WikiPrint - from Polar Technologies

This page talks about language used to design experiments. It should both be used to design metadescriptions and perhaps to make them more specific to a particular experiment the user wants to run.


I'll start with a few examples of experiments first, that we should be able to design in this language.

  1. [BotnetExample]
  2. [CachePoisonExample]
  3. [MitmExample]

Expressiveness of the Meta-description

We may end up with a single language or a set of related languages. Here is what we need to express:

  1. Logical topology - both at the level of individual nodes or groups of nodes. We are expressing a logical topology of the experiment where there are objects that do something in the experiment - generate traffic, change state, hold data, whatever. Whether these objects are individually generated or generated as a group of entities, whether they are physical nodes or virtual, etc. does not matter. The expressiveness should be such that the actual implementation of objects and the cardinality of each object is orthogonal to the topology description. We should however be able to give hints such as "these objects are in the same network or on same physical node or object A resides on object B". Here is a rough list of hints we'd like to be able to give:
  1. Timeline of events - we need to express the ordering of actions that some objects will take in the experiment, their duration, repetition and concurrency. We also need to express state transitions in objects. In some domains this is called a workflow. It could be pre-created in the experiment design stage or it could be generated manually during the experiment (mined from events that happen as user takes manual actions) or a mix of those. Each experiment class must have some default workflow that user can manipulate during experiment design. Here is a rough list of things to express here:
  1. Invariants - we need to express what MUST happen in the experiment for it to be valid. This is not a complete set, just the necessary one. If any of the invariants were violated the experiment would become invalid. Valid here means "for it to belong to a class of experiments whose metadescription we used" plus any other conditions that user wants to impose. There are two types of invariants:
    1. those that deal with objects and their states ("cache must be poisoned")
    2. those that deal with events and their features ("traffic must flow from A to B for 5 minutes at 100Mbps")

In general case invariants are defined in the logical topology and timeline of events. Additional invariants may be defined in this section but so far I had hard time coming up with those for a meta-description. Naturally when the user designs her experiment starting from the metadescription this will lead to more invariants being defined automatically and to some that a user can choose to define.

Note that intentionally this is all pretty high-level and is orthogonal to any generator used to generate topologies, traffic, etc. There must be a mapping process that selects eligible generators for each dimension and takes their output and maps objects and events to it. More about this mapping process later.

Domain Knowledge

The entire system has a domain knowledge database that contains domain-specific information, such as:

The context part would be mostly populated by us. The parameterization and relationship parts would be seeded by us but then extended by other experts that create meta-descriptions. There is an automated way of identifying unknowns from a meta-description that must be defined in the knowledge DB.

Generator Descriptions

Our system keeps the following info about each generator:

Mapping elements of metadescription to generators during experiment design