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Filter expressions

FFPF is language neutral, which means that different languages may be mixed. As mentioned earlier, we currently support five languages: BPF, FPL-1, FPL-2, C, and OKE-Cyclone. Support for C is limited to root users. The nature of the other languages will be discussed in more detail in Section 3. Presently, we only sketch how multiple languages are supported by the framework.

Figure (2.a) shows an example with two simplified flow definitions, for flows $A$ and $B$, respectively. The grabber for flow $A$ scans web traffic for the occurrence of a worm signature and saves the IP source and destination addresses of all infected packets. In case the signature was not encountered before, the packet is also handed to the application. Flow grabber $B$ counts the number of fragments in web traffic. The first fragment of each fragmented packet is passed to the application.

There are a few things that we should notice. First, one of these applications is fairly complex, performing a full payload scan, while the other shows how state is kept regardless of whether a packet itself is sent to userspace. It is difficult to receive these flows efficiently using existing packet filtering frameworks, because they either don't allow complex processing in the kernel, or do not keep persistent state, or both. Second, both flows may end up grabbing the same packets. Third, the processing in both flows is partly overlapping: they both work on HTTP packets, which means that they first check whether the packets are TCP/IP with destination port 80 (first block in Figure 2). Fourth, as fragmentation is rare and few packets contain the CodeRed worm, in the common case there is no need for the monitoring application to get involved at all.

Figure 2: (a) combining different languages in two flows (A and B), (b) calling external functions from a single flow
\includegraphics[width=0.9\linewidth]{figs/concat_filters.eps}

Figure (2.a) shows how these two flows can be accommodated. A common BPF filter selecting HTTP/TCP/IP packets is shared by both flows. They are connected to the flow-specific parts of the data paths. As shown in the figure, the data paths are made up of small components written in different languages. The constituent filters are connected in a fashion similar to UNIX pipes. Moreover, a pipe may be `split' (i.e., sent to multiple other pipes, as shown in the figure) and multiple pipes may even be `joined'. Again, in UNIX fashion, the framework allows applications to create complex filter structures using simple components. A difference with UNIX pipes, however, is the method of connection: FFPF automatically recognises overlapping requests and merges the respective filters, thereby also taking care of all component interconnects.

Each filter has its own \ensuremath{IBuf}, and \ensuremath{MBuf}, and, once connected to a packet source, may be used as a `flow grabber' in its own right (just like a stage in a UNIX pipe is itself an application). Filters may read the \ensuremath{MBuf} of other filters in their flow group (although we have not yet implemented synchronisation primitives to prevent races). In case the same \ensuremath{MBuf} needs to be written by multiple filters, the solution is to use function-like filter calls supported by FPL-1 and FPL-2, rather than pipe-like filter concatenation discussed so far. For filter call semantics, a filter is called explicitly as an external function by a statement in an FPL expression, rather than implicitly in a concatenated pipe. An explicit call will execute the target filter expression with the calling filter's \ensuremath{IBuf} and \ensuremath{MBuf}. An example is shown in Figure (2.b), where a first filter call creates a hash table with counters for each TCP flow, while a second filter call scans the hash table for the top-10 most active flows. Both access the same memory area.


next up previous
Next: Construction of filter graphs Up: FFPF high-level overview Previous: Receiving packets in a
Herbert Bos 2004-10-06