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Physically Unclonable Function–Based Security and Privacy in RFID Systems

Physically Unclonable Function–Based Security and Privacy in RFID Systems. Leonid Bolotnyy and Gabriel Robins Dept. of Computer Science University of Virginia www.cs.virginia.edu/robins. Contribution and Motivation. Contribution Privacy-preserving tag identification algorithm

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Physically Unclonable Function–Based Security and Privacy in RFID Systems

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  1. Physically Unclonable Function–Based Security and Privacy in RFID Systems Leonid Bolotnyy and Gabriel Robins Dept. of Computer Science University of Virginia www.cs.virginia.edu/robins

  2. Contribution and Motivation Contribution • Privacy-preserving tag identification algorithm • Secure MAC algorithms • Comparison of PUF with digital hash functions Motivation • Digital crypto implementations require 1000’s of gates • Low-cost alternatives • Pseudonyms / one-time pads • Low complexity / power hash function designs • Hardware-based solutions

  3. PUF-Based Security • Physical Unclonable Function (PUF) [Gassend et al 2002] • PUF Security is based on • wire delays • gate delays • quantum mechanical fluctuations • PUF characteristics • uniqueness • reliability • unpredictability • PUF Assumptions • Infeasible to accurately model PUF • Pair-wise PUF output-collision probability is constant • Physical tampering will modify PUF

  4. privacy Privacy in RFID • Privacy A B C Alice was here: A, B, C

  5. Database ID1, p(ID1), p2(ID1), …, pk(ID1) ... IDn, pn(IDn), pn2(IDn), …, pnk(IDn) ID Request Private Identification Algorithm ID p(ID) • It is important to have • a reliable PUF • no loops in PUF chains • no identical PUF outputs • Assumptions • no denial of service attacks (e.g., passive adversaries, DoS detection/prevention mechanisms) • physical compromise of tags not possible

  6. number of runs unreliability probability chain length N μm(1-μ)N-m )k R(μ, N, k)≥ (1 -∑ overall reliability R(0.02, 5, 100) ≥ 0.992 ∞ tuple size expected numberof identifications S(μ, q) = ∑ i [(1 – (1-μ)i+1)q -(1 – (1-μ)i)q] N+1 2 N m i=1 m= S(0.02, 1) = 49, S(0.02, 2) = 73, S(0.02, 3) = 90 Improving Reliability of Responses • Run PUF multiple times for same ID & pick majority • Create tuples of multi-PUF computed IDs &identify a tag based on at least one valid position value (ID1, ID2, ID3)

  7. Privacy Model Experiment: • A passive adversary observes polynomially-many rounds of reader-tag communications with multiple tags • An adversary selects 2 tags • The reader randomly and privately selects one of the 2 tags and runs one identification round with the selected tag • An adversary determines the tag that the reader selected Definition: The algorithm is privacy-preserving if an adversary can notdetermine reader selected tag with probability substantially greater than ½ Theorem: Given random oracle assumption for PUFs, an adversary has no advantage in the above experiment.

  8. valid signature σ: υ (M, σ) = 1 K • forged signature σ’ : υ (M’, σ’) = 1, M = M’ K PUF-Based MAC Algorithms • MAC = (K, τ, υ) • MAC based on PUF • Motivation: “yoking-proofs”, signing sensor data • large keys (PUF is the key) • cannot support arbitrary messages • Assumptions • adversary can adaptively learn poly-many (m, σ) pairs • signature verifiers are off-line • tag can store a counter (to protect against replay attacks)

  9. Large Message Space Assumption: tag can generate good random numbers (can be PUF-based) Key: PUF σ (m) =c, r1, ..., rn, pc(r1, m), ..., pc(rn, m) • Signature verification • requires tag’s presence • password-based or in radio-protected environment (Faraday Cage) • learn pc(ri, m), 1 ≤ i ≤ n • verify that the desired fraction of PUF computations is correct • To protect against hardware tampering • authenticate tag before MAC verification • store verification password underneath PUF

