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In order to address the described severe resource scarcity, the ECG biometric has been found to speci cally exhibit desirable characteristics for BSN applications. Basically, the ECG signals are used for two purposes: rst, to construct good cryptographic keys; and then, to securely manage the key distribution to various sensor nodes in a BSN. To this end, the following properties are exploited. r Time-Variance and Key Randomness. The ECG biometric is highly timevariant. Fortunately, for a BSN setting, it is precisely the time-varying nature of ECG that makes it a prime candidate for good security. Good cryptographic keys need a high degree of randomness; and keys derived from random timevarying signals have higher security, since an intruder cannot reliably predict the true key. As previously reported in reference 29, ECG heart rate variability is in fact characterized by a (bounded) random process. r Timing Synchronization and Key Recoverability. Key randomness is only part of the security problem. The second requirement is that the ECG-generated key should be reproducible with high delity at various sensor nodes in the same BSN. To demonstrate the feasibility of accurate biometric reproducibility at various sensors, consider typical ECG signals from the PhysioBank [30], as shown in Figure 16.3. In this case, three different ECG signals are measured simultaneously from three different electrode or lead placements (I, AVL, VZ

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The last of the three problems identified in the section above regarding the use of this automatic server-side validation may be the worst of all, and for many, it s reason enough to not even recommend the use of server-side automatic validation. The problem is that the process requires the user to use the back button on your Web browser to return to the previous page and correct the listed problems. Is that a good thing to recommend Probably not.

PhysioBank [30]).

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In some instances, doing so causes the information that was entered on the form to be lost! Imagine the frustration of a user spending a good bit of time filling out a registration form that s asking for several pieces of data. S/he submits it, is told that it contains an error (maybe just one mistake), and the user hits the Back button only to find that the form is cleared! And you can do absolutely nothing about this problem. It s generally related to browser caching issues that aren t easily controlled. You may be thinking that this isn t that big a deal anyway, because failing the required validation means that the user didn t enter anything for the required field in the first place, but consider that you may be asking for several fields of data, of which only one fails the validation. The issue isn t that serious if the prompt is just for username and password. But in a more complex form, it could indeed become a major problem. Just be sensitive to the challenge. Fortunately, alternatives exist in the client-side validation that we discuss later. For now, you do have other kinds of validations that you can perform by using this automatic server-side validation. After you understand how the process works in general, you need to learn about the other directives, which we discuss in the following sections.

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and multi-stage dikes. It is worth noting that a previous committee had recommended using F = 1.4 for minor dikes and F = 1.7 for major (i.e. multistage) dikes.

Besides the _required validation, several more provide some of the simple validations that we list in the section Validating the format of input data, earlier in this chapter. Table 20-1 lists all the available validation directives.

[30, 31]). The focus is on the sequence of R R intervals, termed the interpulse interval (IPI) sequence [3]. What is noteworthy is that while the shapes of speci c QRS complexes are different for each signal, the sequences of IPI for the three signals, with proper timing synchronization, are remarkably identical. r Interpulse Interval (IPI) Sequence. Theoretically, the IPI sequences should be identical. This is because, physiologically, the IPI sequences capture the heart rate variations originating from the same heart, which should be the same regardless of the measurement site. This observation is completely analogous to the scenario with various sensor nodes located on different sites on the human body in a BSN: Each sensor point is capable of extracting the same sequence of IPI. And interestingly, other cardiovascular signals from the same individual or BSN including phonocardiogram (PCG), and photoplethysmogram (PPG) can also be used to derive the same sequence of IPI [3]. Thus, the use of cardiovascular IPI for security has potentially a wide domain of applicability. 16.3.3.5 Single-Point Fuzzy Commitment Schemes

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