Machine Learning Empowered Security Management and Quality of Service Provision in SDN-NFV Environment
With the rising demand for data access, network service providers face the challenge of growing their capital and operating costs while at the same time enhancing network capacity and meeting the increased demand for access. To increase efficacy of Software Defined Network (SDN) and Network Function...
Saved in:
| Published in: | Computers, materials & continua Vol. 66; no. 3; pp. 2723 - 2749 |
|---|---|
| Main Authors: | , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Henderson
Tech Science Press
2021
|
| Subjects: | |
| ISSN: | 1546-2226, 1546-2218, 1546-2226 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | With the rising demand for data access, network service providers face the challenge of growing their capital and operating costs while at the same time enhancing network capacity and meeting the increased demand for access. To increase efficacy of Software Defined Network (SDN) and Network Function Virtualization (NFV) framework, we need to eradicate network security configuration errors that may create vulnerabilities to affect overall efficiency, reduce network performance, and increase maintenance cost. The existing frameworks lack in security, and computer systems face few abnormalities, which prompts the need for different recognition and mitigation methods to keep the system in the operational state proactively. The fundamental concept behind SDN-NFV is the encroachment from specific resource execution to the programming-based structure. This research is around the combination of SDN and NFV for rational decision making to control and monitor traffic in the virtualized environment. The combination is often seen as an extra burden in terms of resources usage in a heterogeneous network environment, but as well as it provides the solution for critical problems specially regarding massive network traffic issues. The attacks have been expanding step by step; therefore, it is hard to recognize and protect by conventional methods. To overcome these issues, there must be an autonomous system to recognize and characterize the network traffic’s abnormal conduct if there is any. Only four types of assaults, including HTTP Flood, UDP Flood, Smurf Flood, and SiDDoS Flood, are considered in the identified dataset, to optimize the stability of the SDN-NFV environment and security management, through several machine learning based characterization techniques like Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Logistic Regression (LR) and Isolation Forest (IF). Python is used for simulation purposes, including several valuable utilities like the mine package, the open-source Python ML libraries Scikit-learn, NumPy, SciPy, Matplotlib. Few Flood assaults and Structured Query Language (SQL) injections anomalies are validated and effectively-identified through the anticipated procedure. The classification results are promising and show that overall accuracy lies between 87% to 95% for SVM, LR, KNN, and IF classifiers in the scrutiny of traffic, whether the network traffic is normal or anomalous in the SDN-NFV environment. |
|---|---|
| AbstractList | With the rising demand for data access, network service providers face the challenge of growing their capital and operating costs while at the same time enhancing network capacity and meeting the increased demand for access. To increase efficacy of Software Defined Network (SDN) and Network Function Virtualization (NFV) framework, we need to eradicate network security configuration errors that may create vulnerabilities to affect overall efficiency, reduce network performance, and increase maintenance cost. The existing frameworks lack in security, and computer systems face few abnormalities, which prompts the need for different recognition