Big Data Analytics for Cyber Security using binary crow search algorithm based Deep Neural Network
Cyber security is the one of the big challenges in Big Data Analytics. The prediction of cyber attackers or threats is performed by presenting machine learning algorithms and Deep Learning algorithms. However, accuracy of the prediction model is further to be improved so that an enhanced DNN, a Deep...
Uložené v:
| Vydané v: | 2022 IEEE 7th International conference for Convergence in Technology (I2CT) s. 1 - 5 |
|---|---|
| Hlavní autori: | , |
| Médium: | Konferenčný príspevok.. |
| Jazyk: | English |
| Vydavateľské údaje: |
IEEE
07.04.2022
|
| Predmet: | |
| On-line prístup: | Získať plný text |
| Tagy: |
Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
|
| Abstract | Cyber security is the one of the big challenges in Big Data Analytics. The prediction of cyber attackers or threats is performed by presenting machine learning algorithms and Deep Learning algorithms. However, accuracy of the prediction model is further to be improved so that an enhanced DNN, a Deep Neural Network is offered here in this paper and this enhanced DNN is utilized as a prediction model. The performance of the DNN is improved with the Binary Crow Search Algorithm (BCSA). Using this algorithm, weight parameters of DNN are optimized. Simulation outcomes illustrate that the projected prediction model outpaces the existing DNN in terms of Recall, Precision, F-score and Accuracy. |
|---|---|
| AbstractList | Cyber security is the one of the big challenges in Big Data Analytics. The prediction of cyber attackers or threats is performed by presenting machine learning algorithms and Deep Learning algorithms. However, accuracy of the prediction model is further to be improved so that an enhanced DNN, a Deep Neural Network is offered here in this paper and this enhanced DNN is utilized as a prediction model. The performance of the DNN is improved with the Binary Crow Search Algorithm (BCSA). Using this algorithm, weight parameters of DNN are optimized. Simulation outcomes illustrate that the projected prediction model outpaces the existing DNN in terms of Recall, Precision, F-score and Accuracy. |
| Author | Godishala, Aruna Kranthi Banoth, Rajkumar |
| Author_xml | – sequence: 1 givenname: Rajkumar surname: Banoth fullname: Banoth, Rajkumar email: naaniraj@gmail.com organization: Marwadi University,Dept. Of. Computer Engineering,Rajkot,Gujarat,India – sequence: 2 givenname: Aruna Kranthi surname: Godishala fullname: Godishala, Aruna Kranthi email: raj.kranthi@gmail.com organization: University Brunei Darussalam,Brunei Darussalam |
| BookMark | eNotj8tqwzAURFVoF03aLyiU-wN2LVmSpWXq9BEI7aLeB0m-ckQdO8g2wX9fQ7M6cBiGmRW57foOCXmmWUpppl92rKwEZ5qmLGMs1YpxJdUNWVEpF0-lovfEvoYGtmY0sOlMO4_BDeD7COVsMcIPuimGcYZpCF0DNnQmzuBif4EBTXRHMG3TL4njCawZsIYt4hm-cIqmXTBe-vj7QO68aQd8vHJNqve3qvxM9t8fu3KzTwJXIqFUFtYLb3zmCq-d9dwXLneKGyqdX1RdO0TBayHtQpq7DHOutNTCFDXP1-TpvzYg4uEcw2nZeri-zv8A2HpT2w |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IL CBEJK RIE RIL |
