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The concept at work in federated identity is that if someone else trusts a login to be John Doe, my systems will trust that it is John Doe and treat him accordingly by allowing access based on this transfer of trust. With federation transfers of the end user, all of the service providers must trust the user s credentials completely. There is no opportunity to reauthenticate the user, provide a challenge question, or ask for a password to verify identity, because there s no direct knowledge of the customer. If your company uses federated identity, you have, by default, accepted the weaknesses in the systems run by every member of your federated group.

In the second line of the above equations, since FS I PfS Ig 1 by de nition, lims3I l s u0 , and lims3t w l s 0 from Eq. (13.5), we see that l s FS s I u0 . The proof is completed by changing the integral variable as t w follows. Denote l s by u; we have t w u u0 1 s and s u0 t w : u0 u j

... Preface -- 1 -- 2 -- 3 -- 4 -- 5 -- 6 -- 7 -- 8 -- 9 -- A -- B -- C -- Refs Front -- Contents -- Help

COMMENT 13.3.4. If PflossjR n r, w 0 wg 1, then it only means that traf c loss due to buffer over ow will occur for certain in 0; S , while not

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necessarily implying that all traf c arrived in 0; S is lost As we can see from Lemmas 1331 and 1333, when PflossjR n r, w 0 wg 1, we still have E ljR n r, w 0 w 1 C=r < 1, given r > C COMMENT 1335 For loss behavior of uid traf c in single states, the only nontrivial case is r > C and w < B Otherwise, the loss probability equals either 0 or 1, and the expected loss ratio is either 0 or a constant equal to u0 So it is suf cient to consider only r > C and w < B for the purpose of this study.

Federated identity revolves around the idea that every organization in the federation has sufficient reason from its enrollment process to place enough trust in the identity of the user that the other members should trust it as well. Furthermore, the other organizations processes are sufficient for my organization to place trust in the identity of users that they enrolled. This might be a more acceptable risk if there were similar security protections and audits conducted on every federation member s security defenses and identity verification processes. Such an agreement begins to add costs, though, canceling some of the savings that might be expected from the use of federation in the first place.

Copyright 1999 Gary McGraw and Edward Felten. All rights reserved. Published by John Wiley & Sons, Inc.

As shown above, both the conditional loss probability and the conditional expected loss ratio depend explicitly on the distribution of S, which is in turn determined by the assumption on the underlying traf c process R t For example, if we assume that R t is a Markov process, then S is exponentially distributed On the other hand, if we assume that R t is an LRD process, then the distribution of S is heavy-tailed To compare the two con icting modeling assumptions, we consider the following scenario Suppose that a Markov uid model, denoted by M t , is used for modeling a uid-type traf c process R t But, in fact, the underlying traf c process R t is an LRD process, denoted by L t , which has the same state space as that of the Markov process M t .

The essential difference between M t and L t lies in the way to characterize Dtn , the length of the time interval tn ; tn 1 for arbitrary n ! 1 We still use 0; S to represent tn ; tn 1 , so the interval length Dtn can be denoted simply by S As we have already mentioned, for Markov model M t , S is exponentially distributed, but for LRD model L t , the distribution of S is heavy tailed or asymptotically heavy tailed; that is, the functional form of the distribution possesses the property of heavy tail if the value of S is suf ciently large.

CHAPTER SECTIONS: 1 / 2 / 3 / 4 / 5 / 6 / 7 / 8 / 9 / 10 / 11 / 12 / 13 / 14 / 15 / 16 / 17 / 18 / 19 / 20

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