and mitigation methods to keep the system in the operational state proactively. The fundamental concept behind SDN-NFV is the encroachment from specific resource execution to the programming-based structure. This research is around the combination of SDN and NFV for rational decision making to control and monitor traffic in the virtualized environment. The combination is often seen as an extra burden in terms of resources usage in a heterogeneous network environment, but as well as it provides the solution for critical problems specially regarding massive network traffic issues. The attacks have been expanding step by step; therefore, it is hard to recognize and protect by conventional methods. To overcome these issues, there must be an autonomous system to recognize and characterize the network traffic’s abnormal conduct if there is any. Only four types of assaults, including HTTP Flood, UDP Flood, Smurf Flood, and SiDDoS Flood, are considered in the identified dataset, to optimize the stability of the SDN-NFV environment and security management, through several machine learning based characterization techniques like Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Logistic Regression (LR) and Isolation Forest (IF). Python is used for simulation purposes, including several valuable utilities like the mine package, the open-source Python ML libraries Scikit-learn, NumPy, SciPy, Matplotlib. Few Flood assaults and Structured Query Language (SQL) injections anomalies are validated and effectively-identified through the anticipated procedure. The classification results are promising and show that overall accuracy lies between 87% to 95% for SVM, LR, KNN, and IF classifiers in the scrutiny of traffic, whether the network traffic is normal or anomalous in the SDN-NFV environment. |
| Author | Basharat, Asma Rizwan, Muhammad Ahmad, Fahad Humayun, Mamoona Alanazi, Saad Naseem, Shahid Shahzadi, Shumaila Alruwaili, Madallah |
| Author_xml | – sequence: 1 givenname: Shumaila surname: Shahzadi fullname: Shahzadi, Shumaila – sequence: 2 givenname: Fahad surname: Ahmad fullname: Ahmad, Fahad – sequence: 3 givenname: Asma surname: Basharat fullname: Basharat, Asma – sequence: 4 givenname: Madallah surname: Alruwaili fullname: Alruwaili, Madallah – sequence: 5 givenname: Saad surname: Alanazi fullname: Alanazi, Saad – sequence: 6 givenname: Mamoona surname: Humayun fullname: Humayun, Mamoona – sequence: 7 givenname: Muhammad surname: Rizwan fullname: Rizwan, Muhammad – sequence: 8 givenname: Shahid surname: Naseem fullname: Naseem, Shahid |
| BookMark | eNp1kE1PAjEQhhuDiYDePTbxvNjv3R4NgpoAalCvTel2sQRa7O5i-PcW8WBMPM1k8rwzk6cHOj54C8AlRgNKBGLXZmMGBBE8QJhxyU5AF3MmMkKI6Pzqz0CvrlcIUUEl6oJqqs278xZOrI7e-SUcbbbh00Zbwrk1bXTNHk6110u7sb6B2pfwudXrwzhUCYk7Zyx8imHnahc8dB7Ob2fZbPwGR37nYvCH3Dk4rfS6thc_tQ9ex6OX4X02ebx7GN5MMkMxbTJbMMsrIheScGuMoBrliMsScy0LnZcS59zwxNC8LJjhZc61QAUSxYKKojS0D66Oe7cxfLS2btQqtNGnk4qwnPFESpQocaRMDHUdbaWMa3ST3m-idmuFkfp2qpJTdXCqjk5TEP0JbqPb6Lj_P_IFfeB7Lg |
| CitedBy_id | crossref_primary_10_32604_cmc_2021_016591 crossref_primary_10_1016_j_ijdrr_2022_103470 crossref_primary_10_32604_cmc_2022_023215 crossref_primary_10_1002_itl2_519 crossref_primary_10_1007_s10207_025_01114_z crossref_primary_10_1155_2022_6138434 crossref_primary_10_32604_cmc_2022_018505 crossref_primary_10_1109_JSEN_2021_3066492 crossref_primary_10_32604_cmc_2021_018625 crossref_primary_10_1016_j_jksuci_2022_02_017 crossref_primary_10_32604_cmc_2021_015922 crossref_primary_10_1016_j_ecolind_2023_110457 |
| Cites_doi | 10.1145/3172866 10.30630/joiv.1.4.40 10.1109/JSAC.2019.2959197 10.1109/MCOM.2018.1700560 10.14569/IJACSA.2019.0100138 10.1109/ACCESS.2019.2915195 10.1016/j.procs.2020.03.330 10.32604/cmc.2020.06418 10.1109/MNET.001.1900273 10.1186/s42400-019-0038-7 10.14569/IJACSA.2019.0100321 10.14569/IJACSA.2019.0100110 10.1109/COMST.2017.2690823 10.1109/COMST.2019.2896380 10.1109/JSAC.2020.2986621 10.1155/2020/5352108 10.1109/ACCESS.2020.2996214 10.1155/2019/2509898 10.3390/su12104255 10.1016/j.future.2018.08.050 10.1016/j.comnet.2020.107364 |
