Fuzzy logic-based DDoS attacks and network traffic anomaly detection methods: Classification, overview, and future perspectives
Nowadays, cybersecurity challenges and their ever-growing complexity are the main concerns for various information technology-driven organizations and companies. Although several intrusion detection systems have been introduced in an attempt to deal with zero-day cybersecurity attacks, computer syst...
Saved in:
Published in | Information sciences Vol. 626; pp. 315 - 338 |
---|---|
Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Inc
01.05.2023
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | Nowadays, cybersecurity challenges and their ever-growing complexity are the main concerns for various information technology-driven organizations and companies. Although several intrusion detection systems have been introduced in an attempt to deal with zero-day cybersecurity attacks, computer systems are still highly vulnerable to various types of distributed denial of service (DDoS) attacks. This complicated cyber-attack caused many system failures and service disruptions, resulting in billions of dollars of financial loss and irrecoverable reputation damage in recent years. Considering the nonnegligible importance of business continuity in the Industry 4.0 era, this paper presents a comprehensive, systematic survey of DDoS attacks. It also proposes a hierarchy for this severe cyber threat, besides conducting deep comparisons from various perspectives between the studies published by reputed venues in this area. Furthermore, this paper recommends the most effective defensive strategies, with a focus on recently offered fuzzy-based detection methods, to mitigate such threats and bridge the gaps existing in the current intrusion detection systems and related works. The outcomes and key findings of this survey paper are highly advantageous for private companies, enterprises, and government agencies to be implemented in their local or global businesses to significantly improve business sustainability. |
---|---|
AbstractList | Nowadays, cybersecurity challenges and their ever-growing complexity are the main concerns for various information technology-driven organizations and companies. Although several intrusion detection systems have been introduced in an attempt to deal with zero-day cybersecurity attacks, computer systems are still highly vulnerable to various types of distributed denial of service (DDoS) attacks. This complicated cyber-attack caused many system failures and service disruptions, resulting in billions of dollars of financial loss and irrecoverable reputation damage in recent years. Considering the nonnegligible importance of business continuity in the Industry 4.0 era, this paper presents a comprehensive, systematic survey of DDoS attacks. It also proposes a hierarchy for this severe cyber threat, besides conducting deep comparisons from various perspectives between the studies published by reputed venues in this area. Furthermore, this paper recommends the most effective defensive strategies, with a focus on recently offered fuzzy-based detection methods, to mitigate such threats and bridge the gaps existing in the current intrusion detection systems and related works. The outcomes and key findings of this survey paper are highly advantageous for private companies, enterprises, and government agencies to be implemented in their local or global businesses to significantly improve business sustainability. |
Author | Lee, Jeong-A Masdari, Mohammad Gorgin, Saeid Javaheri, Danial |
Author_xml | – sequence: 1 givenname: Danial orcidid: 0000-0002-7275-2370 surname: Javaheri fullname: Javaheri, Danial email: javaheri@chosun.ac.kr organization: Department of Computer Engineering, Chosun University, Gwangju 61452, Republic of Korea – sequence: 2 givenname: Saeid orcidid: 0000-0001-5898-4872 surname: Gorgin fullname: Gorgin, Saeid email: gorgin@chosun.ac.kr organization: Department of Computer Engineering, Chosun University, Gwangju 61452, Republic of Korea – sequence: 3 givenname: Jeong-A orcidid: 0000-0002-5166-0629 surname: Lee fullname: Lee, Jeong-A email: jalee@chosun.ac.kr organization: Department of Computer Engineering, Chosun University, Gwangju 61452, Republic of Korea – sequence: 4 givenname: Mohammad surname: Masdari fullname: Masdari, Mohammad email: m.masdari@iaurmia.ac.ir organization: Department of Computer Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran |
BookMark | eNp9kLFOwzAQhi0EEqXwAGx-ABJsJ7UTmFChgITEAMyWY1_AJY0r221VFl4dhzIxdDrpdN-v-78TdNi7HhA6pySnhPLLeW77kDPCipzQnHBxgEa0EizjrKaHaEQIIxlhk8kxOglhTggpBecj9D1bfX1tceferc4aFcDg21v3glWMSn8GrHqDe4gb5z9x9KptrU47t1DdFhuIoKN1PV5A_HAmXOFpp0Kw6UgN-wvs1uDXFjYXv0HtKq484CX4sBzINYRTdNSqLsDZ3xyjt9nd6_Qhe3q-f5zePGWa1SJmQhBdUd1WpoKCKUah4LqsVFUTmLTKlIY30DQ1azjwmjemZEIXlWK8qgvRimKMxC5XexeCh1ZqG3-fTK1sJymRg0c5l8mjHDxKQmXymEj6j1x6u1B-u5e53jGQKqX-XgZtoddgrE_FpXF2D_0DSc-QxQ |
