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The authors also propose to refresh the keys proactively in order to tolerate mobile adversaries, because the adversary will have to capture multiple shares during the same interval Thus, if the old keys under the control of the adversary are refreshed, then they will be of no use with the new keys that the adversary might compromise Additionally, the system can also be designed to adapt its con guration to the changes in the network For example, a key management service might start with a (7, 3) con guration but then modify this later to a (4, 2) combination since some servers were detected to be compromised while other servers were unavailable 3312 Fully Distributed Authority The studies [25] and [26] describe an approach for distributing the functions of a certi cation authority The difference compared to schemes in Section 3311, however, is that in this case any node instead of a chosen few can contain a share of the private key of the service A new node that does not have a certi cate will have to contact at least t 1 servers These servers can issue a certi cate to such a node after establishing the identity of the node Any t 1 nodes can also renew a certi cate In addition, a node that does not possess a share can obtain one by contacting any group of at least t 1 nodes that already possess the share The bootstrapping of the system, however, needs a trusted authority that provides the initial shares to the rst t 1 nodes 3313 Self-Issued Certi cates We next describe an approach where the security of the system does not rely on any trusted authority This is the self-organized approach that allows users to create, store, distribute, and revoke their own public keys without the help of any trusted authority Such a self-organized public key management approach for ad hoc networks has been considered in [27, 28] Each user decides their own public private key pair Other users issue certi cates to each other based on other factors such as personal acquaintances Each user then maintains in their personal repository the list of valid certi cates When a user A needs to authenticate a certi cate belonging to user B, then user A checks if a certi cate has been issued by itself to B earlier If not, user A checks if the repository contains a certi cate to any other user C who in turn has B s certi cate Thus, a chain of valid public key certi cates is obtained by user A such that the rst certi cate of the chain is one issued by A Further, each remaining certi cate in the chain can be veri ed using the public key contained in the previous certi cate of the chain The last certi cate of the chain should then contain the public key of user B Thus, certi cate chaining is used in order to authenticate public keys of users If A cannot form a certi cate chain to B, then A cannot authenticate B s public key In addition to this, another problem is related to bootstrapping the certi cate repository of a node without depending on a separate authentication channel 3314 Other Schemes Other approaches for solving the key management problem in ad hoc network have also been proposed In [29] and [30] it is proposed to derive the IP address of the node from the public key of the node This is done by hashing the public key and then using part of the hash value as the part of the IP address of the node As a result, it is easy to verify if a public key corresponds to a node with a given IP address, thereby addressing the key authentication problem associated with public keys A problem, however, arises when the private key corresponding to a public key is compromised, thereby making the public key unusable As a result a new public private key pair will.

There are two other parameters that also help to better simulate the workload from real users grindersleepMillis and grinderinitialSleepTimes

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The LMS algorithm (6-18) simplifies computations by using derivatives of g itself instead of derivatives of its sample average In effect, the LMS algorithm approximates each derivative of the sample average by accumulating many small steps The choice of the optimization gain lrate is a trial-and-error compromise between computing speed and stable convergence Successive values of lrate must decrease to avoid overshooting the optimal connection weights More specifically, if the sum of all successive squares lrate2 has a finite limit, then the LMS algorithm converges with probability 1 to at least a local minimum of the expected value E{g} (the theoretical risk, as in Section 6-7), assuming that such a minimum exists [8,9] The algorithm should then approximately minimize measured sample averages of g (the empirical risk) In any case, results must be checked with multiple samples DESIRE s computer-readable vector/matrix language represents the N nx matrix (6-20) neatly as the outer product (W * x S) * x of the N-dimensional vector W * x S and the nx-dimensional vector x (Section 3-10) We start the connection weights W[i, k] with random values and implement the LMS algorithm (6-18) with the matrix difference equation

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