Calculating trust in sensor networks

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Figure 11: A graph of average reputations in a grid of nodes. The grid contains 17 normal nodes and 3 black hole -nodes. 47. This way each scenario would produce 6 different results that could be used to assess how a trusted routing protocol and a chain of trust -scheme will operate in a sensor network. Since a trusted routing protocol requires information about its neighbours before it will operate normally, the network was primed by transmitting random data between the nodes. This was implemented by two nodes on the opposite corners of the grid each downloading roughly 2 kB of data from each non-malicious node. In a 5x5 grid of nodes with 23 transmitting nodes and a 256 byte payload this would amount to around 170 packets transmitted. At that point, every node will have a pretty good opinion about its neighbours. 5.1 Scenario 1: A cloud of nodes Scenario number 1 consists of 25 nodes aligned in a 5x5 grid. When malicious nodes are added to the grid, they are spaced as a cluster of 7 nodes near one side of the grid. Nodes in the opposite left lower- and right upper-corners function as the service asking nodes. 46
Figure 12: A graph describing chains of trust of other nodes for node in position 0,0 (the yellow box). The larger the box, the more trustworthy a route to a node is. This graph contains 13 normal nodes (one unreachable) and 3 black hole -nodes. The addition of the black hole -nodes does not completely cut off the two corner nodes, but only a few friendly nodes connect the two nodes. The results from the scenario shows that at least when no malicious nodes are in the grid, both the average reputations and chains of trust are as predicted. Findings from these graphs are: • In Figure 13c there seems to be number of nodes scattered randomly in the grid that are less trustworthy (under 0.7) than the rest of the nodes (above 0.75). This is because all of their service replies have taken a route through either nodes coordinates 0,100 or 100. This is because the node on 0,0 happens to have less trust for these two nodes. It appers that although all of the nodes have dropped packets, these two nodes have done it a bit more than their neighbours. So it is more a fault of why these two nodes have misbehaved, there is nothing particularly wrong with the other 47
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 and 48: esults. The square root-method reac
Page 49: 5 Results The JSIM network simulato
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

Calculating trust in sensor networks

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