Dynamic Trust Relationships Aware Data Privacy Protection in Mobile Crowd-Sensing
Malicious network nodes often incur problems to network and data privacy by distributing forged public keys. To address this issue, this paper proposes a dynamic trust relationships aware data privacy protection (DTRPP) mechanism for mobile crowd-sensing. In this mechanism, combining key distributio...
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Veröffentlicht in: | IEEE internet of things journal 2018-08, Vol.5 (4), p.2958-2970 |
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creator | Wu, Dapeng Si, Shushan Wu, Shaoen Wang, Ruyan |
description | Malicious network nodes often incur problems to network and data privacy by distributing forged public keys. To address this issue, this paper proposes a dynamic trust relationships aware data privacy protection (DTRPP) mechanism for mobile crowd-sensing. In this mechanism, combining key distribution with trust management, the trust value of a public key is evaluated according to both the number of supporter and the trust degree of the public key. The trust value is estimated from the accuracy of the public key provided by the encountering nodes. DTRPP achieves the dynamic management of nodes and estimates the trust degree of the public key. In addition, by classifying traffic data into different types and selecting a proper relay node to forward the data according to data types, it is more effective to use the network resource with the trust degree and centrality of the relays. With extensive evaluations, results show that the proposed mechanism protects the data privacy effectively and has better performance on the average delay, the delivery rate and the loading rate when compared to traditional mechanisms. |
doi_str_mv | 10.1109/JIOT.2017.2768073 |
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To address this issue, this paper proposes a dynamic trust relationships aware data privacy protection (DTRPP) mechanism for mobile crowd-sensing. In this mechanism, combining key distribution with trust management, the trust value of a public key is evaluated according to both the number of supporter and the trust degree of the public key. The trust value is estimated from the accuracy of the public key provided by the encountering nodes. DTRPP achieves the dynamic management of nodes and estimates the trust degree of the public key. In addition, by classifying traffic data into different types and selecting a proper relay node to forward the data according to data types, it is more effective to use the network resource with the trust degree and centrality of the relays. 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To address this issue, this paper proposes a dynamic trust relationships aware data privacy protection (DTRPP) mechanism for mobile crowd-sensing. In this mechanism, combining key distribution with trust management, the trust value of a public key is evaluated according to both the number of supporter and the trust degree of the public key. The trust value is estimated from the accuracy of the public key provided by the encountering nodes. DTRPP achieves the dynamic management of nodes and estimates the trust degree of the public key. In addition, by classifying traffic data into different types and selecting a proper relay node to forward the data according to data types, it is more effective to use the network resource with the trust degree and centrality of the relays. With extensive evaluations, results show that the proposed mechanism protects the data privacy effectively and has better performance on the average delay, the delivery rate and the loading rate when compared to traditional mechanisms.</description><subject>Computer privacy</subject><subject>Data communication</subject><subject>Data privacy</subject><subject>Loading rate</subject><subject>Mobile communication</subject><subject>Mobile crowd-sensing</subject><subject>Nodes</subject><subject>Privacy</subject><subject>privacy protection</subject><subject>Public key</subject><subject>Public Key Infrastructure</subject><subject>Relays</subject><subject>Sensors</subject><subject>Traffic information</subject><subject>trust management</subject><subject>Trustworthiness</subject><subject>Wireless