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amounts of data on removable media such as CD to be examined by humans at a later date if attacks should be uncovered. The analysis of data is not a task for humans, however. The level of detail is more than any human can digest, and the rate of its production and the attention-span and continuity required are inhuman. Rather, we should be looking at ways in which machine analysis and pattern detection could be employed to perform this analysis and not merely after the fact. In the future, adaptive neural nets and semantic detection will be used to analyse these logs in real time, avoiding the need to even store the data. Unfortunately, there is currently no way of capturing the details of every action performed by the local host, analogous to promiscuous network monitoring without drowning the host in excessive auditing. The best one can do currently is to watch system logs for conspicuous error messages. Programs like SWATCH [113] perform this task. Another approach which we have been experimenting with at Oslo college is the analysis of system logs at a statistical level. Rather than looking for individual occurrences of log message, one looks for patterns of logging behaviour. The idea is that logging behaviour reflects (albeit imperfectly) the state of the host [74]. Visualization is now being recognized as an important tool in understanding the behaviour of network systems [57, 135, 100]. This reinforces the importance of investing in a documentable understanding of host behaviour, rather than merely relating experiences and beliefs [36]. Network traffic analysis has been considered in refs. [11, 278, 189]. 7.4.3 Formalizing System Policy: cfengine
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Experience indicates that simple rules are always preferable, though this is so far unsubstantiated by any specific studies. A rule which says "If the user concerned has consumed more than X megabytes of diskspace and it is not Friday (when there is little activity) and his/ her boss has not said anythings in advance, and..." may seem smart, but most users will immediately write it off as being stupid. It is ill-advised because it is opaque. Principle 33 (Simplest is best) Simple rules make system behaviour easy to understand. Users tolerate rules if they understand them. 7.4.4 Using cfengine as a Front-end to cron
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One of cfengine's strengths is its use of classes to identify systems from a single file or set of files. Distributed resource administration would be much easier if the cron daemon also worked in this way. One way of setting this up is to use cfengine's time classes to work like a user interface for cron. This allows us to have a single, central file which contains all the c r o n jobs for the whole network without losing any of the fine control which cron affords us. All of the usual advantages apply: It is easier to keep track of what cron jobs are running on the system when they are all registered in one place. Groups and user-defined classes can be used to identify which host should run which programs.
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The central idea behind this scheme is to set up a regular cron job on every system which executes cfengine at frequent intervals. Each time cfengine is started, it evaluates time classes
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and executes the shell commands defined in its configuration file. In this way, we use cfengine as a wrapper for the cron scripts, so that we can use cfengine's classes to control jobs for multiple hosts. Cfengine's time classes are at least as powerful as cron's time specification possibilities, so this does not restrict us in any way. The only price is the overhead of parsing the cfengine configuration file. To be more concrete, imagine installing the following c r o n t a b file onto every host on the network:
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