I'm willing to bet that the automated detection tools used by Blizzard are somewhat similar to the concept of IDS commonly used in network security to detect intrusions.
How would such a system work? A ton of metrics describing your activities as a player are aggregated over time. These metrics probably include your daily online time, daily node gathering count, daily pick pocket count, daily mob kills, auction posted, gold traded, gold from vendor, afk time, zone change count, messages sent, instances created, achievement points, honor points, etc. The next step for them is to identify the suspicious players. This is usually done using machine learning predictions based on a training data set of real player patterns and bot patterns.
This leads me to think that variety is probably the most important thing to avoid bans. Botting LFR, BG or dungeons on top of gather buddy for an additional couple of hours a week might reduce the chances of getting banned. E.G. 6 hours of gather buddy is probably more risky than 6 hours of gather buddy followed by an hour of LFR. This is based on the fact that a false positive ban is extremely damaging for them. The introduction of a very slight player-like behavior will therefor most likely reduce the risks.
This would also explain why people often lose only a certain percentage of their accounts. Machine learning classification can be very sensitive to only slight differences in the activity pattern, leading to the ban of only a portion of the accounts. Obviously, i'm not talking about IP bans, which are most likely the result of manual investigation following player reports.
Thoughts?
How would such a system work? A ton of metrics describing your activities as a player are aggregated over time. These metrics probably include your daily online time, daily node gathering count, daily pick pocket count, daily mob kills, auction posted, gold traded, gold from vendor, afk time, zone change count, messages sent, instances created, achievement points, honor points, etc. The next step for them is to identify the suspicious players. This is usually done using machine learning predictions based on a training data set of real player patterns and bot patterns.
This leads me to think that variety is probably the most important thing to avoid bans. Botting LFR, BG or dungeons on top of gather buddy for an additional couple of hours a week might reduce the chances of getting banned. E.G. 6 hours of gather buddy is probably more risky than 6 hours of gather buddy followed by an hour of LFR. This is based on the fact that a false positive ban is extremely damaging for them. The introduction of a very slight player-like behavior will therefor most likely reduce the risks.
This would also explain why people often lose only a certain percentage of their accounts. Machine learning classification can be very sensitive to only slight differences in the activity pattern, leading to the ban of only a portion of the accounts. Obviously, i'm not talking about IP bans, which are most likely the result of manual investigation following player reports.
Thoughts?