Confidential system for retaining unrestricted auditing using datamining

The system which is so much required in this generation is the confidential system which will be observed by the basis of auditing the data records present in the research areas of effective way of algorithms present in the deep learning and machine learning which can be understood by the machines w...

Full description

Saved in:
Bibliographic Details
Main Authors: Asif, S., Veeresh, U., Kumar, G. Krishna Lava
Format: Conference Proceeding
Language:English
Subjects:
Algorithms
Data mining
Deep learning
Machine learning
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page
container_issue 1
container_start_page
container_title
container_volume 2548
creator Asif, S.
Veeresh, U.
Kumar, G. Krishna Lava
description The system which is so much required in this generation is the confidential system which will be observed by the basis of auditing the data records present in the research areas of effective way of algorithms present in the deep learning and machine learning which can be understood by the machines will be doing the things of humans automatically. Inculcating the needs of various models can be done with the algorithms. The background details are so much importance to get the mood. The elevation of the background details gives us the confidentiality of the system for the getting the details of auditing and the data mining is broad area to find the efficient way to find the topic to get the awesomeness of the Algorithms
doi_str_mv 10.1063/5.0118362
format conference_proceeding
fullrecord <record><control><sourceid>proquest_scita</sourceid><recordid>TN_cdi_scitation_primary_10_1063_5_0118362</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2838414238</sourcerecordid><originalsourceid>FETCH-LOGICAL-p967-30e09a139d62665de2f16d50f9b085d609dec6ce87bf740ee4bf288ee6c5254c3</originalsourceid><addsrcrecordid>eNotkE9LAzEUxIMoWKsHv8GCN2Hry99NjlLUCgUvPXgL6eZFUtpsTbKHfntb28sMDD_mPYaQRwozCoq_yBlQqrliV2RCpaRtp6i6JhMAI1om-PctuStlA8BM1-kJWcyHFKLHVKPbNuVQKu6aMOQmY3UxxfTTjCljqTn2FX3jRh_rf1pO6l11u3_sntwEty34cPEpWb2_reaLdvn18Tl_XbZ7o7qWA4JxlBuvmFLSIwtUeQnBrEFLr8B47FWPuluHTgCiWAemNaLqJZOi51PydK7d5-F3PP5lN8OY0_GiZZprQQXj-kg9n6nSx-pqHJLd57hz-WAp2NNQVtrLUPwPh5ZbHg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype><pqid>2838414238</pqid></control><display><type>conference_proceeding</type><title>Confidential system for retaining unrestricted auditing using datamining</title><source>American Institute of Physics:Jisc Collections:Transitional Journals Agreement 2021-23 (Reading list)</source><creator>Asif, S. ; Veeresh, U. ; Kumar, G. Krishna Lava</creator><contributor>Babu, B. Sridhar ; Prasad, B Anjaneya ; Swamy, Adepu Kumara ; Kumar, Kaushik</contributor><creatorcontrib>Asif, S. ; Veeresh, U. ; Kumar, G. Krishna Lava ; Babu, B. Sridhar ; Prasad, B Anjaneya ; Swamy, Adepu Kumara ; Kumar, Kaushik</creatorcontrib><description>The system which is so much required in this generation is the confidential system which will be observed by the basis of auditing the data records present in the research areas of effective way of algorithms present in the deep learning and machine learning which can be understood by the machines will be doing the things of humans automatically. Inculcating the needs of various models can be done with the algorithms. The background details are so much importance to get the mood. The elevation of the background details gives us the confidentiality of the system for the getting the details of auditing and the data mining is broad area to find the efficient way to find the topic to get the awesomeness of the Algorithms</description><identifier>ISSN: 0094-243X</identifier><identifier>EISSN: 1551-7616</identifier><identifier>DOI: 10.1063/5.0118362</identifier><identifier>CODEN: APCPCS</identifier><language>eng</language><publisher>Melville: American Institute of Physics</publisher><subject>Algorithms ; Data mining ; Deep learning ; Machine learning</subject><ispartof>AIP conference proceedings, 2023, Vol.2548 (1)</ispartof><rights>Author(s)</rights><rights>2023 Author(s). Published by AIP Publishing.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>309,310,314,780,784,789,790,23930,23931,25140,27924,27925</link.rule.ids></links><search><contributor>Babu, B. Sridhar</contributor><contributor>Prasad, B Anjaneya</contributor><contributor>Swamy, Adepu Kumara</contributor><contributor>Kumar, Kaushik</contributor><creatorcontrib>Asif, S.</creatorcontrib><creatorcontrib>Veeresh, U.