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because the analyzer must determine how memory modifications performed through one pointer would affect the data accessed using other pointers that point to the same memory location. In this case, the idea is to create several pointers that point to the array of indexes and have to write to several locations within at several stages. It would be borderline impossible for an automated deobfuscator to predict in advance the state of the array, and without knowing the exact contents of the array it would not be possible to properly analyze the code. In a brief performance comparison I conducted, I measured a huge runtime difference between the original function and the function from Listing 10.4: The obfuscated function from Listing 10.4 was about 3.8 times slower than the original unobfuscated function in Listing 10.2. Scattering 11 copies of the OBFUSCATE macro increased this number to about 12, which means that the heavily obfuscated version runs about 12 times slower than its unobfuscated counterpart! Whether this kind of extreme obfuscation is worth it depends on how concerned you are about your program being reversed, and how concerned you are with the runtime performance of the particular function being obfuscated. Remember that there s usually no reason to obfuscate the entire program, only the parts that are particularly sensitive or important. In this particular situation, I think I would stick to the array-based approach from Listing 10.4 the OBFUSCATE macros wouldn t be worth the huge performance penalty they incur.

6 5.6 4 3.5 2 0.6 0 4 5 6 Excavation depth [m] 7 8

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Inlining is a well-known compiler optimization technique where functions are duplicated to any place in the program that calls them. Instead of having all callers call into a single copy of the function, the compiler replaces every call into the function with an actual in-place copy of it. This improves runtime performance because the overhead of calling a function is completely eliminated, at the cost of significantly bloating the size of the program (because functions are duplicated). In the context of obfuscating transformations, inlining is a powerful tool because it eliminates the internal abstractions created by the software developer. Reversers have no information on which parts of a certain function are actually just inlined functions that might be called from numerous places throughout the program. One interesting enhancement suggested in [Collberg3] is to combine inlining with outlining in order to create a highly potent transformation. Outlining means that you take a certain code sequence that belongs in one function and create a new function that contains just that sequence. In other words it is the exact opposite of inlining. As an obfuscation tool, outlining becomes effective when you take a random piece of code and create a dedicated function for it. When done repetitively, such a process can really add to the confusion factor experienced by a human reverser.

10

Quite simply, how good your start is can have a major impact on how good your nish is! With the number of discards low in most series, we can rarely afford a bad start Starting can form a very large percentage of the race Obviously, in conditions when you are particularly fast, the importance of a start will diminish (just do not get OCSed), but being able to start well is de nitely a skill worth having, especially when competing in competitions with shorter courses, or where one side of the rst beat is heavily favoured The better you are at starting, the more dif cult the starts you can attempt in a regatta situation As with all practical skills, practice makes perfect! All boats behave differently, and this varies as the racing area changes (Some boats will quickly become overpowered, while others are usually underpowered.

Figure 19.1 Reliability index versus excavation depth for sheet pile study. (Reprinted with permission from Schweiger, H. F., Turner, R. and Pottler, R. (2001). Reliability Analysis in Geotechnics with Deterministic Finite Elements. International Journal of Geomechanics, Vol. 1, No. 4, pp. 389 413, CRC Press, Boca Raton, Florida.)

Code interleaving is a reasonably effective obfuscation technique that is highly potent, yet can be quite costly in terms of execution speed and code size. The basic concept is quite simple: You take two or more functions and interleave their implementations so that they become exceedingly difficult to read.

Function1() { Function1_Segment1; Function1_Segment2; Function1_Segment3; } Function2() { Function2_Segment1; Function2_Segment2; Function2_Segment3; } Function3() { Function3_Segment1; Function3_Segment2; Function3_Segment3; }

0.10 1E+00 1E 01 1E 02 1E 03 1E 04 1E 05 1E 06 1E 07 1E 08 1E 09 1E 10 1E 11 1E 12 1E 13 1E 14 1E 15 1E 16

Function1_Segment3; End of Function1 Function1_Segment1; (This is Opaque Predicate -> Always Function3_Segment2; Opaque Predicate -> Always Function3_Segment1; (This is Opaque Predicate -> Always Function2_Segment2; Opaque Predicate -> Always Function1_Segment2; Opaque Predicate -> Always Function2_Segment3; End of Function2 Function3_Segment3; End of Function3 Function2_Segment1; (This is Opaque Predicate -> Always

the Function1 entry-point) jumps to Function1_Segment2 jumps to Segment3 the Function3 entry-point) jumps to Function3_Segment2 jumps to Function2_Segment3 jumps to Function1_Segment3

Probability of failure pf [ ]

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