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Under JDK 1.1 the same system applies as was the case in JDK 1.0. However, a class loaded from the network can become trusted if it is digitally signed by a party whom the user has decided to trust. The idea is to allow code signed by a trusted party to attain the same level of privilege as is usually afforded to builtin code. This is a decision not to be taken lightly. Security ramifications are just as critical as those raised when adding classes to the CLASSPATH. Note that the way JDK 1.1 is used in practice, the resulting trust model is still black and white. Code is still either completely trusted, or it's not trusted at all.

These effects can be seen graphically in Fig. 3.5. This gure shows histograms of An for varying values n. In plot (a) we show the case in which the Xi were drawn from an exponential distribution; in plot (b) we show the case in which the Xi were drawn from a strictly positive heavy-tailed distribution with a 1:4. In both cases the mean of the underlying distribution was 1. Plot (a) shows that the most likely value of the sample mean is equal to the true mean, even when summing only a small number of samples. In addition, it shows that as one sums larger numbers of samples, the sample mean converges quickly to the true mean. However, neither of these observations are true for the case of the heavy-tailed distribution in plot (b). When summing small numbers of samples, the most likely value of the sample mean is far from the true mean, and the distribution progresses to its nal shape rather slowly. Thus we have seen that the convergence properties of sums of heavy-tailed random variables are quite different from those of nite variance random variables. We relate this to steady state in simulation as follows: presumably for a simulation to reach steady state, it must at a minimum have seen enough of the input workload to observe its mean. Of course, it may be necessary for much more of the input to be consumed before the simulation reaches steady state, so this condition is a relatively weak one. Still, we show in the next two subsections that this condition has surprising implications for simulations. 3.3.1 Slow Convergence to Steady State

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Equation (3.6) states that for large n, Zn converges in distribution. Thus another way of formulating Eq. (3.5) is jAn mj $ n1=a 1 : In this form it is more clear how slowly An converges to m. If a is close to 1, then the rate of convergence, measured as the difference between An and m, is very slow

With Java 2, things get even more complicated. Built-in classes are still completely trusted, but external, digitally signed classes can become partially trusted at the whim of the user. By adding partial trust and access control to the VM, Java 2 opens the door for complex, fine-grained security policies that grant

Protecting the confidentiality of your own private information and shielding the privacy of the data an organization s management wants to keep secret share common concepts that are parallel core considerations for protecting data of any kind. This chapter introduces them as elements to be considered before progressing with the design of the controls architecture. In the design flowchart, each protection element is considered first as a required need or not in relation to the particular data. Then if controls are needed, to what level or strength of controls over each element is to become a functional requirement within the design. Privacy laws in the European Union and Canada are in some ways considered to be stronger than those in the United States. In the United States, states vary considerably in what has been passed into law; California is considered to be a leader in legislation aimed at protecting personal privacy. Mushrooming identity theft has caused a huge increase in new legislation at both state and federal levels. From a legal point of view, the legislation of privacy and data protection is a fast-moving target in terms of what must, or could, be done within the current technology environment. Public demand for accuracy of financial information and legislators responding to consumers requests for legal protection for personally identifying or financial information will continue to challenge technology designs. Plan your systems to accommodate the need to apply changes to the controls as regulation evolves.

until, for a 1, the average does not converge at all, re ecting the fact that the mean is in nite. Suppose one would like to use An to form a estimate of the mean m that is accurate to k digits. Alternatively, one might state that a simulation has reached steady state when the observed mean of the input An agrees with m to k digits. Then we would like jAn mj=m 10 k :

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