</creatorcontrib><creatorcontrib>Kumar, G. Krishna Lava</creatorcontrib><title>Confidential system for retaining unrestricted auditing using datamining</title><title>AIP conference proceedings</title><description>The system which is so much required in this generation is the confidential system which will be observed by the basis of auditing the data records present in the research areas of effective way of algorithms present in the deep learning and machine learning which can be understood by the machines will be doing the things of humans automatically. Inculcating the needs of various models can be done with the algorithms. The background details are so much importance to get the mood. The elevation of the background details gives us the confidentiality of the system for the getting the details of auditing and the data mining is broad area to find the efficient way to find the topic to get the awesomeness of the Algorithms</description><subject>Algorithms</subject><subject>Data mining</subject><subject>Deep learning</subject><subject>Machine learning</subject><issn>0094-243X</issn><issn>1551-7616</issn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2023</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNotkE9LAzEUxIMoWKsHv8GCN2Hry99NjlLUCgUvPXgL6eZFUtpsTbKHfntb28sMDD_mPYaQRwozCoq_yBlQqrliV2RCpaRtp6i6JhMAI1om-PctuStlA8BM1-kJWcyHFKLHVKPbNuVQKu6aMOQmY3UxxfTTjCljqTn2FX3jRh_rf1pO6l11u3_sntwEty34cPEpWb2_reaLdvn18Tl_XbZ7o7qWA4JxlBuvmFLSIwtUeQnBrEFLr8B47FWPuluHTgCiWAemNaLqJZOi51PydK7d5-F3PP5lN8OY0_GiZZprQQXj-kg9n6nSx-pqHJLd57hz-WAp2NNQVtrLUPwPh5ZbHg</recordid><startdate>20230717</startdate><enddate>20230717</enddate><creator>Asif, S.</creator><creator>Veeresh, U.</creator><creator>Kumar, G. Krishna Lava</creator><general>American Institute of Physics</general><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope></search><sort><creationdate>20230717</creationdate><title>Confidential system for retaining unrestricted auditing using datamining</title><author>Asif, S. ; Veeresh, U. ; Kumar, G. Krishna Lava</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p967-30e09a139d62665de2f16d50f9b085d609dec6ce87bf740ee4bf288ee6c5254c3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Algorithms</topic><topic>Data mining</topic><topic>Deep learning</topic><topic>Machine learning</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Asif, S.</creatorcontrib><creatorcontrib>Veeresh, U.</creatorcontrib><creatorcontrib>Kumar, G. Krishna Lava</creatorcontrib><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Asif, S.</au><au>Veeresh, U.</au><au>Kumar, G. Krishna Lava</au><au>Babu, B. Sridhar</au><au>Prasad, B Anjaneya</au><au>Swamy, Adepu Kumara</au><au>Kumar, Kaushik</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Confidential system for retaining unrestricted auditing using datamining</atitle><btitle>AIP conference proceedings</btitle><date>2023-07-17</date><risdate>2023</risdate><volume>2548</volume><issue>1</issue><issn>0094-243X</issn><eissn>1551-7616</eissn><coden>APCPCS</coden><abstract>The system which is so much required in this generation is the confidential system which will be observed by the basis of auditing the data records present in the research areas of effective way of algorithms present in the deep learning and machine learning which can be understood by the machines will be doing the things of humans automatically. Inculcating the needs of various models can be done with the algorithms. The background details are so much importance to get the mood. The elevation of the background details gives us the confidentiality of the system for the getting the details of auditing and the data mining is broad area to find the efficient way to find the topic to get the awesomeness of the Algorithms</abstract><cop>Melville</cop><pub>American Institute of Physics</pub><doi>10.1063/5.0118362</doi><tpages>6</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0094-243X
ispartof AIP conference proceedings, 2023, Vol.2548 (1)
issn 0094-243X
1551-7616
language eng
recordid cdi_scitation_primary_10_1063_5_0118362
source American Institute of Physics:Jisc Collections:Transitional Journals Agreement 2021-23 (Reading list)
subjects Algorithms
Data mining
Deep learning
Machine learning
title Confidential system for retaining unrestricted auditing using datamining
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-04T03%3A32%3A07IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_scita&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Confidential%20system%20for%20retaining%20unrestricted%20auditing%20using%20datamining&rft.btitle=AIP%20conference%20proceedings&rft.au=Asif,%20S.&rft.date=2023-07-17&rft.volume=2548&rft.issue=1&rft.issn=0094-243X&rft.eissn=1551-7616&rft.coden=APCPCS&rft_id=info:doi/10.1063/5.0118362&rft_dat=%3Cproquest_scita%3E2838414238%3C/proquest_scita%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-p967-30e09a139d62665de2f16d50f9b085d609dec6ce87bf740ee4bf288ee6c5254c3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2838414238&rft_id=info:pmid/&rfr_iscdi=true