CitedBy_id | crossref_primary_10_1002_ett_5056 crossref_primary_10_1007_s10207_024_00844_w crossref_primary_10_1007_s10922_024_09882_0 crossref_primary_10_1016_j_comcom_2024_04_035 crossref_primary_10_1109_ACCESS_2024_3495819 crossref_primary_10_3390_app14052173 crossref_primary_10_3390_ai5040143 crossref_primary_10_1016_j_adhoc_2023_103332 crossref_primary_10_1002_nem_2326 crossref_primary_10_1007_s11042_023_15244_w crossref_primary_10_3390_electronics13214145 crossref_primary_10_1016_j_eswa_2025_127072 crossref_primary_10_1016_j_ins_2024_121012 crossref_primary_10_1016_j_heliyon_2024_e32087 crossref_primary_10_1007_s41976_025_00204_9 crossref_primary_10_1007_s10489_024_05673_x crossref_primary_10_1016_j_oceaneng_2023_115915 crossref_primary_10_1016_j_neunet_2025_107194 crossref_primary_10_3390_app131910745 crossref_primary_10_1016_j_ins_2023_119633 crossref_primary_10_1109_TSC_2024_3433580 crossref_primary_10_1016_j_engappai_2024_108996 crossref_primary_10_1016_j_asoc_2024_112152 crossref_primary_10_1007_s11227_023_05715_0 crossref_primary_10_1016_j_ins_2023_119914 crossref_primary_10_3390_app132212374 crossref_primary_10_1016_j_ins_2024_121020 crossref_primary_10_1007_s10489_024_05288_2 crossref_primary_10_1016_j_eij_2024_100526 crossref_primary_10_2166_wst_2023_340 crossref_primary_10_1016_j_ins_2023_119770 crossref_primary_10_7717_peerj_cs_2333 crossref_primary_10_1016_j_eswa_2023_122697 crossref_primary_10_1002_ett_4921 crossref_primary_10_1007_s11042_024_20489_0 crossref_primary_10_1109_ACCESS_2023_3322205 crossref_primary_10_1007_s11761_024_00393_z crossref_primary_10_53759_7669_jmc202404010 crossref_primary_10_1007_s40747_024_01376_5 crossref_primary_10_1016_j_eswa_2024_124572 crossref_primary_10_1109_ACCESS_2024_3377690 |
Cites_doi | 10.1007/s10586-021-03281-9 10.3390/ai1010005 10.1109/TNSM.2019.2929425 10.1016/j.jpdc.2019.09.013 10.1007/s11277-021-09040-8 10.1088/1742-6596/1813/1/012046 10.1109/ACCESS.2021.3077295 10.1155/2022/5069104 10.1016/j.ins.2019.08.023 10.1016/j.jnca.2021.103111 10.1007/s00521-020-04747-4 10.1007/s10845-020-01690-y 10.1109/ICIT52682.2021.9491742 10.1109/ACCESS.2020.2997939 10.1016/j.eswa.2022.116895 10.1109/ICIEVicIVPR48672.2020.9306666 10.1109/ICICT48043.2020.9112403 10.1111/coin.12433 10.1016/j.ins.2022.11.074 10.1145/3368926.3369714 10.1016/j.cose.2020.101906 10.1016/j.future.2020.03.049 10.1016/j.asoc.2020.106301 10.1109/ACCESS.2018.2884964 10.1016/j.sysarc.2019.101701 10.1016/j.ins.2021.05.076 10.4018/IJBDCN.2020010103 10.1016/j.cose.2019.06.005 10.1016/j.comcom.2022.10.026 10.1109/ACCESS.2020.2992044 10.1016/j.jpdc.2017.12.011 10.1109/ACCESS.2020.2983986 10.1016/j.micpro.2020.103261 10.1016/j.ins.2019.08.047 10.1016/j.eswa.2019.112845 10.1016/j.knosys.2018.11.026 10.1007/s00500-018-3636-5 10.1109/FUZZ48607.2020.9177762 10.1016/j.ins.2019.05.040 10.1142/S0218126620500747 10.1109/TII.2020.3011444 |
ContentType | Journal Article |
Copyright | 2023 Elsevier Inc. |
Copyright_xml | – notice: 2023 Elsevier Inc. |
DBID | AAYXX CITATION |
DOI | 10.1016/j.ins.2023.01.067 |
DatabaseName | CrossRef |
DatabaseTitle | CrossRef |
DatabaseTitleList | |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Engineering Library & Information Science |
EISSN | 1872-6291 |
EndPage | 338 |
ExternalDocumentID | 10_1016_j_ins_2023_01_067 S0020025523000683 |
GroupedDBID | --K --M --Z -~X .DC .~1 0R~ 1B1 1OL 1RT 1~. 1~5 29I 4.4 457 4G. 5GY 5VS 7-5 71M 8P~ 9JN 9JO AAAKF AAAKG AABNK AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AARIN AAXUO AAYFN ABAOU ABBOA ABEFU ABFNM ABJNI ABMAC ABTAH ABUCO ABXDB ABYKQ ACAZW ACDAQ ACGFS ACNNM ACRLP ACZNC ADBBV ADEZE ADGUI ADJOM ADMUD ADTZH AEBSH AECPX AEKER AENEX AFFNX AFKWA AFTJW AGHFR AGUBO AGYEJ AHHHB AHJVU AHZHX AIALX AIEXJ AIGVJ AIKHN AITUG AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD APLSM ARUGR ASPBG AVWKF AXJTR AZFZN BJAXD BKOJK BLXMC CS3 DU5 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 F5P FDB FEDTE FGOYB FIRID FNPLU FYGXN G-Q GBLVA GBOLZ HAMUX HLZ HVGLF HZ~ H~9 IHE J1W JJJVA KOM LG9 LY1 M41 MHUIS MO0 MS~ N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 R2- RIG ROL RPZ SBC SDF SDG SDP SDS SES SEW SPC SPCBC SSB SSD SST SSV SSW SSZ T5K TN5 TWZ UHS WH7 WUQ XPP YYP ZMT ZY4 ~02 ~G- AATTM AAXKI AAYWO AAYXX ABWVN ACRPL ACVFH ADCNI ADNMO ADVLN AEIPS AEUPX AFJKZ AFPUW AFXIZ AGCQF AGQPQ AGRNS AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP BNPGV CITATION SSH |
ID | FETCH-LOGICAL-c297t-770c81cf8d8e32a21e36c48a890e5fad4d6bebb92b6e696bd427c38a268937f73 |
IEDL.DBID | .~1 |
ISSN | 0020-0255 |
IngestDate | Thu Apr 24 23:07:06 EDT 2025 Tue Jul 01 01:26:56 EDT 2025 Fri Feb 23 02:36:14 EST 2024 |
IsPeerReviewed | true |
IsScholarly | true |
Keywords | Fuzzy logic Network security Cyber-attacks Denial of service Anomaly detection Business sustainability |
Language | English |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c297t-770c81cf8d8e32a21e36c48a890e5fad4d6bebb92b6e696bd427c38a268937f73 |
ORCID | 0000-0002-7275-2370 0000-0002-5166-0629 0000-0001-5898-4872 |
PageCount | 24 |
ParticipantIDs | crossref_citationtrail_10_1016_j_ins_2023_01_067 crossref_primary_10_1016_j_ins_2023_01_067 elsevier_sciencedirect_doi_10_1016_j_ins_2023_01_067 |
ProviderPackageCode | CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | May 2023 2023-05-00 |
PublicationDateYYYYMMDD | 2023-05-01 |
