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Event –based Trust Framework Model in Wireless Sensor Networks. Veronica Eyo Sharvari Joshi. What is a Wireless sensor network. Constraints-unsecured wireless sensor nodes. The nodes are left unattended An Adversary can physically compromise the nodes Solution?
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Event –based Trust Framework Model in Wireless Sensor Networks Veronica Eyo Sharvari Joshi
Constraints-unsecured wireless sensor nodes. • The nodes are left unattended • An Adversary can physically compromise the nodes Solution? • Authentication and cryptographic mechanisms alone can not solve this problem • The trust system was used for security in the Wireless sensor network
Trust Systems • These systems identify malicious nodes, computes a trust rating of the node and exclude the nodes from the network.
RFSN (Reputation-based Framework for high Integrity Sensor Network) • First trust based model designed and developed for sensor networks. • It makes use of the watchdog mechanism to collect data and monitor different events going on in the node, to build reputation(Rij)of the node and then get the trust rating (Tij)of the node.
RFSN (contd) Tij = Pj + 1 Pj + Nj + 2 Pj = Positive outcome Nj = Negative outcome RFSN can not distinguish between negative and positive events in the node.
ATSN (Agent-based Trust model for Wireless Sensor Networks) • Addressed the uncertainty issue but still cooperated with the malicious nodes. • Has one value of trust rating for different events.
Outline of the paper • Event based trust framework is proposed to detect malicious sensor nodes • A new protocol ESTN is developed • A new direction in trust system for wireless sensor network is proposed
ETSN (Event-based Trust Framework for Sensor Network) • The trust rating is dependent on different events in the node • Each event on the sensor node has a different trust rating • A sensor node has several trust ratings stored in its neighbor nodes
How does it work? • The agent node • Classifies all the events and then builds a reputation table of the nodes • A trust table is then computed from the reputation table and broadcast to all the nodes.
Event and Event Function • Event E happened in sensor nodes. • Let E={e1 ,e2 ,e3 ,....en } • Event function. • F={F(ei )| ∀ei ∈E,F(ei) ≥1,F(ei )∈N} • Positive outcome pi • Negative outcome ni • <p ,n > is binary event for a certain event ei of sensor node.
More definitions… • Define reputation space of event ei • RS(ei )={<pi ,ni>|ti=pi+ni;pi=F(ei ) or ni=F(ei ) ∀ei∈E} • P<pi ni> (x)= (pi+ni+1)! Xi ^(pi) (1-Xi)^ni pi! ni!
Reputation and Trust • Reputation: opinion of one entity about another • Trust: Expectation of one entity about another. • Reputation space to Trust space • Let Ti (<pi ,ni >)=(pti ,nti ,uti ) be the transformation from binary event <pi ,ni > to trust rating (pti ,nti,uti )
Trust Rating Distribution Mechanism • while True • For all the nodes s and t in the agent node radio • range • For event e1 to en • Agnet node gets the binary event <pi ,ni > • Agent computes the trust rating Tsti; • If (Tsti) < a certain value • Break; • End if • End for • The agent broadcasts the trust rating Tsti; • End for • If the time is the begin of window time • The agent broadcasts all the trust rating Tsti; • End If • End While
Simulation • Modules used: • Wireless sensor networks (xA, xB…xN) • Agent nodes (xi) • Intruder nodes (xm) • Traffic data () • Events generator
Drawbacks • Need to design a special Agent node • Higher processing power for the agent node • Complex architecture • Protection of agent node
Improvements • Protect agent node from discovery. • Broadcast trust rating to the remote monitoring facility.
Conclusion • This trust model can be used in large scale wireless networks • It provides a more accurate guarantee along with cryptographic mechanisms in detecting malicious nodes of different events in sensor networks