| ContentType | Journal Article |
| Copyright | 2021. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| Copyright_xml | – notice: 2021. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| DBID | AAYXX CITATION 7SC 7SR 8BQ 8FD ABUWG AFKRA AZQEC BENPR CCPQU DWQXO JG9 JQ2 L7M L~C L~D PHGZM PHGZT PIMPY PKEHL PQEST PQQKQ PQUKI PRINS |
| DOI | 10.32604/cmc.2021.014594 |
| DatabaseName | CrossRef Computer and Information Systems Abstracts Engineered Materials Abstracts METADEX Technology Research Database ProQuest Central (Alumni) ProQuest Central UK/Ireland ProQuest Central Essentials ProQuest Central ProQuest One ProQuest Central Korea Materials Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional Proquest Central Premium ProQuest One Academic (New) ProQuest Publicly Available Content Database ProQuest One Academic Middle East (New) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China |
| DatabaseTitle | CrossRef Publicly Available Content Database Materials Research Database Technology Research Database Computer and Information Systems Abstracts – Academic ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest One Academic Eastern Edition ProQuest Computer Science Collection Computer and Information Systems Abstracts ProQuest Central (Alumni Edition) ProQuest One Community College ProQuest Central China METADEX Computer and Information Systems Abstracts Professional ProQuest Central Engineered Materials Abstracts ProQuest One Academic UKI Edition ProQuest Central Korea ProQuest Central (New) ProQuest One Academic Advanced Technologies Database with Aerospace ProQuest One Academic (New) |
| DatabaseTitleList | Publicly Available Content Database |
| Database_xml | – sequence: 1 dbid: PIMPY name: ProQuest Publicly Available Content Database url: http://search.proquest.com/publiccontent sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| EISSN | 1546-2226 |
| EndPage | 2749 |
| ExternalDocumentID | 10_32604_cmc_2021_014594 |
| GroupedDBID | AAFWJ AAYXX ACIWK ADMLS AFFHD AFKRA ALMA_UNASSIGNED_HOLDINGS BENPR CCPQU CITATION EBS EJD J9A OK1 P2P PHGZM PHGZT PIMPY RTS TUS 7SC 7SR 8BQ 8FD ABUWG AZQEC DWQXO JG9 JQ2 L7M L~C L~D PKEHL PQEST PQQKQ PQUKI PRINS |
| ID | FETCH-LOGICAL-c313t-e84e5f29b925ecc63a07059d15a98a7d9175c54e537d84c5d75a608068b368dc3 |
| IEDL.DBID | BENPR |
| ISICitedReferencesCount | 27 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000604616100001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1546-2226 1546-2218 |
| IngestDate | Sun Nov 09 07:37:17 EST 2025 Tue Nov 18 22:08:03 EST 2025 Sat Nov 29 05:53:47 EST 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 3 |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c313t-e84e5f29b925ecc63a07059d15a98a7d9175c54e537d84c5d75a608068b368dc3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| OpenAccessLink | https://www.proquest.com/docview/2474506890?pq-origsite=%requestingapplication% |
| PQID | 2474506890 |
| PQPubID | 2048737 |
| PageCount | 27 |
| ParticipantIDs | proquest_journals_2474506890 crossref_citationtrail_10_32604_cmc_2021_014594 crossref_primary_10_32604_cmc_2021_014594 |
| PublicationCentury | 2000 |
| PublicationDate | 2021-00-00 20210101 |
| PublicationDateYYYYMMDD | 2021-01-01 |
| PublicationDate_xml | – year: 2021 text: 2021-00-00 |
| PublicationDecade | 2020 |
| PublicationPlace | Henderson |
| PublicationPlace_xml | – name: Henderson |
| PublicationTitle | Computers, materials & continua |
| PublicationYear | 2021 |
| Publisher | Tech Science Press |
| Publisher_xml | – name: Tech Science Press |