PublicationDate_xml | – month: 05 year: 2023 text: May 2023 |
PublicationDecade | 2020 |
PublicationTitle | Information sciences |
PublicationYear | 2023 |
Publisher | Elsevier Inc |
Publisher_xml | – name: Elsevier Inc |
References | Alsirhani, Sampalli, Bodorik (b0225) 2019; 16 Jafarian, Masdari, Ghaffari, Majidzadeh (b0040) 2020 Wang, Wang, Wang (b0170) 2020; 32 Srilatha, Shyam (b0235) 2021; 24 Beslin Pajila, Golden Julie, Harold Robinson (b0075) 2022 Fang, Li, Liu, Yin, Li, Cao (b0135) 2020; 17 D. Wang, Z. Shen, W. Wu, “A Fuzzy Clustering Based Anomaly Node Detection Method for Publish/Subscribe Distributed Systems,” in Javaheri, Gorgin, Lee, Masdari (b0115) 2022; 36 Novaes, Carvalho, Lloret, Proença (b0215) 2020; 8 Fan, Wang, Zhang (b0250) 2020; 506 Karthiga, Durairaj, Nawaz, Venkatasamy, Ramasamy, Hariharasudan (b0085) 2022; 2022 Masdari, Khezri (b0015) 2020 Kwon, Kim, Kim, Suh, Kim, Kim (b0045) 2019 L. Decker, D. Leite, L. Giommi, and D. Bonacorsi, Real-time anomaly detection in data centers for log-based predictive maintenance using an evolving fuzzy-rule-based approach, in 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2020: IEEE, pp. 1-8. Manimurugan, Majdi, Mohmmed, Narmatha, Varatharajan (b0095) 2020; 79 de Miranda Rios, Inácio, Magoni, Freire (b0230) 2021; 186 Lee (b0010) 2021; 187 2021, vol. 1813, no. 1: IOP Publishing, p. 012046. Xiao, Su, Du, Jiang, Lin, Lin (b0160) 2019; 165 V.-T. Nguyen, T.-X. Nguyen, T.-M. Hoang, N.-L. Vu, “A new Anomaly Traffic Detection Based on Fuzzy Logic Approach in Wireless Sensor Networks,” in Proceedings of the Tenth International Symposium on Information and Communication Technology, 2019, pp. 205-209. Haider, Moustafa, Keshk, Fernandez, Choo, Wahab (b0180) 2020; 96 F. Farhin, I. Sultana, N. Islam, M.S. Kaiser, M.S. Rahman, M. Mahmud, Attack detection in internet of things using software defined network and fuzzy neural network, in 2020 Joint 9th International Conference on Informatics, Electronics & Vision (ICIEV) and 2020 4th International Conference on Imaging, Vision & Pattern Recognition (icIVPR), 2020: IEEE, pp. 1-6. Alabdulatif, Khalil, Kumarage, Zomaya, Yi (b0120) 2019; 127 Ateş, Özdel, Anarım (b0150) 2019 Selvakumar (b0165) 2019; 497 Lu, Wu, Gu, Liu, Zhu (b0205) 2021; vol. 5 Liu (b0175) 2020; 139 Santhosh Kumar, Parthiban (b0185) 2020; 29 Velliangiri, Pandey (b0100) 2020 Wang, Wang, Fan, Song (b0245) 2020; 8 de Campos Souza, Guimarães, Rezende, Silva Araujo, Araujo (b0130) 2020; 1 Shao, Yuan, Wang (b0055) 2021; 574 Huang, Guo, Yang, Zha, Liu, Fang (b0200) 2021; 32 Hande, Muddana (b0025) 2020; 16 Garg (b0190) 2020; 135 Nadimi-Shahraki, Zamani (b0155) 2022; 198 Velliangiri, Pandey (b0110) 2020; 110 Javaheri, Lalbakhsh, Hosseinzadeh (b0005) 2021; 9 Javaheri, Hosseinzadeh, Rahmani (b0060) 2018; 6 He, Qi, Yan, Cheng, Shi (b0065) 2023; 621 Guendouzi, Boukra (b0145) 2021 Pajila, Julie, Robinson (b0240) 2022; 122 Alsaadi, ALmuttari, Ucan, Bayat (b0070) 2022; 38 Ring, Wunderlich, Scheuring, Landes, Hotho (b0035) 2019; 86 H. Fan, Data Monitoring and Anomaly Analysis for Information Systems based on Balanced Scorecard and Fuzzy Neural Network, in 2020 International Conference on Inventive Computation Technologies (ICICT), 2020: IEEE, pp. 117-120. Wang, Yang, Nie, Ren, Li, Kuang (b0030) 2020; 513 Khan, Mehmood, Khan, Khan, Iqbal, Mashwani (b0020) 2020; 105 Chaganti, Bhushan, Ravi (b0050) 2023; 197 G.F. Scaranti, L.F. Carvalho, S. Barbon, M.L. Proença, Artificial Immune Systems and Fuzzy Logic to Detect Flooding Attacks in Software-defined networks, IEEE Access, 2020. Vijayakumar, Pradeep Mohan Kumar, Kottilingam, Karthick, Vijayakumar, Ganeshkumar (b0080) 2019; 23 M. Almseidin, J. Al-Sawwa, M. Alkasassbeh, Anomaly-based intrusion detection system using fuzzy logic, in 2021 International Conference on Information Technology (ICIT), 2021: IEEE, pp. 290-295. Jafarian (10.1016/j.ins.2023.01.067_b0040) 2020 Velliangiri (10.1016/j.ins.2023.01.067_b0110) 2020; 110 10.1016/j.ins.2023.01.067_b0210 Lu (10.1016/j.ins.2023.01.067_b0205) 2021; vol. 5 Srilatha (10.1016/j.ins.2023.01.067_b0235) 2021; 24 Guendouzi (10.1016/j.ins.2023.01.067_b0145) 2021 de Miranda Rios (10.1016/j.ins.2023.01.067_b0230) 2021; 186 10.1016/j.ins.2023.01.067_b0090 Selvakumar (10.1016/j.ins.2023.01.067_b0165) 2019; 497 Alsirhani (10.1016/j.ins.2023.01.067_b0225) 2019; 16 de Campos Souza (10.1016/j.ins.2023.01.067_b0130) 2020; 1 10.1016/j.ins.2023.01.067_b0125 Shao (10.1016/j.ins.2023.01.067_b0055) 2021; 574 Fan (10.1016/j.ins.2023.01.067_b0250) 2020; 506 Xiao (10.1016/j.ins.2023.01.067_b0160) 2019; 165 Karthiga (10.1016/j.ins.2023.01.067_b0085) 2022; 2022 10.1016/j.ins.2023.01.067_b0195 Javaheri (10.1016/j.ins.2023.01.067_b0115) 2022; 36 Ateş (10.1016/j.ins.2023.01.067_b0150) 2019 Khan (10.1016/j.ins.2023.01.067_b0020) 2020; 105 Novaes (10.1016/j.ins.2023.01.067_b0215) 2020; 8 Alsaadi (10.1016/j.ins.2023.01.067_b0070) 2022; 38 Fang (10.1016/j.ins.2023.01.067_b0135) 2020; 17 Haider (10.1016/j.ins.2023.01.067_b0180) 2020; 96 Masdari (10.1016/j.ins.2023.01.067_b0015) 2020 Pajila (10.1016/j.ins.2023.01.067_b0240) 2022; 122 Wang (10.1016/j.ins.2023.01.067_b0030) 2020; 513 Javaheri (10.1016/j.ins.2023.01.067_b0060) 