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Master images Versions Projects 11 Albums 11 Folders 11 Stacks 11 A Brief Tour of Aperture s Interface Understanding the Inspector, Browser, and Viewer Inspector 14 Browser 16 Viewer 19 Managing files with Projects and Albums Using special built-in views All Projects Faces and Places Aperture Trash Basic Customization Options 7 Setting library location and other General preferences Changing appearance preferences Changing default import behavior Modifying preview preferences 8 9 Running in 32-bit or 64-bit mode

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Most of this chapter is devoted to introducing terminology and discussing a select few classic pen and paper ciphers. Our goal here is not to cover classical cryptography in detail, since there are already many excellent sources of information on such ciphers. For example, Kahn s history [74] has a general discussion of virtually every cipher developed prior to its original publication date of 1967, Barr [7] presents a readable introduction to cryptography, Spillman [139] nicely covers the cryptanalysis of several classic cipher systems and Bauer [8]provides rigorous coverage of a large number of classical crypto topics. The ciphers we discuss in this chapter have been selected t o illustrate a few important points that arise in upcoming chapters. Even if you are familiar with classical cryptosystems, you should read the next two sections where terminology is discussed, since the terminology in cryptography is not always consistent. In addition, the material in Sections 1.4.3 and 1.4.4 is directly referenced in upcoming chapters.

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In cryptography, it is traditional that Alice and Bob are the good guys who are trying to communicate securely over an insecure channel. We employ Trudy (the intruder ) as our generic bad guy. Some books have a whole cast of bad guys with the name indicating the particular evil activity (Eve, the eavesdropper, for example), but we use Trudy as our all-purpose bad guy . 1

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"Keep it simple: as simple as possible, but no simpler." - A. Einstein A major thrust in algorithmic development is the design of algorithmic models to solve increasingly complex problems. Enormous successes have been achieved through the modeling of biological and natural intelligence, resulting in so-called "intelligent systems". These intelligent algorithms include artificial neural networks, evolutionary computing, swarm intelligence, and fuzzy systems. Together with logic, deductive reasoning, expert systems, case-based reasoning and symbolic machine learning systems, these intelligent algorithms form part of the field of Artificial Intelligence (AI). Just looking at this wide variety of AI techniques, AI can be seen as a combination of several research disciplines, for example, computer science, physiology, philosophy, sociology and biology. But what is intelligence Attempts to find definitions of intelligence still provoke heavy debate. Dictionaries define intelligence as the ability to comprehend, to understand and profit from experience, to interpret intelligence, having the capacity for thought and reason (especially to a high degree). Other keywords that describe aspects of intelligence include creativity, skill, consciousness, emotion and intuition. Can computers be intelligent This is a question that to this day causes more debate than do definitions of intelligence. In the mid-1900s, Alan Turing gave much thought to this question. He believed that machines could be created that would mimic the processes of the human brain. Turing strongly believed that there was nothing the brain could do that a well-designed computer could not. Fifty years later

Since this is a cryptanalysis book, we often play the role of Trudy. Trudy is an inherently more interesting character than boring old Alice and Bob, and this is part of what makes cryptanalysis so much more fun than cryptography. Trudy does not have to play by any preconceived set of rules. However, it is important to remember that attacks on real systems are almost certainly illegal, so do not attempt to play Trudy in the real world.

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