[assume that somehow we have this data [for example two parallel spywares]]
[we then need to act on it in a way that is humanly normal: [- what is similar between removal events?] - what is the cause or are the causes of the remove / what things were involved or necessary for it to happen? - what can be done to prevent the removal, by acting on those causes?] [ - what things are necessary for the event - how can one or more of these things be changed ] [ a basic part of interest is “what things are necessary for the event” this is a problem that can possibly be recursively simplified, but roughly involves something akin to AI. something is necessary if it always precedes a result, in any occurrence. in logical systems se call these logical rules. in statistical observation, we call it 100% correlation uhh dependent variables or such things. so if A causes B, we can then step back and consider if C causes A. we likely need a tree of these things. A possibility or dependency tree. We need to consider what parts things break down into. Or, contrariwise, you can just train some existing AI structure on history. ]
