Calculating trust in sensor networks

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Figure 10: Different methods of calculating chains of trust in a route consisting of alter- nating bad and good nodes. results, so both of them would be good candidates for defining a chain of trust out of individual reputations. 4.4 Summary If a sensor network uses a trust management scheme, or in our case: uses a trust-based routing protocol, the nodes could aggregate individual trusts to form chains of trust from one node to another. This would allow nodes to identify packets from less trustworthy nodes near of far away. All this requires is a way of calculating individual opinions into one representative number. The previous chapter has proposed and compared some methods. One of these methods will be later simulated in the JSIM network simulator using the ATSR routing protocol described in Chapter 3.10. 44
5 Results The JSIM network simulator was used to test how a chain of trust scheme would work in a sensor network. The JSIM simulator was used mainly because it had support for simulating both sensor networks and the Dynamic Trusted Routing-protocol. A basic service discovery-protocol was then implemented on top of the Dynamic Truster Routing protocol-layer. The simulation was setup as a grid of sensor nodes. The simulations were divided into 3 scenarios. Each scenario had a different number of nodes in different kinds of locations. Each scenario was divided into 2 tests. One test included no malicious nodes and one had a number of malicious nodes, implementing a black hole-attack. These two tests could then be compared to see how the network behaves when attacking nodes are inside the network. Three metrics were calculated from each of these tests: average reputations of all the nodes and chains of trust towards two different nodes. An average reputation is derived as the arithmetic average of every nodes opinion of a node (excluding the ones that don’t have an opinion). When presenting the average reputation of nodes, the grid is populated with blue boxes that represent nodes, and black boxes that represent malicious black hole -nodes. The size of a box indicates the average reputation of a node with a larger box meaning a more reputable node. An example of this kind of graph can be found in Figure 11. A chain of trust is calculated for two asking nodes. This test is dependent on the position of the asking node in the grid and the average reputations of other nodes. The test reveals how trustworthy a service would be from any other node in the network for the asking node. When representing chain of trust from one to to another, a different kind of graph is used. One node is designated as the asking node, represented as a yellow box. Every other non-malicious node is represented as blue box, with the size of the box representing the trustworthiness of a route to the asking node. Malicious nodes are presented as black boxes. An unknown node that could not be reached by the asking node is presented as a question mark (?). An example of this kind of graph can be found in Figure 12 on page 45
Page 1 and 2: Calculating trust in sensor network
Page 3 and 4: Contents 1 Introduction 1 2 Sensor
Page 5 and 6: 1 Introduction Wireless sensor netw
Page 7 and 8: 2 Sensor networks Advances in integ
Page 9 and 10: low power. A good guideline for des
Page 11 and 12: Figure 2: The SPEC mote and the tip
Page 13 and 14: n neither use every drop of enthe b
Page 15 and 16: of transmitting directly to the sin
Page 17 and 18: for sensor networks. SensorML conta
Page 19 and 20: would be to eavesdrop on the wires
Page 21 and 22: Development of these sensors leans
Page 23 and 24: called recommending or gossiping ab
Page 25 and 26: of trustworthy nodes. These are nod
Page 27 and 28: node uses this table to determine i
Page 29 and 30: and the nodes willingness (or malic
Page 31 and 32: Trust-based geographical routing do
Page 33 and 34: The rating component also employs a
Page 35 and 36: trust = (1 − w) ∗ trustold + w
Page 37 and 38: that nodes around it send in their
Page 39 and 40: positives, nodes that seem to be fi
Page 41 and 42: 4 Analysis of trusted service disco
Page 43 and 44: To other sensors... Simulated Senso
Page 45 and 46: A simple way of defining this metri
Page 47: esults. The square root-method reac
Page 51 and 52: Figure 12: A graph describing chain
Page 53 and 54: (a) Average reputations with no mal
Page 55 and 56: (a) Chains of trust for node 0, wit
Page 57 and 58: (a) Average reputations with no mal
Page 59 and 60: • The trustworthiness of nodes de
Page 61 and 62: (a) Average reputations with blackh
Page 63 and 64: (a) Chains of trust for node 28 wit
Page 65 and 66: Figure 20: Identifying malicious no
Page 67 and 68: BB02 Buchegger, S. and Boudec, J.-Y
Page 69 and 70: MICAZ The MicaZ datasheet. http://w

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