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Effective DDoS Security Scheme for Mobile Cloud Computing Systems

EasyChair Preprint no. 12822

7 pagesDate: March 28, 2024


With the increasing use of mobile Cloud Computing systems (MCC) in various domains, including offices, homes, hospitals, and transportation, Distributed Denial of Service (DDoS) attacks have become more frequent and complex, posing new challenges and risks. Therefore, enhancing the three defense mechanisms (prevention, detection, and mitigation) is crucial. In this paper, we propose a machine-learning model that utilizes neural network techniques, such as an Evolutionary recurrent self-organizing map (ERSOM), in combination with a K-means classifier to detect botnet attacks and ensure the establishment of all defense mechanisms in mobile cloud computing system. Our performance results demonstrate the effectiveness of the proposed adaptive ERSOM model compared with the literature.

Keyphrases: DDoS, detection, Mitigation, Mobile Cloud Computing, neural network, Prevention

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Chaima Ishak and Yosra Ben Saied},
  title = {Effective DDoS Security Scheme for Mobile Cloud Computing Systems},
  howpublished = {EasyChair Preprint no. 12822},

  year = {EasyChair, 2024}}
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