Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Different from most existing studies on b session identification for commerce purposes, a novel dynamic real time HTTP-session processes description method is presented in this paper for detecting the anomaly HTTP traffic for network boundary. The proposed scheme doesn't rely on presupposed threshold and client/server-side data which are widely used in traditional session detection approaches. A new parameter is defined based on inter-arrival time of HTTP requests. A nonlinear algorithm is introduced for quantization. Trained by the quantized sequences, nonparametric hidden Markov model with explicit state duration is applied to cluster and scout the HTTP-session processes. A probability function is derived for predicting HTTP-session processes. The deviation beten the prediction result and the real observation is used for sham b behavior detection. Experiments based on real HTTP traces of large-scale b proxies are implemented to valid the proposal.
['Yi Xie', 'Xiangnong Huang']
I am writing a research paper on a idea HTTP-session Model and Its Application in Anomaly HTTP Traffic Detection
[{"from": "human", "value": "I am writing a research paper on a idea HTTP-session Model and Its Application in Anomaly HTTP Traffic Detection"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Different from most existing studies on b session identification for commerce purposes, a novel dynamic real time HTTP-session processes description method is presented in this paper for detecting the anomaly HTTP traffic for network boundary. The proposed scheme doesn't rely on presupposed threshold and client/server-side data which are widely used in traditional session detection approaches. A new parameter is defined based on inter-arrival time of HTTP requests. A nonlinear algorithm is introduced for quantization. Trained by the quantized sequences, nonparametric hidden Markov model with explicit state duration is applied to cluster and scout the HTTP-session processes. A probability function is derived for predicting HTTP-session processes. The deviation beten the prediction result and the real observation is used for sham b behavior detection. Experiments based on real HTTP traces of large-scale b proxies are implemented to valid the proposal."}]