Reliability of Wireless Sensors with Code Attestation for Intrusion Detection

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 Verifier sensor Program memo checksum 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: Send ID Random hash function Program memo Verifier sensor 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 Secret share1 Secret share2 neighbor1 Traversal Seed&noise seed checksum neighbor2 Node A

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

12. Modeling (cont’) System activities • Periodic sensing (plus transmitting) T—sensing interval; Es – energy consumption; • Intrusion λ – intrusion rate; e^(-λT) – 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^(- λT) – 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^(- λT) code attestation generated before sensing: prob(attestation happening) = q(1-e ^(- λT) ) the false node being recovered: prob1(recover) = q(1-e ^(- λT) )(1-Pfn)

15. Calculation (cont’) • Case 2: uncompromised in a sensing round; prob(x>T) = e^(-λT) the code attestation still happened though prob(attestation happening) = q*e ^(-λT) recovery triggered prob2(recovery) = q*e ^(-λT)*Pfp So the probability of recovery happening during code attestation is: θ = (prob1 + prob2)/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+ θEr)) • 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 = Gλ(q); MTTF = Gpfn(q); MTTF = Gpfp(q); MTTF = GEs(q); MTTF = GEc(q); MTTF = GEr(q)

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

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

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

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

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

24. Performance and Analysis (cont’) -- MTTF = GEr(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