networks</subject><issn>2327-4662</issn><issn>2327-4662</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkE1PAjEQhhujiUT5AcZLE8-LnXa37R4J-IHB4Aeem26Z1RLYxXaR8O_dDcR4eufwvDOTh5ArYAMAlt8-TWbzAWegBlxJzZQ4IT0uuEpSKfnpv_mc9GNcMsbaWga57JHX8b6ya-_oPGxjQ99wZRtfV_HLbyId7mxAOraNpS_B_1i3b7Nu0HUI9RV9rgu_QjoK9W6RvGMVffV5Sc5Ku4rYP-YF-bi_m48ek-nsYTIaThPHc9EkBQqnpMhKsKzUkqWyWKQFzzPGZdl-WKBTUKBMmdIpByutttlCSKU1gshTcUFuDns3of7eYmzMst6Gqj1pOIACwTKhWgoOlAt1jAFLswl-bcPeADOdPNPJM508c5TXdq4PHY-If7xmOlcZF7_xSWl7</recordid><startdate>20180801</startdate><enddate>20180801</enddate><creator>Wu, Dapeng</creator><creator>Si, Shushan</creator><creator>Wu, Shaoen</creator><creator>Wang, Ruyan</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>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-4768-6930</orcidid><orcidid>https://orcid.org/0000-0003-2105-9418</orcidid></search><sort><creationdate>20180801</creationdate><title>Dynamic Trust Relationships Aware Data Privacy Protection in Mobile Crowd-Sensing</title><author>Wu, Dapeng ; Si, Shushan ; Wu, Shaoen ; Wang, Ruyan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c293t-be3c7635f1a0f86046bd4b295026f000bec71be64078421a6a8a5d36788e13943</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Computer privacy</topic><topic>Data communication</topic><topic>Data privacy</topic><topic>Loading rate</topic><topic>Mobile communication</topic><topic>Mobile crowd-sensing</topic><topic>Nodes</topic><topic>Privacy</topic><topic>privacy protection</topic><topic>Public key</topic><topic>Public Key Infrastructure</topic><topic>Relays</topic><topic>Sensors</topic><topic>Traffic information</topic><topic>trust management</topic><topic>Trustworthiness</topic><topic>Wireless networks</topic><toplevel>online_resources</toplevel><creatorcontrib>Wu, Dapeng</creatorcontrib><creatorcontrib>Si, Shushan</creatorcontrib><creatorcontrib>Wu, Shaoen</creatorcontrib><creatorcontrib>Wang, Ruyan</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>Technology Research Database</collection><collection>ProQuest Computer Science Collection</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 internet of things journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Wu, Dapeng</au><au>Si, Shushan</au><au>Wu, Shaoen</au><au>Wang, Ruyan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Dynamic Trust Relationships Aware Data Privacy Protection in Mobile Crowd-Sensing</atitle><jtitle>IEEE internet of things journal</jtitle><stitle>JIoT</stitle><date>2018-08-01</date><risdate>2018</risdate><volume>5</volume><issue>4</issue><spage>2958</spage><epage>2970</epage><pages>2958-2970</pages><issn>2327-4662</issn><eissn>2327-4662</eissn><coden>IITJAU</coden><abstract>Malicious network nodes often incur problems to network and data privacy by distributing forged public keys. To address this issue, this paper proposes a dynamic trust relationships aware data privacy protection (DTRPP) mechanism for mobile crowd-sensing. In this mechanism, combining key distribution with trust management, the trust value of a public key is evaluated according to both the number of supporter and the trust degree of the public key. The trust value is estimated from the accuracy of the public key provided by the encountering nodes. DTRPP achieves the dynamic management of nodes and estimates the trust degree of the public key. In addition, by classifying traffic data into different types and selecting a proper relay node to forward the data according to data types, it is more effective to use the network resource with the trust degree and centrality of the relays. With extensive evaluations, results show that the proposed mechanism protects the data privacy effectively and has better performance on the average delay, the delivery rate and the loading rate when compared to traditional mechanisms.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/JIOT.2017.2768073</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-4768-6930</orcidid><orcidid>https://orcid.org/0000-0003-2105-9418</orcidid></addata></record> |
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subjects | Computer privacy Data communication Data privacy Loading rate Mobile communication Mobile crowd-sensing Nodes Privacy privacy protection Public key Public Key Infrastructure Relays Sensors Traffic information trust management Trustworthiness Wireless networks |
title | Dynamic Trust Relationships Aware Data Privacy Protection in Mobile Crowd-Sensing |
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