Mathematical Approach as Qualitative Metrics of Distributed Denial of Service Attack Detection Mechanisms
The distributed denial of service (DDoS) attack is one of the most destructive organized cyber-attacks against online services or computers on the network. Despite the existence of many mechanisms to detect DDoS attacks, the problem is still prevalent. This research dissected and analyzed twenty-two...
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9530416/ |
| _version_ | 1798002000312401920 |
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| author | Ayman Ghaben Mohammed Anbar Iznan Husainy Hasbullah Shankar Karuppayah |
| author_facet | Ayman Ghaben Mohammed Anbar Iznan Husainy Hasbullah Shankar Karuppayah |
| author_sort | Ayman Ghaben |
| collection | DOAJ |
| description | The distributed denial of service (DDoS) attack is one of the most destructive organized cyber-attacks against online services or computers on the network. Despite the existence of many mechanisms to detect DDoS attacks, the problem is still prevalent. This research dissected and analyzed twenty-two existing DDoS attack detection mechanisms, representing all types of DDoS attack defense approaches, to determine the reason for the persistent successful DDoS attacks. This research posits two hypotheses concerning this gap: First, a lack of mathematical function usage by the existing detection mechanisms. The few functions used are limited to logical, statistical, or probability functions, resulting in reduced detection effectiveness. Second, researchers unintentionally or inadvertently miscalculate the mechanisms’ detection accuracy rate by partially using quantitative metrics. This research has three objectives; to propose a set of qualitative metrics based on mathematical functions, to measure the relationship between the quantitative and qualitative metrics in the DDoS attack detection mechanisms, and to prove the relationship between the genuineness of the existing mechanisms’ detection accuracy, and full consideration of quantitative metrics and diversity of qualitative and metrics. The result revealed a correlation rate of 84.22 %, which reflects the correctness of the detection accuracy. Third, identifying the manipulation percentage of reported detection accuracy by employing the correlation rate complement. The result indicated that 15.78 % of the reviewed mechanisms had manipulated or inadvertently miscalculated the accuracy. |
| first_indexed | 2024-04-11T11:45:12Z |
| format | Article |
| id | doaj.art-2c3e4e1571ad4cf8b1e3e1f61612d238 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-11T11:45:12Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-2c3e4e1571ad4cf8b1e3e1f61612d2382022-12-22T04:25:35ZengIEEEIEEE Access2169-35362021-01-01912301212302810.1109/ACCESS.2021.31105869530416Mathematical Approach as Qualitative Metrics of Distributed Denial of Service Attack Detection MechanismsAyman Ghaben0Mohammed Anbar1https://orcid.org/0000-0002-7026-6408Iznan Husainy Hasbullah2https://orcid.org/0000-0002-2275-3201Shankar Karuppayah3https://orcid.org/0000-0003-4801-6370National Advanced IPv6 Centre (NAv6), Universiti Sains Malaysia, Pulau Penang, MalaysiaNational Advanced IPv6 Centre (NAv6), Universiti Sains Malaysia, Pulau Penang, MalaysiaNational Advanced IPv6 Centre (NAv6), Universiti Sains Malaysia, Pulau Penang, MalaysiaNational Advanced IPv6 Centre (NAv6), Universiti Sains Malaysia, Pulau Penang, MalaysiaThe distributed denial of service (DDoS) attack is one of the most destructive organized cyber-attacks against online services or computers on the network. Despite the existence of many mechanisms to detect DDoS attacks, the problem is still prevalent. This research dissected and analyzed twenty-two existing DDoS attack detection mechanisms, representing all types of DDoS attack defense approaches, to determine the reason for the persistent successful DDoS attacks. This research posits two hypotheses concerning this gap: First, a lack of mathematical function usage by the existing detection mechanisms. The few functions used are limited to logical, statistical, or probability functions, resulting in reduced detection effectiveness. Second, researchers unintentionally or inadvertently miscalculate the mechanisms’ detection accuracy rate by partially using quantitative metrics. This research has three objectives; to propose a set of qualitative metrics based on mathematical functions, to measure the relationship between the quantitative and qualitative metrics in the DDoS attack detection mechanisms, and to prove the relationship between the genuineness of the existing mechanisms’ detection accuracy, and full consideration of quantitative metrics and diversity of qualitative and metrics. The result revealed a correlation rate of 84.22 %, which reflects the correctness of the detection accuracy. Third, identifying the manipulation percentage of reported detection accuracy by employing the correlation rate complement. The result indicated that 15.78 % of the reviewed mechanisms had manipulated or inadvertently miscalculated the accuracy.https://ieeexplore.ieee.org/document/9530416/DDoS attacksnetworking securityqualitative metricsquantitative metrics |
| spellingShingle | Ayman Ghaben Mohammed Anbar Iznan Husainy Hasbullah Shankar Karuppayah Mathematical Approach as Qualitative Metrics of Distributed Denial of Service Attack Detection Mechanisms IEEE Access DDoS attacks networking security qualitative metrics quantitative metrics |
| title | Mathematical Approach as Qualitative Metrics of Distributed Denial of Service Attack Detection Mechanisms |
| title_full | Mathematical Approach as Qualitative Metrics of Distributed Denial of Service Attack Detection Mechanisms |
| title_fullStr | Mathematical Approach as Qualitative Metrics of Distributed Denial of Service Attack Detection Mechanisms |
| title_full_unstemmed | Mathematical Approach as Qualitative Metrics of Distributed Denial of Service Attack Detection Mechanisms |
| title_short | Mathematical Approach as Qualitative Metrics of Distributed Denial of Service Attack Detection Mechanisms |
| title_sort | mathematical approach as qualitative metrics of distributed denial of service attack detection mechanisms |
| topic | DDoS attacks networking security qualitative metrics quantitative metrics |
| url | https://ieeexplore.ieee.org/document/9530416/ |
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