2018; 6 Nadimi-Shahraki (10.1016/j.ins.2023.01.067_b0155) 2022; 198 Huang (10.1016/j.ins.2023.01.067_b0200) 2021; 32 Velliangiri (10.1016/j.ins.2023.01.067_b0100) 2020 Alabdulatif (10.1016/j.ins.2023.01.067_b0120) 2019; 127 Chaganti (10.1016/j.ins.2023.01.067_b0050) 2023; 197 He (10.1016/j.ins.2023.01.067_b0065) 2023; 621 10.1016/j.ins.2023.01.067_b0140 Wang (10.1016/j.ins.2023.01.067_b0170) 2020; 32 10.1016/j.ins.2023.01.067_b0220 Hande (10.1016/j.ins.2023.01.067_b0025) 2020; 16 Beslin Pajila (10.1016/j.ins.2023.01.067_b0075) 2022 Manimurugan (10.1016/j.ins.2023.01.067_b0095) 2020; 79 10.1016/j.ins.2023.01.067_b0105 Liu (10.1016/j.ins.2023.01.067_b0175) 2020; 139 Lee (10.1016/j.ins.2023.01.067_b0010) 2021; 187 Ring (10.1016/j.ins.2023.01.067_b0035) 2019; 86 Santhosh Kumar (10.1016/j.ins.2023.01.067_b0185) 2020; 29 Garg (10.1016/j.ins.2023.01.067_b0190) 2020; 135 Wang (10.1016/j.ins.2023.01.067_b0245) 2020; 8 Javaheri (10.1016/j.ins.2023.01.067_b0005) 2021; 9 Vijayakumar (10.1016/j.ins.2023.01.067_b0080) 2019; 23 Kwon (10.1016/j.ins.2023.01.067_b0045) 2019 |
References_xml | – volume: 16 start-page: 936 year: 2019 end-page: 949 ident: b0225 article-title: DDoS detection system: Using a set of classification algorithms controlled by fuzzy logic system in apache spark publication-title: IEEE Trans. Netw. Serv. Manag. – year: 2020 ident: b0100 article-title: Fuzzy-Taylor-elephant herd optimization inspired Deep Belief Network for DDoS attack detection and comparison with state-of-the-arts algorithms publication-title: Futur. Gener. Comput. Syst. – volume: 497 start-page: 77 year: 2019 end-page: 90 ident: b0165 article-title: Intelligent temporal classification and fuzzy rough set-based feature selection algorithm for intrusion detection system in WSNs publication-title: Inf. Sci. – volume: 187 year: 2021 ident: b0010 article-title: Towards secure intrusion detection systems using deep learning techniques: comprehensive analysis and review publication-title: J. Netw. Comput. Appl. – volume: 29 start-page: 2050074 year: 2020 ident: b0185 article-title: Scalable anomaly detection for large-scale heterogeneous data in cloud using optimal elliptic curve cryptography and gaussian kernel fuzzy C-means clustering publication-title: J. Circ., Syst. Comput. – start-page: 1 year: 2020 end-page: 19 ident: b0040 article-title: A survey and classification of the security anomaly detection mechanisms in software defined networks publication-title: Clust. Comput. – volume: 574 start-page: 84 year: 2021 end-page: 95 ident: b0055 article-title: Adaptive online learning for IoT botnet detection publication-title: Inf. Sci. – start-page: 338 year: 2019 end-page: 345 ident: b0150 article-title: Graph–based anomaly detection using fuzzy clustering publication-title: International Conference on Intelligent and Fuzzy Systems – year: 2020 ident: b0015 article-title: A survey and taxonomy of the fuzzy signature-based intrusion detection systems publication-title: Appl. Soft Comput. – reference: M. Almseidin, J. Al-Sawwa, M. Alkasassbeh, Anomaly-based intrusion detection system using fuzzy logic, in 2021 International Conference on Information Technology (ICIT), 2021: IEEE, pp. 290-295. – volume: 17 start-page: 4260 year: 2020 end-page: 4269 ident: b0135 article-title: A practical model based on anomaly detection for protecting medical IoT control services against external attacks publication-title: IEEE Trans. Ind. Inf. – volume: 79 year: 2020 ident: b0095 article-title: Intrusion detection in networks using crow search optimization algorithm with adaptive neuro-fuzzy inference system publication-title: Microprocess. Microsyst. – volume: 6 start-page: 78321 year: 2018 end-page: 78332 ident: b0060 article-title: Detection and elimination of spyware and Ransomware by intercepting kernel-level system routines publication-title: IEEE Access – reference: , 2021, vol. 1813, no. 1: IOP Publishing, p. 012046. – volume: 24 start-page: 2657 year: 2021 end-page: 2672 ident: b0235 article-title: Cloud-based intrusion detection using kernel fuzzy clustering and optimal type-2 fuzzy neural network publication-title: Clust. Comput. – start-page: 1 year: 2021 end-page: 12 ident: b0145 article-title: A new differential evolution algorithm for cooperative fuzzy rule mining: application to anomaly detection publication-title: Evol. Intel. – volume: 513 start-page: 65 year: 2020 end-page: 83 ident: b0030 article-title: Data-driven software defined network attack detection: state-of-the-art and perspectives publication-title: Inf. Sci. – volume: 122 start-page: 3053 year: 2022 end-page: 3083 ident: b0240 article-title: FBDR-Fuzzy based DDoS attack Detection and Recovery mechanism for wireless sensor networks publication-title: Wirel. Pers. Commun. – start-page: 1 year: 2019 end-page: 13 ident: b0045 article-title: A survey of deep learning-based network anomaly detection publication-title: Clust. Comput. – reference: L. Decker, D. Leite, L. Giommi, and D. Bonacorsi, Real-time anomaly detection in data centers for log-based predictive maintenance using an evolving fuzzy-rule-based approach, in 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2020: IEEE, pp. 1-8. – reference: G.F. Scaranti, L.F. Carvalho, S. Barbon, M.L. Proença, Artificial Immune Systems and Fuzzy Logic to Detect Flooding Attacks in Software-defined networks, IEEE Access, 2020. – volume: 8 start-page: 63381 year: 2020 end-page: 63389 ident: b0245 article-title: Network traffic anomaly detection algorithm based on intuitionistic fuzzy time series graph mining publication-title: IEEE Access – volume: 197 start-page: 96 year: 2023 end-page: 112 ident: b0050 article-title: A survey on Blockchain solutions in DDoS attacks mitigation: techniques, open challenges and future directions publication-title: Comput. Commun. – volume: 506 start-page: 131 year: 2020 end-page: 147 ident: b0250 article-title: Network traffic forecasting model based on long-term intuitionistic fuzzy time series publication-title: Inf. Sci. – volume: 86 start-page: 147 year: 2019 end-page: 167 ident: b0035 article-title: A survey of network-based intrusion detection data sets publication-title: Comput. Secur. – volume: 2022 year: 2022 ident: b0085 article-title: Intelligent Intrusion Detection System for VANET using machine learning and deep learning approaches publication-title: Wirel. Commun. Mob. Comput. – volume: 32 start-page: 13035 year: 2020 end-page: 13049 ident: b0170 article-title: A density weighted fuzzy outlier clustering approach for class imbalanced learning publication-title: Neural Comput. Applic. – reference: V.-T. Nguyen, T.-X. Nguyen, T.-M. Hoang, N.-L. Vu, “A new Anomaly Traffic Detection Based on Fuzzy Logic Approach in Wireless Sensor Networks,” in Proceedings of the Tenth International Symposium on Information and Communication Technology, 2019, pp. 205-209. – volume: 23 start-page: 2655 year: 2019 end-page: 2667 ident: b0080 article-title: An adaptive neuro-fuzzy logic based jamming detection system in WSN publication-title: Soft. Comput. – volume: 105 year: 2020 ident: b0020 article-title: A survey on intrusion detection and prevention in wireless ad-hoc networks publication-title: J. Syst. Archit. – volume: 186 year: 2021 ident: b0230 article-title: Detection of reduction-of-quality DDoS attacks using Fuzzy Logic and machine learning algorithms publication-title: Comput. Netw. – volume: vol. 5 start-page: 1782 year: 2021 end-page: 1785 ident: b0205 article-title: An anomaly detection parameter optimization algorithm for data center data – reference: D. Wang, Z. Shen, W. Wu, “A Fuzzy Clustering Based Anomaly Node Detection Method for Publish/Subscribe Distributed Systems,” in – volume: 165 start-page: 149 year: 2019 end-page: 156 ident: b0160 article-title: SFAD: Toward effective anomaly detection based on session feature similarity publication-title: Knowl.-Based Syst. – volume: 139 year: 2020 ident: b0175 article-title: Adaptive intrusion detection via GA-GOGMM-based pattern learning with fuzzy rough set-based attribute selection publication-title: Expert Syst. Appl. – volume: 8 start-page: 83765 year: 2020 end-page: 83781 ident: b0215 article-title: Long short-term memory and fuzzy logic for anomaly detection and mitigation in software-defined network environment publication-title: IEEE Access – volume: 9 start-page: 69951 year: 2021 end-page: 69970 ident: b0005 article-title: A novel method for detecting future generations of targeted and metamorphic malware based on genetic algorithm publication-title: IEEE Access – volume: 127 start-page: 209 year: 2019 end-page: 223 ident: b0120 article-title: Privacy-preserving anomaly detection in the cloud for quality assured decision-making in smart cities publication-title: J. Parallel Distrib. Comput. – volume: 36 year: 2022 ident: b0115 article-title: An improved discrete harris hawk optimization algorithm for efficient workflow scheduling in multi-fog computing publication-title: Sustainable Comput. Inf. Syst. – volume: 198 year: 2022 ident: b0155 article-title: DMDE: Diversity-maintained multi-trial vector differential evolution algorithm for non-decomposition large-scale global optimization publication-title: Expert Syst. Appl. – start-page: 1 year: 2022 end-page: 25 ident: b0075 article-title: ABAP: anchor node based DDoS attack detection using adaptive neuro-fuzzy inference system publication-title: Wirel. Pers. Commun. – volume: 110 start-page: 80 year: 2020 end-page: 90 ident: b0110 article-title: Fuzzy-Taylor-elephant herd optimization inspired Deep Belief Network for DDoS attack detection and comparison with state-of-the-arts algorithms publication-title: Futur. Gener. Comput. Syst. – reference: F. Farhin, I. Sultana, N. Islam, M.S. Kaiser, M.S. Rahman, M. Mahmud, Attack detection in internet of things using software defined network and fuzzy neural network, in 2020 Joint 9th International Conference on Informatics, Electronics & Vision (ICIEV) and 2020 4th International Conference on Imaging, Vision & Pattern Recognition (icIVPR), 2020: IEEE, pp. 1-6. – volume: 32 start-page: 1845 year: 2021 end-page: 1861 ident: b0200 article-title: A weighted fuzzy C-means clustering method with density peak for anomaly detection in IoT-enabled manufacturing process publication-title: