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Clean Slate (or not)

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Sebastian Lenzlinger
2024-06-12 13:31:49 +02:00
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notes/journal/2024-05-15-wed.md
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@@ -11,4 +11,5 @@ With the above idea it would be possible to also refactor or rewrite how tcpdump
I want an option such that one can automatically convert a captures resulting file into a csv. Probably will focus on tcpdump for now, since other tools like [[mitmproxy]] have different output files.
## Defining Experiment
I want a pair of commands that 1. provide a guided cli interface to define an experiment and 2. to run that experiment -> Here [Collective Knowledge Framework](https://github.com/mlcommons/ck) might actually come in handy. The already have tooling for setting up and defining aspects of experiments so that they become reproducible. So maybe one part of the `iottb` as a tool would be to write the correct json files into the directory which contain the informatin on how the command was run. Caveat: All all option values are the same, basically only, if it was used or not (flagging options) or that it was used (e.g. an ip address was used in the filter but the specific value of the ip is of no use for reproducing). Also, Collective Minds tooling relies very common ML algos/framework and static data. So maybe this only comes into play after a capture has been done. So maybe a feature extraction tool (see [[further considerations#Usage paths/ Workflows]]) should create the data and built the database separately.
I want a pair of commands that 1. provide a guided cli interface to define an experiment and 2. to run that experiment -> Here [Collective Knowledge Framework](https://github.com/mlcommons/ck) might actually come in handy. The already have tooling for setting up and defining aspects of experiments so that they become reproducible. So maybe one part of the `iottb` as a tool would be to write the correct json files into the directory which contain the informatin on how the command was run. Caveat: All all option values are the same, basically only, if it was used or not (flagging options) or that it was used (e.g. an ip address was used in the filter but the specific value of the ip is of no use for reproducing). Also, Collective Minds tooling relies very common ML algos/framework and static data. So maybe this only comes into play after a capture has been done. So maybe a feature extraction tool (see [[further considerations#Usage paths/ Workflows]]) should create the data and built the database separately.
#remark TCP dump filter could also be exported into an environment variable? But then again what is the use of defining a conformance, then could use the raw capture idea for tcpdump, too.