  10. n n i n j probv(n, t, μ)= 1 -∑ μi(1-μ)n-i i=t+1 n probf(n, t, τ)= 1 -∑ τj(1-τ)n-j j=t+1 α < probv ≤ 1 and probf ≤ β ≤ 1 0 ≤ t ≤ n-1 Choosing # of PUF Computations probv(n, 0.1n, 0.02) probf(n, 0.1n, 0.4)

  11. Theorem Given random oracle assumption for a PUF, the probability that an adversary could forge a signature for a message is bounded from above by the tag impersonation probability.

  12. message counter PUF Key[p, mi, c] = c, pc(1)(mi), ..., pc(n) (mi) σ(m) =c, pc(1)(m), ..., pc(n)(m), ..., c+q-1, pc+q-1(1)(m), pc+q-1(n)(m) sub-signature Small Message Space Assumption: small and known a priori message space PUF reliability is again crucial Verify that the desired number of sub-signatures are valid

  13. Theorem Given random oracle assumption for a PUF, the probability that an adversary could forge a signature for a message is bounded by the tag impersonation probability times the number of sub-signatures.

  14. original clone • Impersonation attacks • manufacture an identical tag • obtain (steal) existing PUFs • Modeling attacks • build a PUF model to predict PUF’s outputs • Side-channel attacks • algorithm timing • power consumption • Hardware-tampering attacks • physically probe wires to learn the PUF • physically read-off/alter keys/passwords Attacks on MAC Protocols

  15. algorithm # of gates MD4 MD5 SHA-256 AES Yuksel PUF 7350 8400 10868 3400 1701 545 Comparison of PUF With Digital Hash Functions • Reference PUF: 545 gates for 64-bit input • 6 to 8 gates for each input bit • 33 gates to measure the delay • Low gate count of PUF has a cost • probabilistic outputs • difficult to characterize analytically • non-unique computation • extra back-end storage • Different attack target for adversaries • model building rather than key discovery • Physical security • hard to break tag and remain undetected

  16. PUF Design • Attacks on PUF • impersonation • modeling • hardware tampering • side-channel • Weaknesses of existing PUF reliability • New PUF design • no oscillating circuit • sub-threshold voltage • Compare different non-linear delay approaches

  17. } in progress Conclusions and Future Work • PUF: hardware primitive for RFID security • Identification and MAC algorithms based on PUF • PUFs protect tags from physical attacks • PUFs is the key • Develop theoretical framework for PUF • Design new sub-threshold voltage based PUF • Manufacture and test PUFs • varying environmental conditions • motion, acceleration, vibration, temperature, noise • Design new PUF-based security protocols • ownership transfer • recovery from privacy compromise • PUFs on RFID readers

  18. Thank You Questions ? Leonid Bolotnyy lbol@cs.virginia.edu Dept. of Computer Science University of Virginia

  19. PUF-Based Ownership Transfer • Ownership Transfer • To maintain privacy we need • ownership privacy • forward privacy • Physical security is especially important • Solutions • public key cryptography (expensive) • knowledge of owners sequence • trusted authority • short period of privacy

  20. s1,2 s2,4 s2,5 s3,8 s3,9 s3,10 Using PUF to Detect and Restore Privacy of Compromised System s1,0 s1,1 s2,0 s2,1 s2,2 s2,3 s3,0 s3,1 s3,2 s3,3 s3,4 s3,5 s3,6 s3,7 • Detect potential tag compromise • Update secrets of affected tags

  21. Related Work on PUF • Optical PUF [Ravikanth 2001] • Silicon PUF [Gassend et al 2002] • Design, implementation, simulation, manufacturing • Authentication algorithm • Controlled PUF • PUF in RFID • Identification/authentication [Ranasinghe et al 2004] • Off-line reader authentication using public key cryptography [Tuyls et al 2006]

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