J. Intell. Manuf. – volume: 135 start-page: 219 year: 2020 end-page: 233 ident: b0190 article-title: En-ABC: An ensemble artificial bee colony based anomaly detection scheme for cloud environment publication-title: J. Parallel Distrib. Comput. – reference: H. Fan, Data Monitoring and Anomaly Analysis for Information Systems based on Balanced Scorecard and Fuzzy Neural Network, in 2020 International Conference on Inventive Computation Technologies (ICICT), 2020: IEEE, pp. 117-120. – volume: 16 start-page: 28 year: 2020 end-page: 47 ident: b0025 article-title: A survey on intrusion detection system for software defined networks (SDN) publication-title: Int. J. Business Data Commun. Network. (IJBDCN) – volume: 96 year: 2020 ident: b0180 article-title: FGMC-HADS: Fuzzy Gaussian mixture-based correntropy models for detecting zero-day attacks from linux systems publication-title: Comput. Secur. – volume: 1 start-page: 92 year: 2020 end-page: 116 ident: b0130 article-title: Detection of anomalies in large-scale cyberattacks using fuzzy neural networks publication-title: AI – volume: 621 start-page: 596 year: 2023 end-page: 610 ident: b0065 article-title: Adaptive fuzzy resilient control for switched systems with state constraints under deception attacks publication-title: Inf. Sci. – volume: 38 start-page: 855 year: 2022 end-page: 875 ident: b0070 article-title: An adapting soft computing model for intrusion detection system publication-title: Comput. Intell. – volume: 24 start-page: 2657 issue: 3 year: 2021 ident: 10.1016/j.ins.2023.01.067_b0235 article-title: Cloud-based intrusion detection using kernel fuzzy clustering and optimal type-2 fuzzy neural network publication-title: Clust. Comput. doi: 10.1007/s10586-021-03281-9 – volume: 1 start-page: 92 issue: 1 year: 2020 ident: 10.1016/j.ins.2023.01.067_b0130 article-title: Detection of anomalies in large-scale cyberattacks using fuzzy neural networks publication-title: AI doi: 10.3390/ai1010005 – volume: 16 start-page: 936 issue: 3 year: 2019 ident: 10.1016/j.ins.2023.01.067_b0225 article-title: DDoS detection system: Using a set of classification algorithms controlled by fuzzy logic system in apache spark publication-title: IEEE Trans. Netw. Serv. Manag. doi: 10.1109/TNSM.2019.2929425 – start-page: 338 year: 2019 ident: 10.1016/j.ins.2023.01.067_b0150 article-title: Graph–based anomaly detection using fuzzy clustering – volume: 135 start-page: 219 year: 2020 ident: 10.1016/j.ins.2023.01.067_b0190 article-title: En-ABC: An ensemble artificial bee colony based anomaly detection scheme for cloud environment publication-title: J. Parallel Distrib. Comput. doi: 10.1016/j.jpdc.2019.09.013 – start-page: 1 year: 2020 ident: 10.1016/j.ins.2023.01.067_b0040 article-title: A survey and classification of the security anomaly detection mechanisms in software defined networks publication-title: Clust. Comput. – volume: 122 start-page: 3053 issue: 4 year: 2022 ident: 10.1016/j.ins.2023.01.067_b0240 article-title: FBDR-Fuzzy based DDoS attack Detection and Recovery mechanism for wireless sensor networks publication-title: Wirel. Pers. Commun. doi: 10.1007/s11277-021-09040-8 – ident: 10.1016/j.ins.2023.01.067_b0195 doi: 10.1088/1742-6596/1813/1/012046 – volume: 9 start-page: 69951 year: 2021 ident: 10.1016/j.ins.2023.01.067_b0005 article-title: A novel method for detecting future generations of targeted and metamorphic malware based on genetic algorithm publication-title: IEEE Access doi: 10.1109/ACCESS.2021.3077295 – volume: 2022 year: 2022 ident: 10.1016/j.ins.2023.01.067_b0085 article-title: Intelligent Intrusion Detection System for VANET using machine learning and deep learning approaches publication-title: Wirel. Commun. Mob. Comput. doi: 10.1155/2022/5069104 – volume: 506 start-page: 131 year: 2020 ident: 10.1016/j.ins.2023.01.067_b0250 article-title: Network traffic forecasting model based on long-term intuitionistic fuzzy time series publication-title: Inf. Sci. doi: 10.1016/j.ins.2019.08.023 – volume: 187 year: 2021 ident: 10.1016/j.ins.2023.01.067_b0010 article-title: Towards secure intrusion detection systems using deep learning techniques: comprehensive analysis and review publication-title: J. Netw. Comput. Appl. doi: 10.1016/j.jnca.2021.103111 – volume: 32 start-page: 13035 issue: 16 year: 2020 ident: 10.1016/j.ins.2023.01.067_b0170 article-title: A density weighted fuzzy outlier clustering approach for class imbalanced learning publication-title: Neural Comput. Applic. doi: 10.1007/s00521-020-04747-4 – volume: 32 start-page: 1845 issue: 7 year: 2021 ident: 10.1016/j.ins.2023.01.067_b0200 article-title: A weighted fuzzy C-means clustering method with density peak for anomaly detection in IoT-enabled manufacturing process publication-title: J. Intell. Manuf. doi: 10.1007/s10845-020-01690-y – volume: 186 year: 2021 ident: 10.1016/j.ins.2023.01.067_b0230 article-title: Detection of reduction-of-quality DDoS attacks using Fuzzy Logic and machine learning algorithms publication-title: Comput. Netw. – ident: 10.1016/j.ins.2023.01.067_b0140 doi: 10.1109/ICIT52682.2021.9491742 – ident: 10.1016/j.ins.2023.01.067_b0210 doi: 