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improvement in the security of the scheme Note that this scheme is similar to the q-composite key in that both schemes increase the dif culty of compromising a given link by requiring that the adversary possess multiple keys in order to eavesdrop on a given link The tradeoff, though, is different in both cases For the q-composite key scheme the tradeoff is in terms of the requirement for a smaller key pool to achieve certain connectivity in the network For the multipath scheme, the tradeoff is in terms of the larger communication overhead Combining both the schemes (q-composite and multipath reinforcement), however, might not be very effective since the combination compounds the weaknesses in both the schemes The smaller key pool size required for q-composite key scheme implies that more links are rendered insecure by compromising nodes greater than a threshold number This could undermine the effectiveness of the multipath reinforcement scheme This is due to the fact that, by compromising nodes beyond a threshold number, the adversary would have control over nearly all links in the network If the adversary has captured the traf c on these links sent earlier, he/she can decrypt the traf c and obtain the shares used to set up the keys This compromises the keys A problem with the two schemes given above is that they do not have mechanisms to allow one node to authenticate the identity of the other node The third scheme, called the random pairwise scheme, addresses this This scheme is a modi cation of the basic pairwise scheme Here each node is provided with its own ID and initialized with a certain number of keys in its key ring Each key on a node is shared with only one other node in the system With each key contained in the key ring of a node is also associated the ID of the other node which shares the same key After deployment a node broadcasts its node ID This information is used by the node s neighbors to search in their key rings to verify if they share a common pairwise key with the broadcasting node A cryptographic handshake can then be performed with nodes that have been identi ed to share common keys so that the nodes can mutually verify knowledge of the key As a result the nodes are aware of the authentic identity of the corresponding party This scheme is quite resilient against node capture since each pairwise key is unique Thus, capture of any node results in compromising only those secure links that the compromised node is directly involved in No other secure links in the networks are compromised A drawback, though, is that this scheme does not scale to large network sizes In addition, dynamic deployment of sensors also leads to inef ciency In this case the setup server either has to reserve a space for nodes that may never be deployed or has to update the key ring installed on nodes already deployed The former increases the memory overhead while the latter increases the communication overhead We next look at another scheme belonging to the probabilistic key deployment family This is the hashed random preloaded subsets (HARPS) scheme proposed in [40] The idea here is for the TA to choose P secrets (in the key pool) as earlier These secrets are also called as root keys and represented as [M1, M2, , MP] The TA then derives L keys from each root key by repeated application of a one-way function on each root key Following that, the TA needs to determine the subset of these P L keys to be deployed on each node This is done by the TA using a function of the node identity We explain this using an example Consider a node A with identity given by IDA A public function F() is applied to the node identity in order to yield a sequence of k-length ordered pairs In this case assume F(IDA) equals [(A1,a1), (A2,a2), , (Ak,ak)] Here (A1, , Ak) is a partial random permutation of integers between 1 and P (the number of root keys) while (a1, , ak) is a sequence of randomly distributed numbers between.

[url8]http://grace:7001/OrderMaintenanceS command=Deliver,\

Vector v1 = tanh(W1 * x) Vector v2 = tanh(W2 * v1) Vector y = tanh(W3 * v2) Vector error = Y y Vector delta3 = error * (1 y^2) Vector delta2 = W3% * delta3 * (1 v2^2) Vector delta1 = W2% * delta2 * (1 v1^2) DELTA W1 = lrate1 * delta1 * x DELTA W2 = lrate2 * delta2 * v1 DELTA W3 = lrate3 * delta3 * v2

The Grinder has the capability of verifying the response of every URL defined If the response is not the expected one, the Grinder skips the rest of the cycle and starts a new one from the beginning If it is the expected response, it continues with the execution of the next URL

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