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Event based Trust Framework model in wireless sensor networks PowerPoint Presentation

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On : Jan 08, 2015

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  • Slide 1 - Event –based Trust Framework Model in Wireless Sensor Networks Veronica Eyo Sharvari Joshi
  • Slide 2 - What is a Wireless sensor network
  • Slide 3 - 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 Constraints-unsecured wireless sensor nodes.
  • Slide 4 - These systems identify malicious nodes, computes a trust rating of the node and exclude the nodes from the network. Trust Systems
  • Slide 5 - 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 (Reputation-based Framework for high Integrity Sensor Network)
  • Slide 6 - Tij = Pj + 1 Pj + Nj + 2 Pj = Positive outcome Nj = Negative outcome RFSN can not distinguish between negative and positive events in the node. RFSN (contd)
  • Slide 7 - Addressed the uncertainty issue but still cooperated with the malicious nodes. Has one value of trust rating for different events. ATSN (Agent-based Trust model for Wireless Sensor Networks)
  • Slide 8 - 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 Outline of the paper
  • Slide 9 - 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 ETSN (Event-based Trust Framework for Sensor Network)
  • Slide 10 - System Architecture
  • Slide 11 - 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. How does it work?
  • Slide 12 - 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

    is binary event for a certain event ei of sensor node. Event and Event Function

  • Slide 13 - Define reputation space of event ei RS(ei )={|ti=pi+ni;pi=F(ei ) or ni=F(ei ) ∀ei∈E} P (x)= (pi+ni+1)! Xi ^(pi) (1-Xi)^ni pi! ni! More definitions…
  • Slide 14 - Reputation: opinion of one entity about another Trust: Expectation of one entity about another. Reputation space to Trust space Let Ti ()=(pti ,nti ,uti ) be the transformation from binary event to trust rating (pti ,nti,uti ) Reputation and Trust
  • Slide 15 - 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 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 Trust Rating Distribution Mechanism
  • Slide 16 - Modules used: Wireless sensor networks (xA, xB…xN) Agent nodes (xi) Intruder nodes (xm) Traffic data () Events generator Simulation
  • Slide 17 - Network Setup
  • Slide 18 - Results and Analysis
  • Slide 19 - Result and analysis
  • Slide 20 - Need to design a special Agent node Higher processing power for the agent node Complex architecture Protection of agent node Drawbacks
  • Slide 21 - Protect agent node from discovery. Broadcast trust rating to the remote monitoring facility. Improvements
  • Slide 22 - 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 Conclusion
  • Slide 23 - Questions?
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