Please use this identifier to cite or link to this item: http://ir.futminna.edu.ng:8080/jspui/handle/123456789/28109
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dc.contributor.authorUgwu, B. D.-
dc.contributor.authorEvwiekpaefe, A. E.-
dc.contributor.authorIrhebhude, M. E.-
dc.contributor.authorAhmed, A.-
dc.date.accessioned2024-05-07T21:59:17Z-
dc.date.available2024-05-07T21:59:17Z-
dc.date.issued2024-05-
dc.identifier.citationUgwu Blessing Dominic, A. E. Evwiekpaefe, M. E. Irhebhude and Aliyu Ahmed, “Advanced Hybrid Anomaly Detection and Mitigation Framework for Slow HTTP DDoS Attacks,” Springer Nature Int. Symposium DoSCI-2024, 10 May 2024, New Delhi, India (in press, accepted 12/Jan/2024).en_US
dc.identifier.urihttp://repository.futminna.edu.ng:8080/jspui/handle/123456789/28109-
dc.description.abstractThis study investigates the Adaptive Hybrid Anomaly Detection and Mitigation (AHADM) framework’s effectiveness against slow HTTP DDoS attacks. Comparing it to established methods, the research highlights AHADM’s superior ability to swiftly detect and neutralize these elusive threats. By using adaptive algorithms and sophisticated anomaly detection mechanisms, AHADM outperforms existing solutions, offering robust defense against evolving cyber threats. The study also provides valuable insights into attack characteristics and practical implementation guidelines, contributing significantly to network security literature. AHADM emerges as a proactive defense strategy, mitigating risks posed by slow HTTP DDoS attacks in modern network environments.en_US
dc.language.isoenen_US
dc.subjectAHADM Framework, Apache Hadoop, DDoS Attacks and MLP.en_US
dc.titleAdvanced Hybrid Anomaly Detection and Mitigation Framework for Slow HTTP DDoS Attacksen_US
dc.typeArticleen_US
Appears in Collections:Computer Engineering

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