Protocols for Secure Communication in Wireless Sensor Networks

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186 Chapter 6. Integrity-Preserving Communications The standard topology being used for simulations is a 1000×1000 units square on which 500 sensor nodes are randomly and uniformly placed. The nodes have a communication range of 100 units. This choice of parameters guarantees almost certainly, i.e. with a probability greater than .99, full connectivity of the graph according to equation (2.1), whereas border effects are being ignored. Simulation results have been obtained by taking the average of a set of simulation runs. As discussed in the previous section, each such set contains data from usually 20 or more simulation rounds. The simplest attack model is a random spread attack, where each node being captured is randomly and independently chosen. Figure 6.14 shows the effect of such an attack on the absolute number of live and functional paths. The live paths correspond to the functional paths under an end-to-end authentication scheme, which is the best achievable result. The number of live paths deteriorates rapidly under an attack, since each captured node removes a live path for each remaining uncompromised node. With half the nodes being captured, only a quarter of the live paths remain. The number of functional paths for the Canvas and the hop-to-hop authentication schemes are well below the number of live paths if there is a high number of compromised nodes in the network. This, of course, is expected, since hop-to-hop authentication provides no protection against malicious nodes at all. Thus, the difference to the end-to-end scheme is dramatic. Canvas is able to perform much better if there are few compromised nodes, but as this number grows, more of them will be placed adjacent to each other and thus become able to undermine the protection provided by Canvas. The strength of Canvas is with a small number of compromised nodes, against which it is quite effective. Canvas is able to keep the number of functional paths close to the live paths, since isolated captured nodes can do no harm to paths of which they are not endpoints. Only when captured nodes are placed close to each other, they diminish the integrity of other paths. In the graph, this effect surfaces when around 50 nodes, i.e. 10% of all nodes, are captured. While Figure 6.14 shows the absolute number of paths, the picture gets more detailed if the number of live paths is used as a baseline and Ψ is used as a measure, as defined in Equation 3.1. Using this measure, the graph in Figure 6.15 is obtained. Here, the advantage of Canvas compared to hop-to-hop authentication is visible even more strikingly. While Canvas manages to keep Ψ close to one for a small number of compromised nodes, it rapidly falls for the hopto-hop scheme right from the start.
6.4. Security Evaluation 187 Paths 250000 200000 150000 100000 50000 Random attack (square) 0 0 100 200 300 400 500 Compromised nodes Live paths Canvas, functional paths (analytical) Canvas, functional paths Hop-to-hop, functional paths Figure 6.14: Deterioration of communication paths under a random attack; measured by absolute count of paths Functional path quotient 1 0.8 0.6 0.4 0.2 Random spread attack (square) 0 0 100 200 300 400 500 Compromised nodes Canvas, functional paths (analytical) Hop-to-hop, functional paths Canvas, functional paths Figure 6.15: Deterioration of communication paths under a random attack; measured by Ψ
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Diss. ETH Nr. 18174 Protocols for S
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ii often ad hoc and transient natur
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iv Dieses Ziel kann durch kryptogra
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Contents 1 Introduction 1 1.1 Backg
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Contents ix 3.3.1 Basic Assumptions
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Contents xi 6.3 Performance Evaluat
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Chapter 1 Introduction 1.1 Backgrou
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1.3. Contributions 3 on the other h
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1.4. Thesis Outline 5 • Mario Str
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Chapter 2 Wireless Sensor Networks
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2.1. Applications of Wireless Senso
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2.1. Applications of Wireless Senso
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2.2. Sensor Node Characteristics 13
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2.3. Related Network Types 21 zero,
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2.3. Related Network Types 23 • P
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2.3. Related Network Types 25 PAN,
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2.4. Related Device Types 27 in con
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2.4. Related Device Types 29 ports
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2.5. Sensor Network Models 31 both
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2.5. Sensor Network Models 33 are a
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2.6. Simulation of Sensor Networks
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2.7. Security Requirements 41 terac
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2.7. Security Requirements 43 netwo
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2.7. Security Requirements 45 acces
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2.7. Security Requirements 47 2.7.6
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2.7. Security Requirements 49 of te
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2.8. Cryptography for Sensor Networ
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2.9. Existing Approaches to Wireles
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Chapter 3 A Security Model for Wire
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3.1. Attack Paths 67 field (cf. [17
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3.1. Attack Paths 69 modules [63].
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3.1. Attack Paths 71 closed environ
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3.2. Attack Objectives 73 • Timel
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3.2. Attack Objectives 75 Critical
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3.2. Attack Objectives 77 Actors A
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3.3. Adversary Characteristics 79 a
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3.3. Adversary Characteristics 81 c
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3.3. Adversary Characteristics 83 p
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3.4. The Cost of End-to-End Securit
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3.4. The Cost of End-to-End Securit
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3.5. Approximating End-to-End Secur
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3.7. Summary 95 Location-constraine
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Chapter 4 Key Establishment Shared
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4.2. Random Key Pre-Distribution 99
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4.3. Key Agreement Based on Hash Ch
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4.4. Multiple Hash Chains for Key A
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4.4. Multiple Hash Chains for Key A
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4.5. Strengthening Random Key Pre-D
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4.6. Related Work 123 pc = 0.33 Du-
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4.6. Related Work 125 Probability o
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4.7. Summary 127 The security of th
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Chapter 5 Multipath Communication T
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5.1. Principles of Multipath Commun
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5.2. Routing on Spanning Trees 133
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Page 223 and 224: 6.7. Applications 209 Psi 1 0.8 0.6
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Page 229 and 230: 6.9. Summary 215 simulations and by
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Page 233 and 234: 7.1. Secure Communication in Wirele
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Page 237 and 238: Bibliography [1] Specification of t
Page 239 and 240: Bibliography 225 1st European Works
Page 241 and 242: Bibliography 227 [41] Rohan Chitrad
Page 243 and 244: Bibliography 229 [64] L. Eschenauer
Page 245 and 246: Bibliography 231 [85] Yahoo! Inc. D
Page 247 and 248: Bibliography 233 [105] Kristof Van
Page 249 and 250: Bibliography 235 [126] Anne Marie M
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Bibliography 237 [150] Sylvia Ratna
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Bibliography 239 [172] Thanos Stath
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Bibliography 241 [192] Eric W. Weis
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Curriculum Vitae Harald Vogt Person
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