| References | Khraisat (ref34) 2019; 2 Abdulqadder (ref22) 2020; 179 Ayoubi (ref26) 2018; 56 Khalid (ref29) 2019; 10 Thakkar (ref38) 2020; 167 Nguyen (ref15) 2017; 19 Shabbir (ref2) 2019; 2019 Kumar (ref6) 2017; 1 Bonfim (ref32) 2019; 51 Shabbir (ref25) 2018; 4 Prasanna (ref37) 2019 Cath (ref23) 2018; 24 Zarca (ref21) 2020; 38 Lee (ref30) 2017 Shah (ref3) 2019 Liu (ref35) 2020; 67 Das (ref1) 2018; 65 Allen (ref8) 2017 Shi (ref5) 2020; 62 Shahzadi (ref10) 2020; 2020 Krishnan (ref33) 2020; 50 Dilawar (ref18) 2019; 10 Abdulqadder (ref14) 2018 Nadeem (ref31) 2019; 10 Mathas (ref36) 2018 Chaabouni (ref7) 2019; 21 Behnke (ref20) 2019 Pastor (ref28) 2018 Wei (ref27) 2020; 38 Benzaid (ref12) 2020; 34 Rehman (ref11) 2019; 7 Yang (ref13) 2019; 93 Bagaa (ref16) 2020; 8 Ahmad (ref24) 2017; 17 ref4 Farris (ref19) 2017 Ali (ref9) 2020; 12 Karan (ref17) 2018 |
| References_xml | – volume: 51 start-page: 1 year: 2019 ident: ref32 article-title: Integrated NFV/SDN architectures: A systematic literature review publication-title: ACM Computing Surveys doi: 10.1145/3172866 – volume: 1 start-page: 122 year: 2017 ident: ref6 article-title: Analysis of network function virtualization and software defined virtualization publication-title: International Journal on Informatics Visualization doi: 10.30630/joiv.1.4.40 – volume: 38 start-page: 245 year: 2020 ident: ref27 article-title: Guest editorial leveraging machine learning in SDN/NFV-based networks publication-title: IEEE Journal on Selected Areas in Communications doi: 10.1109/JSAC.2019.2959197 – year: 2017 ident: ref8 publication-title: Artificial intelligence and national security – volume: 56 start-page: 158 year: 2018 ident: ref26 article-title: Machine learning for cognitive network management publication-title: IEEE Communications Magazine doi: 10.1109/MCOM.2018.1700560 – volume: 10 start-page: 288 year: 2019 ident: ref31 publication-title: International Journal of Advanced Computer Science and Applications doi: 10.14569/IJACSA.2019.0100138 – volume: 50 start-page: 757 year: 2020 ident: ref33 article-title: SDN/NFV security framework for fog-to-things computing infrastructure publication-title: Software: Practice and Experience – volume: 7 start-page: 60439 year: 2019 ident: ref11 article-title: Network functions virtualization: The long road to commercial deployments publication-title: IEEE Access doi: 10.1109/ACCESS.2019.2915195 – volume: 167 start-page: 636 year: 2020 ident: ref38 article-title: A review of the advancement in intrusion detection datasets publication-title: Procedia Computer Science doi: 10.1016/j.procs.2020.03.330 – volume: 62 start-page: 385 year: 2020 ident: ref5 article-title: An openflow-based load balancing strategy in SDN publication-title: Computers, Materials & Continua doi: 10.32604/cmc.2020.06418 – volume: 34 start-page: 124 year: 2020 ident: ref12 article-title: ZSM security: Threat surface and best practices publication-title: IEEE Network doi: 10.1109/MNET.001.1900273 – volume: 67 start-page: 1 year: 2020 ident: ref35 article-title: A SDN-based intelligent prediction approach to power traffic identification and monitoring for smart network access publication-title: Wireless Networks – volume: 2 start-page: 2 year: 2019 ident: ref34 article-title: Survey of intrusion detection systems: Techniques, datasets and challenges publication-title: Cybersecurity doi: 10.1186/s42400-019-0038-7 – volume: 24 start-page: 505 year: 2018 ident: ref23 article-title: Artificial intelligence and the ‘good society’: The US, EU, and UK approach publication-title: Science and Engineering Ethics – start-page: 1 year: 2018 ident: ref14 article-title: Deployment of robust security scheme in SDN based 5G network over NFV enabled cloud environment publication-title: IEEE Transactions on Emerging Topics in Computing – start-page: 169 year: 2017 ident: ref19 article-title: Towards provisioning of SDN/NFV-based security enablers for integrated protection of IoT systems – ident: ref4 – start-page: 866 year: 2019 ident: ref37 article-title: Detection of distributed denial of service attack using NSL-KDD dataset: A survey – volume: 10 start-page: 166 year: 2019 ident: ref29 article-title: Cloud server security using bio-cryptography publication-title: International Journal of Advanced Computer Science and Applications doi: 10.14569/IJACSA.2019.0100321 – volume: 10 start-page: 82 year: 2019 ident: ref18 article-title: Blockchain: Securing internet of medical things (IoMT) publication-title: International Journal of Advanced Computer Science and Applications doi: 10.14569/IJACSA.2019.0100110 – volume: 19 start-page: 1567 year: 2017 ident: ref15 article-title: SDN/NFV-based mobile packet core network architectures: A survey publication-title: IEEE Communications Surveys & Tutorials doi: 10.1109/COMST.2017.2690823 – start-page: 1 year: 2019 ident: ref20 article-title: NFV-driven intrusion detection for smart manufacturing – volume: 21 start-page: 2671 year: 2019 ident: ref7 article-title: Network intrusion detection for IoT security based on learning techniques publication-title: IEEE Communications Surveys and Tutorials doi: 10.1109/COMST.2019.2896380 – start-page: 265 year: 2018 ident: ref17 article-title: Detection of DDoS attacks in software defined networks – start-page: 1 year: 2019 ident: ref3 article-title: An intuitive study: Intrusion detection systems and anomalies, how AI can be used as a tool to enable the majority, in 5G era – volume: 38 start-page: 1262 year: 2020 ident: ref21 article-title: Virtual IoT honeynets to mitigate cyberattacks in SDN/NFV-enabled IoT networks publication-title: IEEE Journal on Selected Areas in Communications doi: 10.1109/JSAC.2020.2986621 – start-page: 1 year: 2018 ident: ref28 article-title: The mouseworld, a security traffic analysis lab based on NFV/SDN – volume: 2020 start-page: 1 year: 2020 ident: ref10 article-title: Security of cloud computing using adaptive neural fuzzy inference system publication-title: Security and Communication Networks doi: 10.1155/2020/5352108 – volume: 4 start-page: 1 year: 2018 ident: ref25 article-title: Neuro-biological emotionally intelligent model for human inspired empathetic agents publication-title: Journal of Cognitive Systems – volume: 8 start-page: 114066 year: 2020 ident: ref16 article-title: A machine learning security framework for IoT systems publication-title: IEEE Access doi: 10.1109/ACCESS.2020.2996214 – volume: 2019 start-page: 1 year: 2019 ident: ref2 article-title: Ensuring the confidentiality of nuclear information at cloud using modular encryption standard publication-title: Security and Communication Networks doi: 10.1155/2019/2509898 – volume: 17 start-page: 77 year: 2017 ident: ref24 article-title: Holographic interface management in the age of artificial intelligence publication-title: International Journal of Computer Science and Network Security – start-page: 1 year: 2018 ident: ref36 article-title: Evaluation of Apache spot’s machine learning capabilities in an SDN/NFV enabled environment – volume: 65 start-page: 139 year: 2018 ident: ref1 article-title: European Union’s general data protection regulation, 2018: A brief overview publication-title: Annals of Library and Information Studies – volume: 12 start-page: 4255 year: 2020 ident: ref9 article-title: Software-defined networking approaches for link failure recovery: A survey publication-title: Sustainability doi: 10.3390/su12104255 – year: 2017 ident: ref30 article-title: DELTA: A security assessment framework for software-defined networks – volume: 93 start-page: 687 year: 2019 ident: ref13 article-title: Implementation of a real-time network traffic monitoring service with network functions virtualization publication-title: Future Generation Computer Systems doi: 10.1016/j.future.2018.08.050 – volume: 179 start-page: 107364 year: 2020 ident: ref22 article-title: Multi-layered intrusion detection and prevention in the SDN/NFV enabled cloud of 5G networks using AI-based defense mechanisms publication-title: Computer Networks doi: 10.1016/j.comnet.2020.107364 |
