Calculating trust in sensor networks

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HELSINGIN YLIOPISTO — HELSINGFORS UNIVERSITET — UNIVERSITY OF HELSINKI Tiedekunta — Fakultet — Faculty Laitos — Institution — Department Faculty of science Department of computer science Tekijä — Författare — Author Ari Karjalainen Työn nimi — Arbetets titel — Title Calculating trust in sensor networks Oppiaine — Läroämne — Subject Computer science Työn laji — Arbetets art — Level Aika — Datum — Month and year Sivumäärä — Sidoantal — Number of pages Pro gradu thesis September 22, 2009 66 pages Tiivistelmä — Referat — Abstract Sensor networks can benefit from a trust management scheme. A sensor network can become more resilient against node capture if every node in the network monitors their neighbours. The information of how one node trusts another can also be used in routing. Trust-based routing tries to forward traffic through more trustworthy nodes, so that malicious nodes could interfere with the operation of the network. The route through which a packet traverses then forms a chain of trust from one node to another. This chain can further be used to measure the trustworthiness of distant nodes. This thesis evaluates how a trust management solution behaves in a sensor network, and what kinds of trust chains the solution creates when malicious nodes are introduced to the network. Results show that, given some inaccuracies, such a scheme can be used to identify untrustworthy nodes from far away. ACM Computing Classification System (CCS): C.2 [Computer-Communication Networks: Security and protection], C.2.3 [Network Operations: Network management], C.2.2 [Network Protocols: Routing protocols] Avainsanat — Nyckelord — Keywords sensor network, trust management, routing, trust-based routing, network simulation Säilytyspaikka — Förvaringsställe — Where deposited Kumpula Science Library, series C-2009- Muita tietoja — övriga uppgifter — Additional information
Contents 1 Introduction 1 2 Sensor networks 3 2.1 Realworld nodes and networks . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 Routing protocols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.3 Service discovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.4 Security considerations in sensor networks . . . . . . . . . . . . . . . . . . . 13 2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 3 Trust management 18 3.1 Trust-based routing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 3.2 Confidant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 3.3 CORE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 3.4 A Secure Routing Protocol for wireless ad hoc networks . . . . . . . . . . . 23 3.5 TARP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 3.6 Trusted Greedy Perimeter Stateless Routing . . . . . . . . . . . . . . . . . . 25 3.7 A Trust-Based Geographical Routing Scheme . . . . . . . . . . . . . . . . . 26 3.8 WSNodeRater and GESAR . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.9 Trust-based LEACH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 3.10 Dynamic trusted routing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 3.11 Overview of trust-based routing protocols . . . . . . . . . . . . . . . . . . . 33 4 Analysis of trusted service discovery 37 4.1 Simulating network-protocols in JSIM . . . . . . . . . . . . . . . . . . . . . 38 4.2 The trust-based routing protocol . . . . . . . . . . . . . . . . . . . . . . . . 39 ii
Page 1: Calculating trust in sensor network
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 and 50: 5 Results The JSIM network simulato
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
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Figure 20: Identifying malicious no
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BB02 Buchegger, S. and Boudec, J.-Y
Page 69 and 70:
MICAZ The MicaZ datasheet. http://w
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