Support Vector Machine (SVM) based Detection for Volumetric Bandwidth Distributed Denial of Service (DVB-DDOS) attack within gigabit Passive Optical Network Article Swipe
Sumayya Bibi
,
Nadiatulhuda Zulkifli
,
Ghazanfar Ali Safdar
,
Sajid Iqbal
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.22441/sinergi.2025.1.017
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.22441/sinergi.2025.1.017
The dynamic bandwidth allocation (DBA) algorithm is highly impactful in improving the network performance of gigabit passive optical networks (GPON). Network security is an important component of today’s networks to combat security attacks, including GPON. However, the literature contains reports highlighting its vulnerability to specific attacks, thereby raising concerns. In this work, we argue that the impact of a volumetric bandwidth distributed denial of service (DVB-DDOS) attack can be mitigated by improving the dynamic bandwidth assignment (DBA) scheme, which is used in PON to manage the US bandwidth at the optical line terminal (OLT). Thus, this study uses a support vector machine (SVM), a machine learning approach, to learn the optical network unit (ONU) traffic demand patterns and presents a hybrid security-aware DBA (HSA-DBA) scheme that is capable of distinguishing malicious ONUs from normal ONUs. In this article, we consider the deployment of the HSA-DBA scheme in OMNET++ to acquire the monitoring data samples used to train the ML technique for the effective classification of ONUs. The simulation findings revealed a mean upstream delay improvement of up to 63% due to the security feature offered by the mechanism. Besides, significant reductions for the upstream delay performance recorded at 63% TCONT2, 65% TCONT3, and 95% TCONT4 and for frame loss rate reduction for normal ONU traffic, respectively, were observed in comparison to the non-secure DBA mechanism. This research provides a significant stride towards secure GPONs, ensuring reliable defense mechanisms are in place, which paves the way for more resilient future broadband network infrastructures.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.22441/sinergi.2025.1.017
- https://publikasi.mercubuana.ac.id/index.php/sinergi/article/download/26933/9195
- OA Status
- diamond
- References
- 27
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4406299039
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4406299039Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.22441/sinergi.2025.1.017Digital Object Identifier
- Title
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Support Vector Machine (SVM) based Detection for Volumetric Bandwidth Distributed Denial of Service (DVB-DDOS) attack within gigabit Passive Optical NetworkWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-01-04Full publication date if available
- Authors
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Sumayya Bibi, Nadiatulhuda Zulkifli, Ghazanfar Ali Safdar, Sajid IqbalList of authors in order
- Landing page
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https://doi.org/10.22441/sinergi.2025.1.017Publisher landing page
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https://publikasi.mercubuana.ac.id/index.php/sinergi/article/download/26933/9195Direct link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
- OA URL
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https://publikasi.mercubuana.ac.id/index.php/sinergi/article/download/26933/9195Direct OA link when available
- Concepts