10.1109/ACCESS.2020.2997939 – volume: 198 year: 2022 ident: 10.1016/j.ins.2023.01.067_b0155 article-title: DMDE: Diversity-maintained multi-trial vector differential evolution algorithm for non-decomposition large-scale global optimization publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2022.116895 – ident: 10.1016/j.ins.2023.01.067_b0090 doi: 10.1109/ICIEVicIVPR48672.2020.9306666 – ident: 10.1016/j.ins.2023.01.067_b0125 doi: 10.1109/ICICT48043.2020.9112403 – start-page: 1 year: 2019 ident: 10.1016/j.ins.2023.01.067_b0045 article-title: A survey of deep learning-based network anomaly detection publication-title: Clust. Comput. – volume: 38 start-page: 855 issue: 3 year: 2022 ident: 10.1016/j.ins.2023.01.067_b0070 article-title: An adapting soft computing model for intrusion detection system publication-title: Comput. Intell. doi: 10.1111/coin.12433 – volume: 621 start-page: 596 year: 2023 ident: 10.1016/j.ins.2023.01.067_b0065 article-title: Adaptive fuzzy resilient control for switched systems with state constraints under deception attacks publication-title: Inf. Sci. doi: 10.1016/j.ins.2022.11.074 – ident: 10.1016/j.ins.2023.01.067_b0220 doi: 10.1145/3368926.3369714 – volume: 96 year: 2020 ident: 10.1016/j.ins.2023.01.067_b0180 article-title: FGMC-HADS: Fuzzy Gaussian mixture-based correntropy models for detecting zero-day attacks from linux systems publication-title: Comput. Secur. doi: 10.1016/j.cose.2020.101906 – volume: 110 start-page: 80 year: 2020 ident: 10.1016/j.ins.2023.01.067_b0110 article-title: Fuzzy-Taylor-elephant herd optimization inspired Deep Belief Network for DDoS attack detection and comparison with state-of-the-arts algorithms publication-title: Futur. Gener. Comput. Syst. doi: 10.1016/j.future.2020.03.049 – volume: vol. 5 start-page: 1782 year: 2021 ident: 10.1016/j.ins.2023.01.067_b0205 article-title: An anomaly detection parameter optimization algorithm for data center data – year: 2020 ident: 10.1016/j.ins.2023.01.067_b0015 article-title: A survey and taxonomy of the fuzzy signature-based intrusion detection systems publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2020.106301 – volume: 6 start-page: 78321 year: 2018 ident: 10.1016/j.ins.2023.01.067_b0060 article-title: Detection and elimination of spyware and Ransomware by intercepting kernel-level system routines publication-title: IEEE Access doi: 10.1109/ACCESS.2018.2884964 – volume: 105 year: 2020 ident: 10.1016/j.ins.2023.01.067_b0020 article-title: A survey on intrusion detection and prevention in wireless ad-hoc networks publication-title: J. Syst. Archit. doi: 10.1016/j.sysarc.2019.101701 – volume: 574 start-page: 84 year: 2021 ident: 10.1016/j.ins.2023.01.067_b0055 article-title: Adaptive online learning for IoT botnet detection publication-title: Inf. Sci. doi: 10.1016/j.ins.2021.05.076 – volume: 16 start-page: 28 issue: 1 year: 2020 ident: 10.1016/j.ins.2023.01.067_b0025 article-title: A survey on intrusion detection system for software defined networks (SDN) publication-title: Int. J. Business Data Commun. Network. (IJBDCN) doi: 10.4018/IJBDCN.2020010103 – start-page: 1 year: 2022 ident: 10.1016/j.ins.2023.01.067_b0075 article-title: ABAP: anchor node based DDoS attack detection using adaptive neuro-fuzzy inference system publication-title: Wirel. Pers. Commun. – year: 2020 ident: 10.1016/j.ins.2023.01.067_b0100 article-title: Fuzzy-Taylor-elephant herd optimization inspired Deep Belief Network for DDoS attack detection and comparison with state-of-the-arts algorithms publication-title: Futur. Gener. Comput. Syst. doi: 10.1016/j.future.2020.03.049 – volume: 86 start-page: 147 year: 2019 ident: 10.1016/j.ins.2023.01.067_b0035 article-title: A survey of network-based intrusion detection data sets publication-title: Comput. Secur. doi: 10.1016/j.cose.2019.06.005 – start-page: 1 year: 2021 ident: 10.1016/j.ins.2023.01.067_b0145 article-title: A new differential evolution algorithm for cooperative fuzzy rule mining: application to anomaly detection publication-title: Evol. Intel. – volume: 197 start-page: 96 year: 2023 ident: 10.1016/j.ins.2023.01.067_b0050 article-title: A survey on Blockchain solutions in DDoS attacks mitigation: techniques, open challenges and future directions publication-title: Comput. Commun. doi: 10.1016/j.comcom.2022.10.026 – volume: 8 start-page: 83765 year: 2020 ident: 10.1016/j.ins.2023.01.067_b0215 article-title: Long short-term memory and fuzzy logic for anomaly detection and mitigation in software-defined network environment publication-title: IEEE Access doi: 10.1109/ACCESS.2020.2992044 – volume: 127 start-page: 209 year: 2019 ident: 10.1016/j.ins.2023.01.067_b0120 article-title: Privacy-preserving anomaly detection in the cloud for quality assured decision-making in smart cities publication-title: J. Parallel Distrib. Comput. doi: 10.1016/j.jpdc.2017.12.011 – volume: 8 start-page: 63381 year: 2020 ident: 10.1016/j.ins.2023.01.067_b0245 article-title: Network traffic anomaly detection algorithm based on intuitionistic fuzzy time series graph mining publication-title: IEEE Access doi: 10.1109/ACCESS.2020.2983986 – volume: 79 year: 2020 ident: 10.1016/j.ins.2023.01.067_b0095 