Exposure of Botnets in Cloud Environment by Expending Trust Model with CANFES Classification Approach
<p dir="ltr">Many cloud service providers offer access to versatile, dependable processing assets following a compensation as-you-go display. Investigation into the security of the cloud focusses basically on shielding genuine clients of cloud administrations from assaults by outer,...
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2022
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| _version_ | 1864513531450228736 |
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| author | Nagendra Prabhu Selvaraj (17542041) |
| author2 | Sivakumar Paulraj (17542044) Parthasarathy Ramadass (17542047) Rajesh Kaluri (17541486) Mohammad Shorfuzzaman (17542050) Abdulmajeed Alsufyani (276154) Mueen Uddin (4903510) |
| author2_role | author author author author author author |
| author_facet | Nagendra Prabhu Selvaraj (17542041) Sivakumar Paulraj (17542044) Parthasarathy Ramadass (17542047) Rajesh Kaluri (17541486) Mohammad Shorfuzzaman (17542050) Abdulmajeed Alsufyani (276154) Mueen Uddin (4903510) |
| author_role | author |
| dc.creator.none.fl_str_mv | Nagendra Prabhu Selvaraj (17542041) Sivakumar Paulraj (17542044) Parthasarathy Ramadass (17542047) Rajesh Kaluri (17541486) Mohammad Shorfuzzaman (17542050) Abdulmajeed Alsufyani (276154) Mueen Uddin (4903510) |
| dc.date.none.fl_str_mv | 2022-07-28T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.3390/electronics11152350 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Exposure_of_Botnets_in_Cloud_Environment_by_Expending_Trust_Model_with_CANFES_Classification_Approach/24717516 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Information and computing sciences Cybersecurity and privacy Distributed computing and systems software trust model bots classifier cloud detection rate CANFES |
| dc.title.none.fl_str_mv | Exposure of Botnets in Cloud Environment by Expending Trust Model with CANFES Classification Approach |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">Many cloud service providers offer access to versatile, dependable processing assets following a compensation as-you-go display. Investigation into the security of the cloud focusses basically on shielding genuine clients of cloud administrations from assaults by outer, vindictive clients. Little consideration is given to restrict malicious clients from utilizing the cloud to dispatch assaults, for example, those as of now done by botnets. These assaults incorporate propelling a DDoS attack, sending spam and executing click extortion. Bots’ detection in the cloud environment is a complex process. The purpose of this study was to create a multi-layered architecture that could detect a variety of existing and emerging botnets. The goal is to be able to detect a larger range of bots and botnets by relying on several techniques called trust model. On this work, the port access verification in trust model is achieved by a Heuristic factorizing algorithm which verifies the port accessibility between client-end-user and client server. Further, back-off features are extracted from the particular node and all these structures are trained and categorized with a Co-Active Neuro Fuzzy Expert System (CANFES) classifier. The performance of the proposed bot detection system in the internet environment is analyzed latency, detection rate, packet delivery ration, energy availability and precision.</p><h2>Other Information</h2><p dir="ltr">Published in: Electronics<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/electronics11152350" target="_blank">https://dx.doi.org/10.3390/electronics11152350</a></p><p dir="ltr">Disclaimer: The University of Doha for Science and Technology replaced the now-former College of the North Atlantic-Qatar after an Amiri decision in 2022. UDST has become and first national applied University in Qatar; it is also second national University in the country.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_7ca450f749d60b32c02e386738a6a16b |
| identifier_str_mv | 10.3390/electronics11152350 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/24717516 |
| publishDate | 2022 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Exposure of Botnets in Cloud Environment by Expending Trust Model with CANFES Classification ApproachNagendra Prabhu Selvaraj (17542041)Sivakumar Paulraj (17542044)Parthasarathy Ramadass (17542047)Rajesh Kaluri (17541486)Mohammad Shorfuzzaman (17542050)Abdulmajeed Alsufyani (276154)Mueen Uddin (4903510)Information and computing sciencesCybersecurity and privacyDistributed computing and systems softwaretrust modelbotsclassifierclouddetection rateCANFES<p dir="ltr">Many cloud service providers offer access to versatile, dependable processing assets following a compensation as-you-go display. Investigation into the security of the cloud focusses basically on shielding genuine clients of cloud administrations from assaults by outer, vindictive clients. Little consideration is given to restrict malicious clients from utilizing the cloud to dispatch assaults, for example, those as of now done by botnets. These assaults incorporate propelling a DDoS attack, sending spam and executing click extortion. Bots’ detection in the cloud environment is a complex process. The purpose of this study was to create a multi-layered architecture that could detect a variety of existing and emerging botnets. The goal is to be able to detect a larger range of bots and botnets by relying on several techniques called trust model. On this work, the port access verification in trust model is achieved by a Heuristic factorizing algorithm which verifies the port accessibility between client-end-user and client server. Further, back-off features are extracted from the particular node and all these structures are trained and categorized with a Co-Active Neuro Fuzzy Expert System (CANFES) classifier. The performance of the proposed bot detection system in the internet environment is analyzed latency, detection rate, packet delivery ration, energy availability and precision.</p><h2>Other Information</h2><p dir="ltr">Published in: Electronics<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/electronics11152350" target="_blank">https://dx.doi.org/10.3390/electronics11152350</a></p><p dir="ltr">Disclaimer: The University of Doha for Science and Technology replaced the now-former College of the North Atlantic-Qatar after an Amiri decision in 2022. UDST has become and first national applied University in Qatar; it is also second national University in the country.</p>2022-07-28T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.3390/electronics11152350https://figshare.com/articles/journal_contribution/Exposure_of_Botnets_in_Cloud_Environment_by_Expending_Trust_Model_with_CANFES_Classification_Approach/24717516CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/247175162022-07-28T03:00:00Z |
| spellingShingle | Exposure of Botnets in Cloud Environment by Expending Trust Model with CANFES Classification Approach Nagendra Prabhu Selvaraj (17542041) Information and computing sciences Cybersecurity and privacy Distributed computing and systems software trust model bots classifier cloud detection rate CANFES |
| status_str | publishedVersion |
| title | Exposure of Botnets in Cloud Environment by Expending Trust Model with CANFES Classification Approach |
| title_full | Exposure of Botnets in Cloud Environment by Expending Trust Model with CANFES Classification Approach |
| title_fullStr | Exposure of Botnets in Cloud Environment by Expending Trust Model with CANFES Classification Approach |
| title_full_unstemmed | Exposure of Botnets in Cloud Environment by Expending Trust Model with CANFES Classification Approach |
| title_short | Exposure of Botnets in Cloud Environment by Expending Trust Model with CANFES Classification Approach |
| title_sort | Exposure of Botnets in Cloud Environment by Expending Trust Model with CANFES Classification Approach |
| topic | Information and computing sciences Cybersecurity and privacy Distributed computing and systems software trust model bots classifier cloud detection rate CANFES |