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Denial-of-service attack, Computer science, Passive optical network, Dynamic bandwidth allocation, Computer network, Bandwidth (computing), Network security, Real-time computing, The Internet, Wavelength-division multiplexing, Physics, Optoelectronics, Wavelength, World Wide WebTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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27Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.of | 14, 26, 57, 63, 128, 142, 164, 175 |
| abstract_inverted_index.to | 29, 43, 83, 107, 148, 155, 177, 180, 220 |
| abstract_inverted_index.up | 176 |
| abstract_inverted_index.we | 52, 138 |
| abstract_inverted_index.63% | 178, 198 |
| abstract_inverted_index.65% | 200 |
| abstract_inverted_index.95% | 203 |
| abstract_inverted_index.DBA | 122, 223 |
| abstract_inverted_index.ONU | 213 |
| abstract_inverted_index.PON | 82 |
| abstract_inverted_index.The | 0, 166 |
| abstract_inverted_index.and | 117, 202, 205 |
| abstract_inverted_index.are | 238 |
| abstract_inverted_index.can | 67 |
| abstract_inverted_index.due | 179 |
| abstract_inverted_index.for | 160, 191, 206, 211, 245 |
| abstract_inverted_index.its | 41 |
| abstract_inverted_index.the | 11, 36, 55, 72, 85, 89, 109, 140, 143, 150, 157, 161, 181, 186, 192, 221, 243 |
| abstract_inverted_index.way | 244 |
| abstract_inverted_index.ONUs | 131 |
| abstract_inverted_index.This | 225 |
| abstract_inverted_index.data | 152 |
| abstract_inverted_index.from | 132 |
| abstract_inverted_index.line | 91 |
| abstract_inverted_index.loss | 208 |
| abstract_inverted_index.mean | 171 |
| abstract_inverted_index.more | 246 |
| abstract_inverted_index.rate | 209 |
| abstract_inverted_index.that | 54, 125 |
| abstract_inverted_index.this | 50, 95, 136 |
| abstract_inverted_index.unit | 112 |
| abstract_inverted_index.used | 80, 154 |
| abstract_inverted_index.uses | 97 |
| abstract_inverted_index.were | 216 |
| abstract_inverted_index.(DBA) | 4, 76 |
| abstract_inverted_index.(ONU) | 113 |
| abstract_inverted_index.GPON. | 34 |
| abstract_inverted_index.ONUs. | 134, 165 |
| abstract_inverted_index.Thus, | 94 |
| abstract_inverted_index.argue | 53 |
| abstract_inverted_index.delay | 173, 194 |
| abstract_inverted_index.frame | 207 |
| abstract_inverted_index.learn | 108 |
| abstract_inverted_index.paves | 242 |
| abstract_inverted_index.study | 96 |
| abstract_inverted_index.train | 156 |
| abstract_inverted_index.which | 78, 241 |
| abstract_inverted_index.work, | 51 |
| abstract_inverted_index.(OLT). | 93 |
| abstract_inverted_index.(SVM), | 102 |
| abstract_inverted_index.GPONs, | 233 |
| abstract_inverted_index.TCONT4 | 204 |
| abstract_inverted_index.attack | 66 |
| abstract_inverted_index.combat | 30 |
| abstract_inverted_index.demand | 115 |
| abstract_inverted_index.denial | 62 |
| abstract_inverted_index.future | 248 |
| abstract_inverted_index.highly | 7 |
| abstract_inverted_index.hybrid | 120 |
| abstract_inverted_index.impact | 56 |
| abstract_inverted_index.manage | 84 |
| abstract_inverted_index.normal | 133, 212 |
| abstract_inverted_index.place, | 240 |
| abstract_inverted_index.scheme | 124, 145 |
| abstract_inverted_index.secure | 232 |
| abstract_inverted_index.stride | 230 |
| abstract_inverted_index.vector | 100 |
| abstract_inverted_index.(GPON). | 19 |
| abstract_inverted_index.HSA-DBA | 144 |
| abstract_inverted_index.Network | 20 |
| abstract_inverted_index.OMNET++ | 147 |
| abstract_inverted_index.TCONT2, | 199 |
| abstract_inverted_index.TCONT3, | 201 |
| abstract_inverted_index.acquire | 149 |
| abstract_inverted_index.capable | 127 |
| abstract_inverted_index.defense | 236 |
| abstract_inverted_index.dynamic | 1, 73 |
| abstract_inverted_index.feature | 183 |
| abstract_inverted_index.gigabit | 15 |
| abstract_inverted_index.machine | 101, 104 |
| abstract_inverted_index.network | 12, 111, 250 |
| abstract_inverted_index.offered | 184 |
