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Principals are entities that can be authorized to perform certain functions They may be users, objects, programs, etc Policies and credentials are speci ed using a concept called assertion Assertions are the basic programming units that de ne the conditions under which a principal authorizes actions requested by other principals Policies are authorized by a principal called Policy who is the root of the trust hierarchy Actions are a collection of attribute-value pairs Applications make queries to the KeyNote system requesting whether a particular set of actions is authorized or not The KeyNote system determines compliance based on the security policies and returns a policy compliance value (eg authorized, unauthorized)

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This fortunate fact an empirical law of large numbers is not derived from probability theory but is based on observations, just like a law of nature in physics Similar mathematical laws of large numbers (eg, the central limit theorem) relate to expected values and probabilities, that is, to properties of models Validation of mathematical laws by empirical laws of large numbers indicates that specific probability models can match and predict real-world experience

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For stateful session beans, a good example is the ubiquitous web shopping cart The state of the order is kept in the bean on behalf of the client; it can be changed and items added, and will be kept while the client maintains the connection with the bean Multiple method calls affect the state of the bean, and this state is only made permanent when the order button is finally pressed Keeping the bean's resources for just one client is more resource intensive than using stateless beans, as we'll see later in this book Entity beans are the persistent side of the EJB specification They represent data that lives in some data store (we use this generic name as it can be more than just an RDBMS), in an object-oriented fashion Entity beans are sharable, that is they can be accessed by many clients, and recoverable, meaning that their state is regularly synchronized with the data store The code to save and retrieve data from a data store can be developed by the programmer (bean-managed persistence, BMP) or (the easier way) by having the EJB automagically include code (container-managed persistence, CMP) For the most part, coding BMP is relatively mechanical and boring, and is much more prone to errors than CMP As we'll see in 5, though, there are times when we need BMP Either way, it is rather easy to access information in a data store with entity beans By combining session beans and entity beans you are able to create all the necessary components that make up the logic of an application It is in the interaction between clients and the EJBs that you create the workflow that makes up the core of your web application The EJB container/allows you design the application for an individual client, as the container enables it to work for multiple clients.

Probability models describe random processes in terms of joint probability distributions of different sample values x(t1), x(t2), [4,5] Such models try to fit observed statistics with theoretical concepts such as probabilities and expected values A random process is stationary if its joint probability distributions are unaffected when we shift the time origin by adding the same time shift to all sampling times ti We are going to simulate random processes generated by dynamic systems with random parameters (this includes random initial conditions) and/or random time-function inputs (noise) A Monte Carlo simulation study repeats or replicates simulations of such systems to produce a sample of different randomprocess sample functions x(t) We then compute statistics such as sample averages over corresponding values read from different sample functions Monte Carlo statistics typically measure various aspects of system performance 4-5 Generating Random Parameters and Random Initial Values Experiment-protocol scripts generate random parameter values a, b, with assignments such as

An example policy based on discussion in [Bl99] is shown below:

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