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tral sensitivity of the eye, which is about 70 percent green, 20 percent red, and 10 percent blue (Figure 32) The remaining color information is called chrominance (denoted as C), which is made up of hue (the proportion of color: the redness, orangeness, greenness, etc), and saturation (the purity of the color, from pastel to vivid) For the purposes of compression and converting from RGB, however, it is easier to use color difference information rather than hue and saturation In other words, the color information is what is left after the luminance is removed By subtracting the luminance value from each RGB value, three color difference signals are created R-Y, G-Y, and B-Y Only three stimulus values are needed, so only two color difference signals need be included with the luminance signal Since green is the largest component of luminance, it has the smallest difference signal (G makes up the largest part of Y, so G-Y results in the smallest values) The smaller the signal, the more it is subject to errors from noise, so B-Y and R-Y are the best choice The green color information can be recreated by subtracting the two difference signals from the Y signal (roughly speaking) Different weightings are used to derive Y and color differences from RGB, such as YUV, YIQ, and YCbCr

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Figure 10-4

The Batch input tool is available from the Logistics screen, Services menu: System, Services, Batch input, Edit

DVD uses YCbCr as its native storage format Details of the variations are beyond the scope of this book As mentioned earlier, the sensitivity of the eye is not linear, and neither is the response of the phosphors used in television tubes Therefore, video is usually represented with corresponding nonlinear values, and the terms luma and chroma are used These are denoted with the prime symbol as Y and C , as is the corresponding R G B Details of nonlinear functions are also beyond the scope of this book

A command shell shoveled via netcat from the victim system showing the output of ipconfig run on the remote machine

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The code here is [SM35] This section is divided into two parts: Recording a batch input Running the batch input In this documentation, we define and run a batch input to change the customer pricing procedure indicator on the customer master sales screen

An understanding of the nuances of human perception led to the development of compression techniques that take advantage of certain characteristics Just such a development is JPEG compression, which was produced by the Joint Photographic Experts Group and is now a worldwide standard JPEG separately compresses Y, B-Y, and R-Y information, with more compression done on the latter two, to which the eye is less sensitive To take advantage of another human vision characteristic less sensitivity to complex detail JPEG divides the image into small blocks and applies a discrete cosine transform (DCT), a mathematical function that changes spatial intensity values to spatial frequency values This describes the block in terms of how much the detail changes and roughly arranges the values from lowest frequency (represented by large numbers) to highest frequency (represented by small numbers) For areas of smooth colors or low detail (low spatial frequency), the numbers will be large For areas with varying colors and detail (high spatial frequency), most of the values will be close to zero A DCT is an essentially lossless transform, meaning that an inverse DCT function can be performed on the resulting set of values to restore the original values In practice, integer math and approximations are used, causing some loss at the DCT stage Ironically, the numbers are bigger after the DCT transform The solution is to quantize the DCT values so that they become smaller and repetitive Quantizing is a way of reducing information by grouping it into chunks For example, if you had a set of numbers between 1 and 100, you could quantize them by 10 That is, you could divide them by 10 and round to the nearest integer The numbers from 5 to 14 would all become 1s, the numbers from 15 to 24 would become 2s, and so on, with 1 representing 10, 2 representing 20, and so forth Instead of individual numbers such as 8, 11, 12, 20, and 23, you end up with 3 numbers near 10 and 2 numbers near 20 Obviously, quantizing results in a loss of detail.

The insidious thing about the netcat shoveled shell just illustrated is the attacker can determine what outbound port to connect with Typically, router or firewall rules allow outbound connections from internal host on nonprivileged ports (> 1024), so this attack has a high chance of success using one of those ports even if TCP 80 is the only inbound traffic allowed to the victim Web server because all preliminary steps in the attack operate over TCP 80 One remaining hurdle remains for the attacker to bypass Even though an interactive command shell has been obtained, it s running in the context of a low-privileged user (either the IUSR_machinename or IWAM_machinename account, depending on the configuration of the server) Certainly at this point, the attacker could do a great deal of damage, even with IUSR privileges The attacker could read sensitive data from the system, connect to other machines on internal networks (if permissible as IUSR), potentially create denial of service situations, and/or deface local Web pages However, the coup de gr ce for this system would be to escalate to one of the most highly privileged accounts on the machine, Administrator or SYSTEM We talk about how to do that next

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