ACO-Based Measure for SYN Flooding Over Mobile Data Connectivity
Dynamics in IP-based SYN-flooding, whereby attacker can create slave daemon generators and distribute attacks, have frightened integration of mobile services over mobile data connectivity. This study proposes unsupervised learning model inspired by three ingredients of ants foraging behaviour to improve accuracy in detection of SYN dynamics and reduces the number of falsified alarms. The evaluation establishes simulation environment and analyse collected data using Mean Value Analysis (MVA) method, whereby results prove the model to dynamically classify, detect and wedge-out SYN-flooding at 58.4% utilization of GGSN gateway.
KeywordsSynchronize sequence numbers SYN Network flood Mobile services Internet Protocol Ants Colony Optimization
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