1 Department of Computer Science University of Virginia New Directions in Reliability, Security and Privacy in Radio Frequency Identification Systems Leonid Bolotnyy Gabriel Robins

2 Talk Outline Introduction to RFID Reliable Object Identification –Multi-Tag RFID Systems Physical Security and Privacy –PUF-Based Algorithms Inter-Tag Communication –Generalized Yoking-Proofs Common Themes and Conclusion

3 Talk Outline Introduction to RFID Reliable Object Identification –Multi-Tag RFID Systems Physical Security and Privacy –PUF-Based Algorithms Inter-Tag Communication –Generalized Yoking-Proofs Common Themes and Conclusion

4 General RFID System Tag ID Tags Reader Local Server

5 Introduction to RFID passivesemi-passiveactive Tags types: Frequencies: Low (125KHz), High (13.56MHz), UHF (915MHz) Coupling methods: reader antenna signal Inductive couplingBackscatter coupling

6 RFID History What’s next?

7 Talk Outline Introduction to RFID Reliable Object Identification –Multi-tag RFID Systems Physical Security and Privacy –PUF-Based Algorithms Inter-Tag Communication –Generalized Yoking-Proofs Common Themes and Conclusion

8 Obstacles of Reliable Identification Bar-codes vs. RFID –line-of-sight –scanning rate Object detection obstacles –radio noise is ubiquitous –liquids and metals are opaque to RF milk, water, juice metal-foil wrappers –temperature and humidity –objects/readers moving speed –object occlusion –number of objects grouped together –tag variability and receptivity –tag aging

9 Case Studies Defense Logistics Agency trials (2001) –3% of moving objects did not reach destination –20% of tags recorded at every checkpoint –2% of a tag type detected at 1 checkpoint –some tags registered on arrival but not departure Wal-Mart experiments (2005) –90% tag detection at case level –95% detection on conveyor belts –66% detection inside fully loaded pallets

10 Multi-Tag RFID Use Multiple tags per object to increase reliability of object detection/identification

11 The Power of an Angle Inductive coupling: distance ~ (power) 1/6 Far-field propagation: distance ~ (power) 1/2 Optimal Tag Placement: B-field β power ~ sin 2 (β)

12 Equipment and Setup Setup –empty room –20 solid non-metallic & 20 metallic and liquid objects –tags positioned perpendicular to each other –tags spaced apart –software drivers Equipment x1 x8 x4 x100’s

13 Experiments Read all tags in reader’s field Randomly shuffle objects Compute average detection rates Variables –reader type –antenna type –tag type –antenna power –object type –number of objects –number of tags per object –tags’ orientation –tags’ receptivity

14 Linear Antennas 1Tag: 58% 2Tags: 79% 3Tags: 89% 4Tags: 93%

15 Circular Antennas 1Tag: 75% 2Tags: 94% 3Tags: 98% 4Tags: 100%

16 Linear Antennas vs. Multi-tags 1 Reader, 1 Tag 58.0% 2 Readers, 1 Tag 64.9% 1 Reader, 2 Tags 79.3% 2 Readers, 2 Tags 84.5% Δ=21.3% Δ=19.8% Δ= 5.2% Δ=14.4% Δ= 6.9%

17 Importance of Tag Orientation 21% -7% 12% 25%

18 Detection in Presence of Metals & Liquids Power=31.6dBm, No Liquids/MetalsPower=31.6dBm, With Liquids/Metals Power=27.6dBm, No Liquids/Metals Power=27.6dBm, With Liquids/Metals Circular Antenna Number of Tags Detection Probability Decrease in solid/non-liquid object detection Significant at low power Similar results for linear antennas

19 Varying Number of Objects Experiment 1: 15 solid non-metallic & 15 liquids and metals Experiment 2: 20 solid non-metallic & 20 liquids and metals Metals & Liquids ∆ : 3%-13%

20 Applications of Multi-Tags ReliabilityAvailability Safety Localization

21 More Applications Tagging Bulk MaterialsPackaging Theft PreventionSecurity

22 Economics of Multi-Tags YearCost Rapid decrease in passive tag cost 5 cent tag expected in penny tag in a few years

23 Cost Trends Time

24 Multi-Tag Conclusion Unreliability of object detection –radio noise is ubiquitous –liquids and metals are opaque to RF milk, water, juice metal-foil wrappers –temperature and humidity –objects/readers moving speed –object occlusion –number of objects grouped together –tag variability and receptivity –tag aging Many useful applications Favorable economics $0.00 $0.20 $0.40 $0.60 $0.80 $ Historical CostPrediction Cost

25 Talk Outline Introduction to RFID Reliable Object Identification –Multi-tag RFID Systems Physical Security and Privacy –PUF-Based Algorithms Inter-Tag Communication –Generalized Yoking-Proofs Common Themes and Conclusion

26 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 MD MD SHA Yuksel 1701 AES 3400 algorithm # of gates

27 PUF-Based Security Physical Unclonable Function [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

28 Individual Privacy in RFID Privacy ABC Alice was here: A, B, C privacy

29 Hardware Tampering Privacy Models 1.Restrict memory tampering functions - allow bit flips read-proof tamper-proof Allow adversary to tamper with tag’s memory 3. Detect privacy compromise - detect PUF modification 2. Purely physical privacy - no digital secrets Cannot provide privacy without restricting adversary - simple secret overwrite allows tag tracking

30 Private Identification Algorithm Assumptions –no denial of service attacks (e.g., passive adversaries, DoS detection/prevention mechanisms) –physical compromise of tags not possible It is important to have –a reliable PUF –no loops in PUF chains –no identical PUF outputs ID Request p(ID) ID Database ID 1, p(ID 1 ), p 2 (ID 1 ), …, p k (ID 1 )... ID n, p n (ID n ), p n 2 (ID n ), …, p n k (ID n )

31 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 –short period of privacy –trusted authority

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

33 Large Message Space σ (m) = c, r 1,..., r n, p c (r 1, m),..., p c (r n, m) Assumption: tag can generate good random numbers (can be PUF-based) Signature verification requires tag’s presence password-based or in radio-protected environment (Faraday Cage) learn p c (r i, 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 Key: PUF

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

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

36 Conclusions and Future Work Hardware primitive for RFID security Identification, MAC, Ownership Transfer, and Tag Authentication Algorithms Properties: –Physical keys –Protect tags from physical attacks –New attack models Future Work: –Design new PUF –Manufacture and test PUF –Develop PUF theory –New attack models

37 Talk Outline Introduction to RFID Reliable Object Identification –Multi-tag RFID Systems Physical Security and Privacy –PUF-Based Algorithms Inter-Tag Communication –Generalized Yoking-Proofs Common Themes and Conclusion

38 Inter-Tag Communication in RFID Idea: Heterogeneity in ubiquitous computing Applications:

39 “Yoking-Proofs” Applications – verify that: –medicine bottle sold together with instructions –tools sold together with safety devices –matching parts were delivered together –several forms of ID were presented Problem Statement: Generate proof that a group of passive tags were identified nearly-simultaneously Key Observation: Passive tags can communicate with each other through reader Yoking: joining together / simultaneous presence of multiple tags

40 Assumptions and Goals Assumptions –Tags are passive –Tags have limited computational abilities –Tags can compute a keyed hash function –Tags can maintain some state –Verifier is trusted and powerful Solution Goals –Allow readers to be adversarial –Make valid proofs improbable to forge –Allow verifier to verify proofs off-line –Detect replays of valid proofs Timer on-board a tag –Capacitor discharge can implement timeout

41 Generalized “Yoking-Proof” Protocol Anonymous Yoking: tags keep their identities private Idea: construct a chain of mutually dependent MACs

42 Related Work on “Yoking-Proofs” Saito and Sakurai [2005] –solution relies on timestamps generated by trusted database –violates original problem statement –one tag is assumed to be more powerful than the others –vulnerable to “future timestamp” attack Piramuthu [2006] –discusses inapplicable replay-attack problem of Juels’ protocol –independently observes the problem with Saito/Sakurai protocol –proposed fix only works for a pair of tags –violates original problem statement Juels [2004] –protocol is limited to two tags –no timely timer update (minor/crucial omission)

43 Talk Outline Introduction to RFID Reliable Object Identification –Multi-tag RFID Systems Physical Security and Privacy –PUF-Based Algorithms Inter-Tag Communication –Generalized Yoking-Proofs Common Themes and Conclusion

44 Generalized “Yoking-Proofs” Multi-Tags PUF-Based Security and Privacy RFID Common Themes

45 Conclusion and Future Research Contributions Future Research –More multi-tag tests –Object localization using multi-tags –Split tag functionality between tags –Prevent adversarial merchandize inventorization –PUF design –More examples of inter-tag communication –Applications of RFID

46 Publications L. Bolotnyy and G. Robins, Multi-tag Radio Frequency Identification Systems, IEEE Workshop on Automatic Identification Advanced Technologies (Auto-ID), Oct L. Bolotnyy and G. Robins, Randomized Pseudo-Random Function Tree Walking Algorithm for Secure Radio- Frequency Identification, IEEE Workshop on Automatic Identification Advanced Technologies (Auto-ID), Oct L. Bolotnyy and G. Robins, Generalized “Yoking Proofs” for a Group of Radio Frequency Identification Tags, International Conference on Mobile and Ubiquitous Systems (Mobiquitous), San Jose, CA, July L. Bolotnyy and G. Robins, Physically Unclonable Function -Based Security and Privacy in RFID Systems, IEEE International Conference on Pervasive Computing and Communications (PerCom), New York, March L. Bolotnyy, S. Krize, and G. Robins, The Practicality of Multi-Tag RFID Systems, International Workshop on RFID Technology - Concepts, Applications, Challenges (IWRT), Madeira, Portugal, June L. Bolotnyy and G. Robins, The Case for Multi-Tag RFID Systems, International Conference on Wireless Algorithms, Systems and Applications (WASA), Chicago, Aug L. Bolotnyy and G. Robins, Multi-Tag RFID Systems, International Journal of Internet and Protocol Technology, Special issue on RFID: Technologies, Applications, and Trends, 2(3/4), conference and 1 journal paper in submission 2 invited book chapters in preparation Security in RFID and Sensor Networks, to be published by Auerbach Publications, CRC Press, Taylor&Francis Group

47 More Successes Deutsche Telekom (largest in EU) offered to patent our multi-tags idea. Received $450,000 NSF Cyber Trust grant, 2007 (PI: Gabriel Robins). Technical Program Committee member: International Workshop on RFID Technology - Concepts, Applications, Challenges (IWRT), Barcelona, Spain, June Our papers and presentation slides used in lecture-based undergraduate/graduate courses (e.g., Rice University, George Washington University).

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49 Thank You! Questions? Dissertation Committee: Gabriel Robins (advisor), Dave Evans, Paul Reynolds, Nina Mishra, and Ben Calhoun Stephen Wilson, Blaise Gassend, Daihyun Lim, Karsten Nohl, Patrick Graydon, and Scott Krize

50 BACK UP SLIDES NOT USED DURING PRESENTATION

51 Types of Multi-Tags Triple-Tags n-Tags Dual-Tags –Own Memory Only –Shared Memory Only –Own and Shared Memory Redundant Tags Complimentary Tags

52 Controlling Variables 1.Radio noise 2.Tag variability 3.Reader variability 4.Reader power level 5.Distance to objects & type, # of antennas