| DOI | 10.1109/I2CT54291.2022.9824868 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Xplore POP ALL IEEE Xplore All Conference Proceedings IEEE Xplore 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 | 1665421681 9781665421683 9781665421669 1665421665 |
| EndPage | 5 |
| ExternalDocumentID | 9824868 |
| Genre | orig-research |
| GroupedDBID | 6IE 6IL CBEJK RIE RIL |
| ID | FETCH-LOGICAL-i485-1167bf5faf0c7f9cbf4f7c3c84a16cf7f9ddcee54d56bee513c0e3489695a7d43 |
| IEDL.DBID | RIE |
| IngestDate | Thu Jun 29 18:36:45 EDT 2023 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-i485-1167bf5faf0c7f9cbf4f7c3c84a16cf7f9ddcee54d56bee513c0e3489695a7d43 |
| PageCount | 5 |
| ParticipantIDs | ieee_primary_9824868 |
| PublicationCentury | 2000 |
| PublicationDate | 2022-April-7 |
| PublicationDateYYYYMMDD | 2022-04-07 |
| PublicationDate_xml | – month: 04 year: 2022 text: 2022-April-7 day: 07 |
| PublicationDecade | 2020 |
| PublicationTitle | 2022 IEEE 7th International conference for Convergence in Technology (I2CT) |
| PublicationTitleAbbrev | I2CT |
| PublicationYear | 2022 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| Score | 1.7904555 |
| Snippet | Cyber security is the one of the big challenges in Big Data Analytics. The prediction of cyber attackers or threats is performed by presenting machine learning... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 1 |
| SubjectTerms | Big Data Binary Crow Search Algorithm (BCSA) Cyber security Deep learning deep neural network (DNN) Feature extraction Machine learning algorithms Neural networks Prediction algorithms Predictive models |
| Title | Big Data Analytics for Cyber Security using binary crow search algorithm based Deep Neural Network |
| URI | https://ieeexplore.ieee.org/document/9824868 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LSwMxEB7a4sGTSiu-mYNHt93NZjfJ1daiIKVgD72VPGuhtqW2iv_eJF0qghdPGUIgIQnzSOabD-A2TZ0PubhJBKVFQomlXspVIrTjXlN6I1NGoPAzGwz4eCyGNbjbY2GstTH5zLaDGP_yzVJvw1NZR3BCecnrUGeM7bBaFeg3S0XniXRHgX0pRH2EtKvBv1hTotHoH_1vumNo_aDvcLi3KydQs4smqPvZFHtyIzGWEQnFldH7m9j9UnaNLxULHYY09imqCLJFr2M_cXeVUc6nSz_i9Q2D3TLYs3aFoTKHnPsmpoK3YNR_GHUfk4ofIZlRXiThB0W5wkmXauaEVo46pnPNqcxK7XyXMX6pBTVFqXyb5Tq1OeWiFIVkhuan0FgsF_YMMDDPcCZ9-BU8itwp57wjlSlGjOaCuHNohu2ZrHYVMCbVzlz83X0Jh-EEYn4Lu4LGZr2113CgPzaz9_VNPLZvV4mbQw |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LTwIxEJ4gmuhJDRjf9uDRhd1uu9teBQ1EJCTugRvpE0kQCILGf29bNhgTL546aZq0aZt5tPPNB3Abx9aFXExHnBAaEWyIk1IZcWWZ05TOyGQBKNzL-302HPJBBe62WBhjTEg-Mw0vhr98PVdr_1TW5AwTlrEd2KWE4GSD1iphv0nMm13cKjz_ko_7MG6Uw3_xpgSz8Xj4vwmPoP6Dv0ODrWU5hoqZ1UDeT8aoLVYChUIivrwych4nan1Js0QvJQ8d8onsYyQDzBY5LfuJNpcZiel47ka8viFvuTRqG7NAvjaHmLomJIPXoXh8KFqdqGRIiCaE0cj_oUhLrbCxyi1X0hKbq1QxIpJMWdeltVsqJZpm0rVJqmKTEsYzTkWuSXoC1dl8Zk4Bee4ZlgsXgHmfIrXSWudKJTLHWjGO7RnU_PaMFpsaGKNyZ87_7r6B_U7x3Bv1uv2nCzjwpxGyXfJLqK6Wa3MFe-pjNXlfXocj_AaW_p6K |
| 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=2022+IEEE+7th+International+conference+for+Convergence+in+Technology+%28I2CT%29&rft.atitle=Big+Data+Analytics+for+Cyber+Security+using+binary+crow+search+algorithm+based+Deep+Neural+Network&rft.au=Banoth%2C+Rajkumar&rft.au=Godishala%2C+Aruna+Kranthi&rft.date=2022-04-07&rft.pub=IEEE&rft.spage=1&rft.epage=5&rft_id=info:doi/10.1109%2FI2CT54291.2022.9824868&rft.externalDocID=9824868 |