However, the false negatives for each application are lower than LASER except Fileguri due to some packet loss while capturing. Table I. Classification accuracy using TMA Classified False False Overall Application Traffic (kB) Negative (kB) Positive (kB) Accuracy (%) 202,018 3,361 0 98.36 BitTorrent LimeWire 87,678 2,951 0 96.74 95,804 9,691 0 90.81 Fileguri YouTube 16,061 0 3,775 80.96 TMA Log 421,339 kB Traffic HTTP packets vs. YouTube signal packets Table II. HTTP packet contents YouTube signal packet contents GET / HTTP/1.1 GET User-Agent: Mozilla/5.0 /videoplayback?sparams=id%2C (Windows; U; Windows NT 5.1; expire%2Cip%2Cipbits%.... en-US) ...... HTTP/1.1 ... User-Agent: Mozilla/5.0 ... (Windows; U; Windows NT 5.1; Connection: Keep-Alive en-US) ...... Connection: Keep-Alive Table III. Flow similarity approach (FSA) vs. LASER False Negative False Positive Application Approach (%) (%) FSA 1.66 0 BitTorrent LASER 10.40 0 FSA 3.36 0 LimeWire LASER 8.42 0 FSA 10.11 0 Fileguri LASER 0.39 0 LASER 97.39% Overall Accuracy FSA 96.01% Finally, we estimate the population proportion with 95% confidence. The confidence interval is (6). The estimated classification accuracy is 96.010.0011.
However, the false negatives for each application are lower than LASER except Fileguri due to some packet loss while capturing. Table I. Classification accuracy using TMA Application Classified Traffic (kB) False Negative (kB) False Positive (kB) Overall Accuracy (%) BitTorrent 202,018 3,361 0 98.36 LimeWire 87,678 2,951 0 96.74 Fileguri 95,804 9,691 0 90.81 YouTube 16,061 0 3,775 80.96 TMA Log Traffic 421,339 kB Table II. HTTP packets vs. YouTube signal packets HTTP packet contents YouTube signal packet contents GET / HTTP/1.1 User-Agent: Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US) ... ... Connection: Keep-Alive GET /videoplayback?sparams=id%2C expire%2Cip%2Cipbits%.... ...... HTTP/1.1 User-Agent: Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US) ...... Connection: Keep-Alive Table III. Flow similarity approach (FSA) vs. LASER Application Approach False Negative (%) False Positive (%) BitTorrent FSA 1.66 0 LASER 10.40 0 LimeWire FSA 3.36 0 LASER 8.42 0 Fileguri FSA 10.11 0 LASER 0.39 0 Overall Accuracy LASER 97.39% FSA 96.01% Finally, we estimate the population proportion with 95% confidence. The confidence interval is (6). The estimated classification accuracy is 96.010.0011.
POSTECH_IPOM_2009%5bFINAL%5d.docx