Hello Everyone!

I am working on the capstone thesis project for my Master's degree and hoping for some professional assistance to determine if I am heading in the right path. To summarize my project, I am testing to see which resource (CPU, Memory, or Bandwidth) displays the greatest improvement in end-user performance against different DDoS attacks. My data is kind of like this...

data1,2,3 = baseline_cpu, baseline_memory, baseline_bandwidth + attack1x5; then attack2x5; then attack 3x5

data4,5,6 = increased_cpu, baseline_memory, baseline_bandwidth + attack1x5; then attack2x5; then attack3x5

data 7,8,9 = baseline_cpu, increased_memory, baseline_bandwidth +attack1x5; then attack2x5; then attack3x5

data 10,11,12 = baseline_cpu, baseline_memory, increased_bandwidth +attack1x5; then attack2x5; then attack3x5

I don't know if it matters for choosing a statistical method, but each attack was conducted for a 5 minute duration. So, all together, the important information is what attack is occurring and what resource is increased at what time so that I can see which, if any, increased resource did display improved performance from the end-user perspective.

For the statistics I was thinking of using ANOVA, but just realized that repeated measures of ANOVA may be the better options. I have taken two statistics course so far, so I don't have a lot of experience with this, but hopefully enough to get me through this. I am really interested to see what statistical method would be the best choice!

Also, are there any reputable free tools that I can find online to help with the mathematics of this?

Thanks a lot for your assistance.

-Cyanide

Edit: Since posting this I have spent some time reading through my Statistics book from a few semesters back. From this I think that the appropriate method would be to use Factorial ANOVA for this. I am thinking this because I have two groups (Resource + Attack) with multiple factors (Level of Resource + Method of Attack). Let me know if anyone has advice concerning any other Statistical methods that may be useful.

I am working on the capstone thesis project for my Master's degree and hoping for some professional assistance to determine if I am heading in the right path. To summarize my project, I am testing to see which resource (CPU, Memory, or Bandwidth) displays the greatest improvement in end-user performance against different DDoS attacks. My data is kind of like this...

data1,2,3 = baseline_cpu, baseline_memory, baseline_bandwidth + attack1x5; then attack2x5; then attack 3x5

data4,5,6 = increased_cpu, baseline_memory, baseline_bandwidth + attack1x5; then attack2x5; then attack3x5

data 7,8,9 = baseline_cpu, increased_memory, baseline_bandwidth +attack1x5; then attack2x5; then attack3x5

data 10,11,12 = baseline_cpu, baseline_memory, increased_bandwidth +attack1x5; then attack2x5; then attack3x5

I don't know if it matters for choosing a statistical method, but each attack was conducted for a 5 minute duration. So, all together, the important information is what attack is occurring and what resource is increased at what time so that I can see which, if any, increased resource did display improved performance from the end-user perspective.

For the statistics I was thinking of using ANOVA, but just realized that repeated measures of ANOVA may be the better options. I have taken two statistics course so far, so I don't have a lot of experience with this, but hopefully enough to get me through this. I am really interested to see what statistical method would be the best choice!

Also, are there any reputable free tools that I can find online to help with the mathematics of this?

Thanks a lot for your assistance.

-Cyanide

Edit: Since posting this I have spent some time reading through my Statistics book from a few semesters back. From this I think that the appropriate method would be to use Factorial ANOVA for this. I am thinking this because I have two groups (Resource + Attack) with multiple factors (Level of Resource + Method of Attack). Let me know if anyone has advice concerning any other Statistical methods that may be useful.

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