article-title: Intrusion detection in networks using crow search optimization algorithm with adaptive neuro-fuzzy inference system publication-title: Microprocess. Microsyst. doi: 10.1016/j.micpro.2020.103261 – volume: 513 start-page: 65 year: 2020 ident: 10.1016/j.ins.2023.01.067_b0030 article-title: Data-driven software defined network attack detection: state-of-the-art and perspectives publication-title: Inf. Sci. doi: 10.1016/j.ins.2019.08.047 – volume: 139 year: 2020 ident: 10.1016/j.ins.2023.01.067_b0175 article-title: Adaptive intrusion detection via GA-GOGMM-based pattern learning with fuzzy rough set-based attribute selection publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2019.112845 – volume: 165 start-page: 149 year: 2019 ident: 10.1016/j.ins.2023.01.067_b0160 article-title: SFAD: Toward effective anomaly detection based on session feature similarity publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2018.11.026 – volume: 23 start-page: 2655 issue: 8 year: 2019 ident: 10.1016/j.ins.2023.01.067_b0080 article-title: An adaptive neuro-fuzzy logic based jamming detection system in WSN publication-title: Soft. Comput. doi: 10.1007/s00500-018-3636-5 – ident: 10.1016/j.ins.2023.01.067_b0105 doi: 10.1109/FUZZ48607.2020.9177762 – volume: 497 start-page: 77 year: 2019 ident: 10.1016/j.ins.2023.01.067_b0165 article-title: Intelligent temporal classification and fuzzy rough set-based feature selection algorithm for intrusion detection system in WSNs publication-title: Inf. Sci. doi: 10.1016/j.ins.2019.05.040 – volume: 29 start-page: 2050074 issue: 05 year: 2020 ident: 10.1016/j.ins.2023.01.067_b0185 article-title: Scalable anomaly detection for large-scale heterogeneous data in cloud using optimal elliptic curve cryptography and gaussian kernel fuzzy C-means clustering publication-title: J. Circ., Syst. Comput. doi: 10.1142/S0218126620500747 – volume: 17 start-page: 4260 issue: 6 year: 2020 ident: 10.1016/j.ins.2023.01.067_b0135 article-title: A practical model based on anomaly detection for protecting medical IoT control services against external attacks publication-title: IEEE Trans. Ind. Inf. doi: 10.1109/TII.2020.3011444 – volume: 36 year: 2022 ident: 10.1016/j.ins.2023.01.067_b0115 article-title: An improved discrete harris hawk optimization algorithm for efficient workflow scheduling in multi-fog computing publication-title: Sustainable Comput. Inf. Syst. |
SSID | ssj0004766 |
Score | 2.5929062 |
Snippet | Nowadays, cybersecurity challenges and their ever-growing complexity are the main concerns for various information technology-driven organizations and... |
SourceID | crossref elsevier |
SourceType | Enrichment Source Index Database Publisher |
StartPage | 315 |
SubjectTerms | Anomaly detection Business sustainability Cyber-attacks Denial of service Fuzzy logic Network security |
Title | Fuzzy logic-based DDoS attacks and network traffic anomaly detection methods: Classification, overview, and future perspectives |
URI | https://dx.doi.org/10.1016/j.ins.2023.01.067 |
Volume | 626 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LS8QwEA6iFz2IT3yt5CAexGqbpnl4W9RlVfSigreSpCmsaHdxuwc96F83k6Y-QD14bEjakklnvibffIPQDlepiXlpI0WEiWhSskhlUkYqESVXOhZGw9bA5RXr39Lzu-xuCh23uTBAqwy-v_Hp3luHlsMwm4ejwQByfIlHxA5EQ6IDKH5SymGVH7x-0jxcC2toHnEEvduTTc_xGlSg2E1Sr9zpS83_EJu-xJveApoPQBF3m3dZRFO2WkJzX-QDl1AnJB3gXRyyimCWcfhcl9Fbb_Ly8oy9d4sgXBX45GR4jVVdQ2Y9VlWBq4YGjusnBWISrm34qB6ecWFrT9KqcFNjenyEff1MYBb5x-xjIH_CwcK-v1EjToJHn8mb4xV02zu9Oe5HoeBCZIjktUPasRGJKUUhbEoUSWzKDBVKyNhmpSpowbTVWhLNLJNMF5RwkwpFGKCekqeraLoaVnYNYe1wp0hVVngmKeVSKvc3nAjJTJZZLtdR3E51boIaORTFeMhb2tl97qyTg3XyOMmdddbR3seQUSPF8Vdn2tov_7aechcqfh-28b9hm2gWrhoi5Baarp8mtuPASq23_WrcRjPds4v-1TswAuqW |
linkProvider | Elsevier |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1NT9wwEB3BcgAOFaWtgJbWB8QBEZE4iT96Q9DVUmAvgMTNsh1HWgTZFYQDXPjreBwHqFR66DXJJJHHmRnH770B2OI6tymvXaKpsEmR1SzRpZSJzkTNtUmFNfhr4HTMRhfF78vycg4Oei4Mwipj7O9ieojW8cheHM292WSCHF8aKmJfRCPRIZ-HBVSnKgewsH90PBq_0iN5t2WJKyU06Dc3A8xr0qBoN82DeGfoNv-X9PQm5QxX4EOsFcl-9zofYc41q7D8RkFwFTYj74Bsk0gswoEm8Yv9BE_D-8fHBxICXIIZqyKHh9MzotsWyfVENxVpOiQ4aW816kn4Y9Mbff1AKtcGnFZDujbTdz9JaKGJ4KLwmF2C-E_cW9gNN-r0Scjslb959xkuhr_OD0ZJ7LmQWCp564vt1IrM1qISLqeaZi5nthBayNSVta6KihlnjKSGOSaZqQrKbS40ZVj41Dz_AoNm2rg1IMaXniLXZRXApAWXUvsFcSYks2XpuFyHtB9qZaMgOfbFuFY98uxKee8o9I5KM-W9sw47LyazTo3jXxcXvf_UH1NK-WzxvtnG_5n9gMXR-emJOjkaH3-FJTzT4SK_waC9vXebvnZpzfc4N58BPErtRw |
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=Fuzzy+logic-based+DDoS+attacks+and+network+traffic+anomaly+detection+methods%3A+Classification%2C+overview%2C+and+future+perspectives&rft.jtitle=Information+sciences&rft.au=Javaheri%2C+Danial&rft.au=Gorgin%2C+Saeid&rft.au=Lee%2C+Jeong-A&rft.au=Masdari%2C+Mohammad&rft.date=2023-05-01&rft.pub=Elsevier+Inc&rft.issn=0020-0255&rft.eissn=1872-6291&rft.volume=626&rft.spage=315&rft.epage=338&rft_id=info:doi/10.1016%2Fj.ins.2023.01.067&rft.externalDocID=S0020025523000683 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0020-0255&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0020-0255&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0020-0255&client=summon |