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If not, the most inconsistent reference is identi ed and removed, and the node location is estimated again It repeats this process until all inconsistent references are discarded The mean square error of the distance measurements is used as an inconsistency indicator A second method proposed by Liu et al [31] is a voting-based location estimation technique In this method, the sensor eld is quantized into a grid of cells, and each reference node votes on the cells to which an unknown node may belong Then, the method selects the most voted cell(s) and uses the center of these cell(s) as the estimated location Voting results can be re ned interactively to improve accuracy This method requires few resources and is suitable for current resource constrained sensor nodes 184.

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4 Location Veri cation If all previous techniques fail to provide the required security, it is still possible to check the computed positions using redundant information available on the nodes and in the network This is the core of some proposed works that focus on the reliability of the nal position computations rather than on avoiding or detecting compromised nodes and attacks For instance, LAD [32] uses deployment knowledge, with a group-based deployment model, to check whether the computed positions of the nodes are consistent with the known model and observations In reference 33 an algorithm is proposed for in-region veri cation, in which a certain node can check whether another node really is inside the particular region that it claims to be.

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The proposed protocol, called Echo, uses known physical properties of both radio-frequency and ultrasound to compute distances and check whether a node really can be inside the claimed region These techniques can be used to provide a layer of security for all three localization system components, since they only verify the result of the overall localization system 1845 Secure and Simple Algorithms Localization systems are vulnerable mostly due to the number of components available to be attacked Another way to secure a localization system is to use simple, less.

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dependable localization algorithms, such as GPS-free, range-free, and/or one hop algorithms One example is SeRLoc [25], in which beacon nodes are equipped with a set of higher-power-directional antennas These nodes send a packet using an asymmetric transmission that contains their position and the sector of the antenna in which the packets are sent Because it is a range-free single-hop localization algorithm, it is protected against attacks aiming at altering range measurements and against regular compromised nodes However, it does not protect against wormholes, which are avoided by checking network properties such as sector uniqueness and communication range A technique similar to SeRLoc is used in HiRLoc [24], which has a greater accuracy but an increased computational and communication complexity Techniques like these can be used to protect the Localization Algorithm Component Another simple and secure algorithm is the already-mentioned Localization with a Mobile Beacon (MBL) [23].

These surveys, published by major consulting firms, industry associations, and the government, provide a great starting point for any plan design analysis. (See 9 for some suggested sources.) Each one of these surveys has a particular focus or slant that you need to be aware of when analyzing their results. Be sure to clarify some basics like:

Although MBL is not designed to be a secure algorithm and the authors do not mention anything about security in their work, the algorithm used in the MBL is quite simple, where a mobile beacon walks the network and broadcasts its position information to near nodes In this case, regular nodes only need to listen to the beacon node and they never exchange messages among themselves By being a simple single-hop algorithm, this localization system is secured against a number of distributed attacks such as the wormhole attack 1846 Comparison of Current Solutions A widely known fact in network security is that there is no system that is totally safe and secure There will always be weak points and the question is simply whether they are acceptable In WSNs, this issue becomes a little more complicated due to resource limitations.

There's one more problem If we run tests twice, we will get a marker for each time the tests fail Here is a test for this: