A deep study of analysis for encryption and decryption algorithm in cloud data with machine learning techniques
An emergence of cloud computing has made secure search on encrypted cloud data a popular area of study. Previous techniques' limited ability to generate query trapdoors made them less effective at ensuring query secrecy. A data user can also readily examine the query results of another data use...
Gespeichert in:
| Veröffentlicht in: | 2024 International Conference on Communication, Computing and Internet of Things (IC3IoT) S. 1 - 5 |
|---|---|
| Hauptverfasser: | , |
| Format: | Tagungsbericht |
| Sprache: | Englisch |
| Veröffentlicht: |
IEEE
17.04.2024
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | An emergence of cloud computing has made secure search on encrypted cloud data a popular area of study. Previous techniques' limited ability to generate query trapdoors made them less effective at ensuring query secrecy. A data user can also readily examine the query results of another data user in these systems, as the data owner often has complete knowledge of the query results of the data users. In certain application settings, the data user could be reluctant to give away the privacy of their query to anybody but themselves. It provide a search technique that enhances privacy by letting the data user create a different random query trapdoor each time and also it suggest the security of our scheme and show through extensive experiments that it is exactly right. Put the suggested plan into practice and evaluate how well it performs in terms of key generation process, secure indexing, trapdoor creation, and search timing. Compared to current hashing and attribute-based encryption searchable encryption technologies, the suggested scheme outperforms them. So, contributed to plan into practice, assess, and contrast its results using the example of searchable algorithms for encryption |
|---|---|
| AbstractList | An emergence of cloud computing has made secure search on encrypted cloud data a popular area of study. Previous techniques' limited ability to generate query trapdoors made them less effective at ensuring query secrecy. A data user can also readily examine the query results of another data user in these systems, as the data owner often has complete knowledge of the query results of the data users. In certain application settings, the data user could be reluctant to give away the privacy of their query to anybody but themselves. It provide a search technique that enhances privacy by letting the data user create a different random query trapdoor each time and also it suggest the security of our scheme and show through extensive experiments that it is exactly right. Put the suggested plan into practice and evaluate how well it performs in terms of key generation process, secure indexing, trapdoor creation, and search timing. Compared to current hashing and attribute-based encryption searchable encryption technologies, the suggested scheme outperforms them. So, contributed to plan into practice, assess, and contrast its results using the example of searchable algorithms for encryption |
| Author | Latha, B. Bharathi, M. Divya |
| Author_xml | – sequence: 1 givenname: M. Divya surname: Bharathi fullname: Bharathi, M. Divya email: divyamoorthi1022@gmail.com organization: Sri Sai Ram Engineering College, Tambaram,Department of Computer Science and Engineering,Chennai – sequence: 2 givenname: B. surname: Latha fullname: Latha, B. email: latha.cse@sairam.edu.in organization: Sri Sai Ram Engineering College, Tambaram,Department of Computer Science and Engineering,Chennai |