53 Circular Antennas vs. Multi-Tags Power = 31.6dBm Object Number Detection Probability 1 Reader, 1 Tag 75.9% 2 Readers, 1 Tag 91.0% 1 Reader, 2 Tags 94.2% 2 Readers, 2 Tags 99.4% Δ=18.3% Δ=8.4% Δ= 5.2% Δ=3.2% Δ= 15.1%

54 1 Tag2 Tags3 Tags4 Tags Power Decrease in detection with decrease in power More rapid decrease in detection for circular antennas

55 Low detection probabilities Drop in detection at low power Linear antennas outperform circular Multi-tags better than multiple readers Multi-Tags on Metals and Liquids

56 Detection Delta 1 tag 2 tags 3 tags 1 tag 2 tags 3 tags 1 tag 2 tags 3 tags 1 tag 2 tags 3 tags

57 Anti-Collision Algorithms BinaryNo Effect Binary VariantNo Effect RandomizedLinear Increase**No Effect* STACCauses DoSNo Effect* Slotted AlohaLinear Increase**No Effect* AlgorithmRedundant TagsConnected-Tags * Assuming tags communicate to form a single response ** If all tags are detected

58 Business Case for RFID Costs & benefits (business case) –Moore’s law –higher employee productivity –automated business processes –workforce reduction Tag manufacturing yield and testing –30% of chips damaged during manufacturing –15% damaged during printing [U.S. GAO] –20% tag failure rate in field [RFID Journal] –5% of tags purchased marked defective

59 RFID Tag Demand Demand drivers –tag cost –desire to stay competitive Cost effective tag design techniques –memory design (self-adaptive silicon) –assembly technology (fluidic self assembly) –antenna design (antenna material) Increase in RFID tag demand Decrease in RFID tag cost

60 Thesis Multi-tags can considerably improve reliability in RFID systems at a reasonable cost; effective PUF implementations can enable hardware- tampering resistant algorithms for RFID security and privacy; generalized yoking-proofs can provide auditing mechanisms for the near-simultaneous reading of multiple RFID tags.

61 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]

62 Privacy Model 1.A passive adversary observes polynomially-many rounds of reader-tag communications with multiple tags 2.An adversary selects 2 tags 3.The reader randomly and privately selects one of the 2 tags and runs one identification round with the selected tag 4.An adversary determines the tag that the reader selected Experiment: Definition: The algorithm is privacy-preserving if an adversary can not determine 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.

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

64 Choosing # of PUF Computations α < prob v ≤ 1 and prob f ≤ β ≤ 1 0 ≤ t ≤ n-1 i=t+1 μ i (1-μ) n-i prob v (n, t, μ) = 1 - ∑ n nini j=t+1 τ j (1-τ) n-j prob f (n, t, τ) = 1 - ∑ n njnj prob v (n, 0.1n, 0.02) prob f (n, 0.1n, 0.4)

65 MAC Large Message Space 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.

66 MAC Small Message Space 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.

67 Purely Physical Ownership Transfer oid = h(counter) r 1, a = h s (r 0, r 1 ) r 0, c 1,..., c n (r 1, a) Challenges sent to tag in increasing order counter = counter - 1 h s (r 1, new) Properties: –All PUF computations must be correct –PUF-based random number generator –Physical write-once counter –oid is calculated for each identification –Inherently limited # of owners s = p oid (v 1 )... p oid (v n ) v 1 = h(c 1 ),..., v n = h(c n ) ++

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

69 PUF vs. Digital Hash Function 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 MD MD SHA Yuksel 1701 PUF 545 AES 3400 algorithm # of gates

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

71 PUF Contribution and Motivation Contribution Physical privacy models Privacy-preserving tag identification algorithm Ownership transfer 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

72 Speeding Up The Yoking Protocol starting / closing tags Idea: split cycle into several sequences of dependent MACs Requires –multiple readers or multiple antennas –anti-collision protocol