the effectiveness of the proposed smart evolution model.</description><subject>Data models</subject><subject>Decision making</subject><subject>Diffusion processes</subject><subject>Evolution</subject><subject>evolutionary game theory</subject><subject>Game theory</subject><subject>Games</subject><subject>Incentives</subject><subject>information diffusion</subject><subject>Information dissemination</subject><subject>malicious users</subject><subject>Reciprocity</subject><subject>Reputation</subject><subject>Reputations</subject><subject>Social networking (online)</subject><subject>Social networks</subject><subject>Sociology</subject><subject>Statistics</subject><issn>1556-6013</issn><issn>1556-6021</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9UE1PAjEQbYwmIvoDjJdNPC_OtNvSXkwMgpIQOYDnZum2ySJQbHcx_nu7QrjMvJm8Nx-PkHuEASKop-V0shhQoDBgwCgwdUF6yLnIBVC8PGNk1-QmxjVAUaCQPfK82JahycYHv2mb2u8y50M23aW4Lf_r19q5NnZofrAhW3hTl5vswzY_PnzFW3Llyk20d6fcJ5-T8XL0ns_mb9PRyyw3VLEmt5W1vLDgJB1SrACEoqVJJ6EUUlYGJQfFkNthJQwoJxRf2ULRYWqZFZWsTx6Pc_fBf7c2Nnrt27BLKzUt0ltpkGSJhUeWCT7GYJ3ehzr996sRdGeT7mzSnU36ZFPSPBw1tbX2zFeUKkTO_gBL02Is</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>Zhang, Hangjing</creator><creator>Li, Yuejiang</creator><creator>Chen, Yan</creator><creator>Zhao, H. Vicky</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-3690-9924</orcidid><orcidid>https://orcid.org/0000-0002-3227-4562</orcidid></search><sort><creationdate>2021</creationdate><title>Smart Evolution for Information Diffusion Over Social Networks</title><author>Zhang, Hangjing ; Li, Yuejiang ; Chen, Yan ; Zhao, H. Vicky</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c293t-edee54e0f82721d00692ac55618688dc18509315e7d6c09f695be492715ecb283</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Data models</topic><topic>Decision making</topic><topic>Diffusion processes</topic><topic>Evolution</topic><topic>evolutionary game theory</topic><topic>Game theory</topic><topic>Games</topic><topic>Incentives</topic><topic>information diffusion</topic><topic>Information dissemination</topic><topic>malicious users</topic><topic>Reciprocity</topic><topic>Reputation</topic><topic>Reputations</topic><topic>Social networking (online)</topic><topic>Social networks</topic><topic>Sociology</topic><topic>Statistics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Hangjing</creatorcontrib><creatorcontrib>Li, Yuejiang</creatorcontrib><creatorcontrib>Chen, Yan</creatorcontrib><creatorcontrib>Zhao, H. Vicky</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on information forensics and security</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Zhang, Hangjing</au><au>Li, Yuejiang</au><au>Chen, Yan</au><au>Zhao, H. Vicky</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Smart Evolution for Information Diffusion Over Social Networks</atitle><jtitle>IEEE transactions on information forensics and security</jtitle><stitle>TIFS</stitle><date>2021</date><risdate>2021</risdate><volume>16</volume><spage>1203</spage><epage>1217</epage><pages>1203-1217</pages><issn>1556-6013</issn><eissn>1556-6021</eissn><coden>ITIFA6</coden><abstract>In social network, the existence of malicious users can create lots of detrimental consequences. To diminish their negative influences, it is necessary for rational users to identify and interact with each neighbor carefully to protect themselves from malicious ones. Therefore, it is crucial to establish a rule for users' interaction in order to mitigate malicious users' influences. In this paper, we propose a smart evolution model based on evolutionary game theory by introducing the reputation mechanism. The model takes into account both current reputation and instant incentives during users' decision-making process. On the basis of whether users share reputation values with others, we introduce schemes without reciprocity principle and with the indirect reciprocity principle respectively. With the social norm and reputation updating policy, we theoretically analyze the evolutionary dynamics and corresponding ESSs by explicitly considering the effects of malicious users. Finally, simulations based on synthetic networks and real-world data are conducted to validate the effectiveness of the proposed smart evolution model.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TIFS.2020.3032039</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-3690-9924</orcidid><orcidid>https://orcid.org/0000-0002-3227-4562</orcidid></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 1556-6013
ispartof IEEE transactions on information forensics and security, 2021, Vol.16, p.1203-1217
issn 1556-6013
1556-6021
language eng
recordid cdi_crossref_primary_10_1109_TIFS_2020_3032039
source IEEE Electronic Library (IEL)
subjects Data models
Decision making
Diffusion processes
Evolution
evolutionary game theory
Game theory
Games
Incentives
information diffusion
Information dissemination
malicious users
Reciprocity
Reputation
Reputations
Social networking (online)
Social networks
Sociology
Statistics
title Smart Evolution for Information Diffusion Over Social Networks
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-08T21%3A09%3A18IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Smart%20Evolution%20for%20Information%20Diffusion%20Over%20Social%20Networks&rft.jtitle=IEEE%20transactions%20on%20information%20forensics%20and%20security&rft.au=Zhang,%20Hangjing&rft.date=2021&rft.volume=16&rft.spage=1203&rft.epage=1217&rft.pages=1203-1217&rft.issn=1556-6013&rft.eissn=1556-6021&rft.coden=ITIFA6&rft_id=info:doi/10.1109/TIFS.2020.3032039&rft_dat=%3Cproquest_RIE%3E2460161883%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2460161883&rft_id=info:pmid/&rft_ieee_id=9229115&rfr_iscdi=true