| abstract_inverted_index.optical | 17, 90, 110 |
| abstract_inverted_index.passive | 16 |
| abstract_inverted_index.raising | 47 |
| abstract_inverted_index.reports | 39 |
| abstract_inverted_index.samples | 153 |
| abstract_inverted_index.scheme, | 77 |
| abstract_inverted_index.service | 64 |
| abstract_inverted_index.support | 99 |
| abstract_inverted_index.thereby | 46 |
| abstract_inverted_index.towards | 231 |
| abstract_inverted_index.traffic | 114 |
| abstract_inverted_index.Besides, | 188 |
| abstract_inverted_index.However, | 35 |
| abstract_inverted_index.article, | 137 |
| abstract_inverted_index.attacks, | 32, 45 |
| abstract_inverted_index.consider | 139 |
| abstract_inverted_index.contains | 38 |
| abstract_inverted_index.ensuring | 234 |
| abstract_inverted_index.learning | 105 |
| abstract_inverted_index.networks | 18, 28 |
| abstract_inverted_index.observed | 217 |
| abstract_inverted_index.patterns | 116 |
| abstract_inverted_index.presents | 118 |
| abstract_inverted_index.provides | 227 |
| abstract_inverted_index.recorded | 196 |
| abstract_inverted_index.reliable | 235 |
| abstract_inverted_index.research | 226 |
| abstract_inverted_index.revealed | 169 |
| abstract_inverted_index.security | 21, 31, 182 |
| abstract_inverted_index.specific | 44 |
| abstract_inverted_index.terminal | 92 |
| abstract_inverted_index.traffic, | 214 |
| abstract_inverted_index.upstream | 172, 193 |
| abstract_inverted_index.(HSA-DBA) | 123 |
| abstract_inverted_index.algorithm | 5 |
| abstract_inverted_index.approach, | 106 |
| abstract_inverted_index.bandwidth | 2, 60, 74, 87 |
| abstract_inverted_index.broadband | 249 |
| abstract_inverted_index.component | 25 |
| abstract_inverted_index.concerns. | 48 |
| abstract_inverted_index.effective | 162 |
| abstract_inverted_index.impactful | 8 |
| abstract_inverted_index.important | 24 |
| abstract_inverted_index.improving | 10, 71 |
| abstract_inverted_index.including | 33 |
| abstract_inverted_index.malicious | 130 |
| abstract_inverted_index.mitigated | 69 |
| abstract_inverted_index.reduction | 210 |
| abstract_inverted_index.resilient | 247 |
| abstract_inverted_index.technique | 159 |
| abstract_inverted_index.today’s | 27 |
| abstract_inverted_index.findings | 168 |
| abstract_inverted_index.(DVB-DDOS) | 65 |
| abstract_inverted_index.allocation | 3 |
| abstract_inverted_index.assignment | 75 |
| abstract_inverted_index.comparison | 219 |
| abstract_inverted_index.deployment | 141 |
| abstract_inverted_index.literature | 37 |
| abstract_inverted_index.mechanism. | 187, 224 |
| abstract_inverted_index.mechanisms | 237 |
| abstract_inverted_index.monitoring | 151 |
| abstract_inverted_index.non-secure | 222 |
| abstract_inverted_index.reductions | 190 |
| abstract_inverted_index.simulation | 167 |
| abstract_inverted_index.volumetric | 59 |
| abstract_inverted_index.distributed | 61 |
| abstract_inverted_index.improvement | 174 |
| abstract_inverted_index.performance | 13, 195 |
| abstract_inverted_index.significant | 229 |
| abstract_inverted_index.highlighting | 40 |
| abstract_inverted_index.significant | 189 |
| abstract_inverted_index.respectively, | 215 |
| abstract_inverted_index.vulnerability | 42 |
| abstract_inverted_index.classification | 163 |
| abstract_inverted_index.distinguishing | 129 |
| abstract_inverted_index.security-aware | 121 |
| abstract_inverted_index.infrastructures. | 251 |
| cited_by_percentile_year | |
| countries_distinct_count | 3 |
| institutions_distinct_count | 4 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.6299999952316284 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile.value | 0.0099945 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |