1. Reliability of Wireless Sensors with Code Attestation for Intrusion Detection Presented by: Yating Wang

2. Outline Background Code attestation Problem definition Modeling Calculation Performance and Analysis Conclusion

3. Background Security properties: authentication secrecy data integrity Security issues for Wireless Sensor Networks(WSN) Outsider attacks (key management) Insider attacks (Intrusion detection)

4. Code Attestation A software based method (verifier) Assumption: original codes must be changed when sensors are compromised Basic method: the trusted verifier evaluates the sensor compromised or not by comparing memory value (hash value) with its original value.

5. Examples of Code Attestation SWATT A sequence of memory address checksum Verifiersensor Program memo Judgement: responding a correct answer within a time boundary Cons: the time to generate challenge; and time out because of channel collision

6. Examples of Code Attestation (cont’) Pre-deployed: Computing digest digital signiture Code attestation: Program memo Verifiersensor Send ID Random hash function Hashing value of codes Judgment: responding a correct hash value Cons: miss the intrusion not within a long service blockage

7. Examples of Code Attestation (cont’) Pre-deployment: filling empty memory with random noise post-deployment: nodes sending distributes seeds to neighbors First scheme: Cluster neighbor1 neighbor2 Node A Secret share1 Secret share2 Traversal Seed&no ise seed checksum

8. Examples of Code Attestation (cont’) Pre-deployment: filling empty memory with random noise post-deployment: nodes sending distributes seeds to neighbors second scheme: neighbor1 neighbor2 Node A neighbor3 C1 R1 C3 R3 C2 R2 Judgment: Voting

9. Problem Definition Problem: the trade-off between energy consumption and code attestation; when should we trigger code attestation Purpose: Maximizing reliability measured by Mean Time to Fail(MTTF) * Fail: either the sensor’s energy is depleted; or the sensor returns false reading

10. Modeling System activities Periodic sensing (plus transmitting) sensing interval – T; unit energy consumption – Es;

11. Modeling (cont’) System activities Periodic sensing (plus transmitting) T—sensing interval; Es – energy consumption; Intrusion: intrusion rate – λ ; if being successfully compromised after sensing, the probability : e^(- λ T)

12. Modeling (cont’) System activities Periodic sensing (plus transmitting) T—sensing interval; Es – energy consumption; Intrusion λ – intrusion rate; e^(- λ T) – healthy when reading Code attestation: Generating probability is q; energy consumption for code attestation is Ec;

13. Modeling (cont’) System activities Periodic sensing (plus transmitting) T—sensing interval; Es – energy consumption; Intrusion λ – intrusion rate; e^(- λ T) – probability of being compromised Code attestation q -- generating probability; Ec– energy consumption: Recovery: energy consumption – Er; generating rate depending on code attestation happening “q” and nodes being attested as unhealthy

14. Calculation Recovery probability case 1: compromised before sensing prob(x<T) = 1-e^(- λ T) code attestation generated before sensing: prob(attestation happening) = q(1-e ^(- λ T) ) the false node being recovered: prob 1 (recover) = q(1-e ^(- λ T) )(1-Pfn)

15. Calculation (cont’) Case 2: uncompromised in a sensing round; prob(x>T) = e^(- λ T) the code attestation still happened though prob(attestation happening) = q*e ^(- λ T) recovery triggered prob 2 (recovery) = q*e ^(- λ T)*Pfp So the probability of recovery happening during code attestation is: θ = (prob 1 + prob 2)/q

16. Calculation (cont’) Probability to return correct readings is prob(node is never compromised) + prob(node was compromised, but recovered) = prob(x>T) + prob1(recovery) = Rq

17. Calculation (cont’) Expected number of rounds before energy depleted (original energy is E) Nq = E(original)/(E(sensing)+E(attestation) + E(recovery)) = E/(Es+q*Ec+q* θ *Er) = E/(Es+q(Ec+ θ Er)) Expected life time – MTTF MTTF = false reading+ energy depleted = ∑i*Rq^i*(1-Rq) + Nq*Ra^Nq (0<i<Nq)

18. Performance and Analysis MTTF = F( λ, T, q, E, Es, Ec, Er, Pfn, Pfp) MTTF = G λ (q); MTTF = G pfn (q); MTTF = G pfp (q); MTTF = G Es (q); MTTF = G Ec (q); MTTF = G Er (q)

19. Performance and Analysis (cont’) -- MTTF = G λ (q)

20. Performance and Analysis (cont’) -- MTTF = G pfn (q)

21. Performance and Analysis (cont’) -- MTTF = G pfp (q)

22. Performance and Analysis (cont’) --MTTF_Es(q)

23. Performance and Analysis (cont’) -- MTTF = G Ec (q)

24. Performance and Analysis (cont’) -- MTTF = G Er (q)

25. Conclusion Developing a probability model to analyze how often code attestation should be generated to maximize the lifetime; Results showing that there is always an optimal q which can make sensor’s reliability maximized Showing that code attestation should be generated more frequently when λ is high, Pfn(Pfp) is low, Ec is low, or Er is low compared with Es