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One way to make this happen and to defend gainst a possible attack is to observe the behavior of the nodes over time and decide whether to trust them These techniques can be used mainly to protect the Position Computation component, since information gathered from untrusted nodes can simply be ignored when computing the position of the nodes For instance, in Liu et al [28] it is proposed a set of techniques for detecting malicious beacon nodes One technique detects malicious beacon nodes by comparing the distance estimated by using the location information provided by these beacon nodes and the distance estimated by means of the signal (eg, RSSI, TDoA, AoA) Another technique evaluates the round-trip time (RTT) between two neighbors, based on the observation that the replay of a (malicious) beacon signal introduces extra delay.

Then, the base station (or sink node) uses such information about malicious beacons to reason about the suspiciousness of each beacon node, and then it lters out malicious beacon nodes accordingly Srinivasan et al [29] extends the techniques proposed by Liu et al [28] by using a continuous scale and a reputation- and trust-based mechanism The result is the Distributed Reputation-based Beacon Trust System (DRBTS), which is a distributed security protocol for excluding malicious beacon nodes In DRBTS, each beacon node monitors its neighborhood for suspicious beacon nodes and provides information by maintaining and exchanging a Neighbor-Reputation Table, in such a way that other sensor nodes can choose trustworthy beacons based on a voting approach 1843 Robust Position Computation Robust position computation can be used in order to increase the security of a localization system This technique can be used when both cryptography and misbehavior detection is compromised.

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In this case, a way to deal with malicious nodes is to accept that they will be present in the network and propose robust position computations that can still work in the presence of bogus information This is done mostly by using statistical and outlier ltering techniques In these cases, it is assumed that the benign nodes outnumber the malicious ones These techniques are used to protect against (or be robust to) attacks on the Position Computation and Distance/Angle Estimation components A technique proposed by Li et al [30] uses the principle behind the least squares data fusion technique to propose an adaptive least squares and least median squares Bar Code In NET Framework Using Barcode scanner for Related: .

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