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Mobile code is a class of benign programs that are specifically meant to be mobile and be executed on a large number of systems without being explicitly installed by end users. Most of today s mobile programs are designed to create a more active Web-browsing experience. This includes all kinds of interactive Java applets and ActiveX controls that allow Web sites to embed highly responsive animated content, 3-D presentations, and so on. Depending on the specific platform, these programs essentially enable Web sites to quickly download and launch a program on the end user s system. In most cases (but not all), the user receives a confirmation message saying a program is about to be installed and launched locally. Still, as mentioned earlier, many users seem to automatically click the confirmation button, without even considering the possibility that potentially malicious code is about to be downloaded into their system. The term mobile code only determines how the code is distributed and not the technical details of how it is executed. Certain types of mobile code, such as Java scripts, are distributed in source code form, which makes them far easier to dissect. Others, such as ActiveX components, are conventional PE executables that contain native IA-32 machine code these are probably the most difficult to analyze. Finally, some mobile code components, such as Java applets, are presented in bytecode form, which makes them highly vulnerable to decompilation and reverse engineering.

The analysis consisted of Monte Carlo simulation of both M and FS. The basic simulations used 10, 100 and 1000 points. For each value of n (number of points), ten independent simulations were run. All the uncertain variables were assumed to be Normally distributed. Then, the simulations were repeated with the same rst n/2 points and a second group of n/2 points using the complements of these values. Mean values of M and FS were calculated for each sampling. The results are shown in Figure 17.10 for the factor of safety. The plot shows the maximum and minimum and the mean of the results for each group of simulations. Antithetic sampling clearly improves the convergence. Indeed, the results using ten points with antithetic simulation are better than those from the simulations using 1000 points. Similar results occur for the margin of safety. When the results of these simulations are used to compute the standard deviations of M or FS, the results are completely different, as Figures 17.11 shows. The results from antithetic simulation are worse than those from direct simulation. Study of Equations (17.49)

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This is a relatively new category of malicious programs that has become extremely popular. There are several different types of programs that are part

Mean Factor of Safety for Culmann Model 2.3 2.2 2.1 2 1.9 1.8 n = 10 n = 100 Number of Simulations Basic MC Antithetic n = 1000

of this category, but probably the most popular ones are the Adware-type programs. Adware is programs that force unsolicited advertising on end users. The idea is that the program gathers various statistics regarding the end user s browsing and shopping habits (sometimes transmitting that data to a centralized server) and uses that information to display targeted ads to the end user. Adware is distributed in many ways, but the primary distribution method is to bundle the adware with free software. The free software is essentially funded by the advertisements displayed by the adware program. There are several problems with these programs that effectively turn them into a major annoyance that can completely ruin the end-user experience on an infected system. First of all, in some programs the advertisements can appear out of nowhere, regardless of what the end user is doing. This can be highly distracting and annoying. Second, the way in which these programs interface with the operating system and with the Web browser is usually so aggressive and poorly implemented that many of these programs end up reducing the performance and robustness of the system. In Internet Explorer for example, it is not uncommon to see the browser on infected systems freeze for a long time just because a spyware DLL is poorly implemented and doesn t properly use multithreaded code. The interesting thing is that this is not intentional the adware/ spyware developers are simply careless, and they tend to produce buggy code.

Different solutions will suit different people, and as you get older you will learn the systems that work for you.

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