| BookMark | eNpFkMtOwzAURI0ECyj9AxbmAxL8uEnsZRXxiFSJTVlXt_ZNYym1S5IK5e-JBIjVaM6MZjF37DqmSIw9SpFLKexTU-sm7UphQOZKKMilKAqhRHXF1rayRhdCF6o09palDfdEZz5OFz_z1HKM2M9jGHmbBk7RDfN5Ciku3C_Nf9sf0xCm7sRD5K5PlyXFCfnXwvgJXRci8Z5wiCEe-USui-HzQuM9u2mxH2n9qyv28fK8q9-y7ftrU2-2WZDSTtnB48EbJcEaDw68L5X0ptVgCTwplKLSRBp8YQDAESC6tkJpD1I7AK1X7OFnNxDR_jyEEw7z_u8H_Q3vNlsI |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IL CBEJK RIE RIL |
| DOI | 10.1109/IC3IoT60841.2024.10550207 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume IEEE Xplore All Conference Proceedings IEEE Electronic Library (IEL) IEEE Proceedings Order Plans (POP All) 1998-Present |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| EISBN | 9798350352689 |
| EndPage | 5 |
| ExternalDocumentID | 10550207 |
| Genre | orig-research |
| GroupedDBID | 6IE 6IL CBEJK RIE RIL |
| ID | FETCH-LOGICAL-i119t-bdabd821498d4c4dd621d8f349e4de2a1073ee34d58444ce4aacf7a19b13c4433 |
| IEDL.DBID | RIE |
| IngestDate | Wed Jul 03 05:40:23 EDT 2024 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-i119t-bdabd821498d4c4dd621d8f349e4de2a1073ee34d58444ce4aacf7a19b13c4433 |
| PageCount | 5 |
| ParticipantIDs | ieee_primary_10550207 |
| PublicationCentury | 2000 |
| PublicationDate | 2024-April-17 |
| PublicationDateYYYYMMDD | 2024-04-17 |
| PublicationDate_xml | – month: 04 year: 2024 text: 2024-April-17 day: 17 |
| PublicationDecade | 2020 |
| PublicationTitle | 2024 International Conference on Communication, Computing and Internet of Things (IC3IoT) |
| PublicationTitleAbbrev | IC3IoT |
| PublicationYear | 2024 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| Score | 1.8667061 |
| Snippet | An emergence of cloud computing has made secure search on encrypted cloud data a popular area of study. Previous techniques' limited ability to generate query... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 1 |
| SubjectTerms | Cloud computing cloud data Data models Data privacy inquery result Machine learning Machine learning algorithms Secure encrypted data Telecommunication computing Timing |
| Title | A deep study of analysis for encryption and decryption algorithm in cloud data with machine learning techniques |
| URI | https://ieeexplore.ieee.org/document/10550207 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LSwMxEA62iHhSseKbCF633cfsZnOUoliQ0kOV3kqymdSFdrdst4L_3iTdtnjw4C3vQAKZb5LM9xHyyGNj1LX0PW2wvgeKx54EkXjGEkYyAcU2WgQfb2w4TCcTPmqC1V0sDCK6z2fYtUn3lq_KbG2vynpWzNHAG9YiLcaSTbDWEXloeDN7g340KMeJn4J1_ELobtv_Uk5xhuPl5J9TnpLOPgSPjnbG5YwcYHFOyieqEJfUccLSUlPRUIpQAz2p6VN9uxPAlCvTcp-dz8oqrz8XNC9oNi_XplbUgtpLWLpw3ymRNvoRM7qjdV11yPvL87j_6jWKCV4eBLz2pBJSpaHxelIFGSiVhIFKdQQcQWEojK8XIUagDOwAyBCEyDQTAZdBlAFE0QVpF2WBl4SG2gemNOMy4RAanGhG8oVGLuJYasAr0rGrNV1uSDGm24W6_qP8hhzbPbEPMQG7Je26WuMdOcy-6nxV3but_AHwxqK1 |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LTwIxEG4UjXpSI8a3NfG6sLudffRoiAYiEg5ouJF2O8VNYJfAYuK_t10WiAcP3vpu0iadb9rO9xHyyANj1LV0HW2wvgOKB44EETrGEjIZgopWWgQf3ajXi4dD3q-C1ctYGEQsP59hwybLt3yVJ0t7Vda0Yo4G3kS7ZM9KZ7mrcK0D8lAxZzY7LdbJB6Ebg3X9fGise_zSTilNx8vxPyc9IfVtEB7tb8zLKdnB7IzkT1QhzmjJCktzTUVFKkIN-KSmz_y7PANMuTItt9nJOJ-nxeeUphlNJvnS1IpCUHsNS6flh0qklYLEmG6IXRd18v7yPGi1nUozwUk9jxeOVEKq2Dd-T6wgAaVC31OxZsARFPrCeHsMkYEywAMgQRAi0ZHwuPRYAsDYOalleYYXhPrahUjpiMuQg2-QohnJFRq5CAKpAS9J3a7WaLaixRitF-rqj_J7ctgevHVH3U7v9Zoc2f2xzzJedENqxXyJt2Q_-SrSxfyu3NYfj1ul-w |
| 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%3Abook&rft.genre=proceeding&rft.title=2024+International+Conference+on+Communication%2C+Computing+and+Internet+of+Things+%28IC3IoT%29&rft.atitle=A+deep+study+of+analysis+for+encryption+and+decryption+algorithm+in+cloud+data+with+machine+learning+techniques&rft.au=Bharathi%2C+M.+Divya&rft.au=Latha%2C+B.&rft.date=2024-04-17&rft.pub=IEEE&rft.spage=1&rft.epage=5&rft_id=info:doi/10.1109%2FIC3IoT60841.2024.10550207&rft.externalDocID=10550207 |