SIP_X i = i / i Δ α An observation value for SPDY experimental simulation was the result of multiplication of the number of TCP streams sent by a user to a SPDY proxy server, by the average number of the resources requested per each TCP stream per time unit ( ) . i Assuming that: : is the total number of TCP streams sent by a user per time unit ( ) i i α : is the average of the number of the resources requested per each TCP stream per i β time unit ( ) i Then the input observation value for SPDY ( ) is computed by: SPDY_X i SPDY_X i = i . i α β The difference in the observation input is to show that the techniques that are used in the research are flexible in different cases. Because the scenario of SIP traffic flow is a communication, and an input value for the SIP experimental simulation is a ratio, which is a mathematical division operation as shown in equation (3.1), then (SIP_X ) i will result in tiny input values. While the scenario of SPDY traffic flow is a one-way communication, and an input value for the SPDY experimental simulation is a multiplication operation as shown in equation (3.2), then (SPDY_X ) will result in very i large input values. Cumulative Summation (CUSUM) Cumulative Summation (CUSUM) [19], [26], [41], and [56], is a sequential statistical analysis technique, which is used to monitor and to detect changes within any sequence of quantitative observations in some experiment, i.e. monitoring for any sudden increase or decrease in the number of incoming messages. CUSUM is a recursive equation, which means a new CUSUM value is dependent on the previous CUSUM values. After a new input value to the sequence of the observations is obtained, it will be used to find a new CUSUM value. CUSUM is computed according to the following equation:
SIP_X i = Δ i / α i An observation value for SPDY experimental simulation was the result of multiplication of the number of TCP streams sent by a user to a SPDY proxy server, by the average number of the resources requested per each TCP stream per time unit ( i ) . Assuming that: α i : is the total number of TCP streams sent by a user per time unit ( i ) β i : is the average of the number of the resources requested per each TCP stream per time unit ( i ) Then the input observation value for SPDY ( SPDY_X i ) is computed by: SPDY_X i = α i . β i The difference in the observation input is to show that the techniques that are used in the research are flexible in different cases. Because the scenario of SIP traffic flow is a communication, and an input value for the SIP experimental simulation is a ratio, which is a mathematical division operation as shown in equation (3.1), then (SIP_X i ) will result in tiny input values. While the scenario of SPDY traffic flow is a one-way communication, and an input value for the SPDY experimental simulation is a multiplication operation as shown in equation (3.2), then (SPDY_X i ) will result in very large input values. Cumulative Summation (CUSUM) Cumulative Summation (CUSUM) [19], [26], [41], and [56], is a sequential statistical analysis technique, which is used to monitor and to detect changes within any sequence of quantitative observations in some experiment, i.e. monitoring for any sudden increase or decrease in the number of incoming messages. CUSUM is a recursive equation, which means a new CUSUM value is dependent on the previous CUSUM values. After a new input value to the sequence of the observations is obtained, it will be used to find a new CUSUM value. CUSUM is computed according to the following equation:
Detection%20of%20Denial%20Of%20Service%20Attacks%20on%20Application%20Layer%20Protocol.docx