| SSID | ssj0036390 |
| Score | 2.360528 |
| Snippet | With the rising demand for data access, network service providers face the challenge of growing their capital and operating costs while at the same time... |
| SourceID | proquest crossref |
| SourceType | Aggregation Database Enrichment Source Index Database |
| StartPage | 2723 |
| SubjectTerms | Abnormalities Anomalies Communications traffic Cybersecurity Decision making Machine learning Maintenance costs Network security Query languages Software-defined networking Source code Structured Query Language-SQL Support vector machines Traffic control Utilities Virtual environments |
| Title | Machine Learning Empowered Security Management and Quality of Service Provision in SDN-NFV Environment |
| URI | https://www.proquest.com/docview/2474506890 |
| Volume | 66 |
| WOSCitedRecordID | wos000604616100001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVPQU databaseName: ProQuest Central Database Suite (ProQuest) customDbUrl: eissn: 1546-2226 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0036390 issn: 1546-2226 databaseCode: BENPR dateStart: 20040101 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Publicly Available Content Database customDbUrl: eissn: 1546-2226 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0036390 issn: 1546-2226 databaseCode: PIMPY dateStart: 20040101 isFulltext: true titleUrlDefault: http://search.proquest.com/publiccontent providerName: ProQuest |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV07T8MwELagZWChPEWhIA8sDKZp_Ig9IR6tQKJRRAGVKUpsB1WiaWkLEv8eO3GourAwZYgTRfns78535_sAOGO-5FoxgTjmGlkNa8SVlyLtESKZJ1KcFqolD0EY8uFQRC7gNndllRUnFkStJtLGyNs-CQj1GBfe5fQDWdUom111EhrroG47lZl5Xr_uhtFjxcXY2N_iSCQlDPnGmpWJSuOyeKQtx7aFod-5sJk1QVYN0yovF8am1_jvZ26DLedmwqtyXuyANZ3vgkYl4QDdit4DWb8optTQ9Vl9g93x1AqnaQUHTtoOLktkYJIrWLbd-IaTDDqmgZENTNi4GxzlcHAborD3ArvLM3T74LnXfbq5Q056AUncwQukOdE080UqfGpAZjgx1ECF6tBE8CRQZpNHJTVjcKA4kVQFNGHG-WQ8xYwriQ9ALZ_k-hBARnVmnKSO72cpYVkqLGVkmRJBIqnx_pqgXf33WLq-5FYe4z02-5MCqdggFVuk4hKpJjj_fWJa9uT4Y2yrwil2q3MeL0E6-vv2Mdi07ypDLi1QW8w-9QnYkF-L0Xx26iabuUb3_ej1B4R73XI |
| linkProvider | ProQuest |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Nb9MwGH5VOiS4UL4mBgV82A47mKb-in2Ypom1WrU2qrQNjVNIbAdNYmlpC6h_it84O3GodtmtB85xLCd-9Lxf9vsA7AuipTVCYUmlxV7DGksT5dhGjGkRqZzmlWrJOE4SeX2tpi3429yF8ccqG06siNrMtM-R9wiLGY-EVNHx_Cf2qlG-utpIaNSwOLfrPy5kWx6NTt3-HhAyHFx-PsNBVQBr2qcrbCWzvCAqV4S79QuaOdRzZfo8UzKLjYtfuOZuDI2NZJqbmGfC-VVC5lRIo6mb9xHsMA_2NuxMR5Pp14b7qbP31RVMzgQmznrWhVHnIkWsp299y0TS_-QreYrdN4T37UBl3Iad_-23PIdnwY1GJzXuX0DLli-h00hUoMBYr6CYVIdFLQp9ZL-jwe3cC8NZgy6CdB_aHAFCWWlQ3VZkjWYFCkyKpj7x4vOK6KZEF6cJToZf0GBzR_A1XG3la3ehXc5K-waQ4LZwTmCfkCJnosiVp8SiMCrONHfe7R70mn1Odei77uU_fqQu_qqQkTpkpB4ZaY2MPTj898a87jnywNhug4s0sM8y3YDi7cOPP8KTs8vJOB2PkvN38NTPW6eXutBeLX7Z9_BY_17dLBcfAtARfNs2iO4A_QU3Pw |
| 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%3Ajournal&rft.genre=article&rft.atitle=Machine+Learning+Empowered+Security+Management+and+Quality+of+Service+Provision+in+SDN-NFV+Environment&rft.jtitle=Computers%2C+materials+%26+continua&rft.au=Shahzadi%2C+Shumaila&rft.au=Ahmad%2C+Fahad&rft.au=Basharat%2C+Asma&rft.au=Alruwaili%2C+Madallah&rft.date=2021&rft.issn=1546-2226&rft.volume=66&rft.issue=3&rft.spage=2723&rft.epage=2749&rft_id=info:doi/10.32604%2Fcmc.2021.014594&rft.externalDBID=n%2Fa&rft.externalDocID=10_32604_cmc_2021_014594 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1546-2226&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1546-2226&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1546-2226&client=summon |