1. Adversarial Models for Wireless Communication Andrea W. Richa Arizona State University SIROCCO'13, Andrea Richa1

2. Motivation Channel availability hard to model: ● Mobility ● Packet injection ● Temporary Obstacles ● Background noise ● Physical Interference ● Co-existing networks ● Jammer 2SIROCCO'13, Andrea Richa

3. 3 Physical layer jamming ●A physical jammer listens to the open medium and broadcasts in the same frequency band as network –can lead to significant disruption of communication at low cost for the jammer honest nodes jammer

4. Motivation Channel availability hard to model: ● Mobility ● Packet injection ● Temporary Obstacles ● Background noise ● Physical Interference ● Co-existing networks ● Jammer 4SIROCCO'13, Andrea Richa all contribute to some form of “background noise”

5. Motivation Ideal world: Usual approach adopted in theory. 0 time Background noise : noise level 5SIROCCO'13, Andrea Richa

6. Motivation Ideal world: OR Usual approach adopted in theory. 0 time Background noise : noise level 6SIROCCO'13, Andrea Richa

7. Motivation Ideal world: OR (bounded, predictable) Usual approach adopted in theory. 0 time Background noise : noise level 7SIROCCO'13, Andrea Richa

8. Motivation Real world: How to model this??? 0 time background noise : noise level 8SIROCCO'13, Andrea Richa

9. Our Approach: Adversarial Jamming Background noise (microwave, radio signal, etc.) Intentional jammer Temporary Obstacles (cars etc.) Co-existing networks … X X X X X 9SIROCCO'13, Andrea Richa

10. Our Approach: Adversarial Jamming ●Idea: model unpredictable behaviors via adversary (a.k.a. adversarial jammer)! X X X X X 10SIROCCO'13, Andrea Richa

11. Overview ●Adaptive adversary –Single-hop scenario –Simple (yet powerful) idea –MAC protocol ●Reactive adversary –Fairness ●Adaptive adversary in multi-hop networks ●Application: Leader Election ●Other adversarial models ●Future work SIROCCO'13, Andrea Richa11

12. SIROCCO'13, Andrea Richa12 Wireless communication model ●single frequency: e.g., sensor nodes ●at each time step, a node may decide to transmit a packet (nodes continuously contend to send packets) ●a node may transmit or sense the channel at any time step (half-duplex) ●when sensing the channel a node v may –sense an idle channel –receive a packet –sense a busy channel (due to interference or adversarial jamming) v

13. SIROCCO'13, Andrea Richa13 Single-hop wireless network ●[Awerbuch, R., Scheideler, PODC’08] ●n reliable honest nodes and a jammer (adversary); all nodes within transmission range of each other and of the jammer jammer

14. SIROCCO'13, Andrea Richa14 Adaptive adversary ●knows protocol and entire history ●(T,λ)-bounded adversary, 0 < λ < 1: in any time window of size w ≥ T, the adversary can jam ≤ λw time steps 0 1 … w steps jammed by adversary other steps

15. SIROCCO'13, Andrea Richa15 Constant-competitive protocol ●a protocol is called constant-competitive against a (T,λ)-bounded adversary if the nodes manage to perform successful transmissions in at least a constant fraction of the steps (w.h.p. or on expectation), for any sufficiently large number of steps successful transmissions steps jammed by adversary 0 1 … w other steps (idle channel, message collisions)

16. SIROCCO'13, Andrea Richa16 Our main contribution ●symmetric local-control MAC protocol that is constant-competitive against any (T,1-ε)-bounded adaptive adversary after Ω (T / ε) steps w.h.p., for any constant 0<ε<1 and any T. ●energy efficient: –converges to bounded amount of energy consumption due to message transmissions by nodes under continuous adversarial jamming (ε=0) ●fast recovery from any state ~

17. SIROCCO'13, Andrea Richa17 Pros and Cons Pros: ●no prior knowledge of global parameters –nodes do not know ε ●no IDs needed Cons: ●nodes know rough estimate γ=O(1/(log T + loglog n)) –allow for superpolynomial change in n and polynomial change in T over time ●fair channel use is not guaranteed –we will see how to fix that later

18. Physical Layer Traditional Jamming Defenses ●spread spectrum & frequency hopping: –Many references in the literature (specially more applied work)… – rely on broad spectrum (large number of available frequencies). However, sensor nodes or common wireless devices based on 802.11 have narrow spreading factors –Our approach is orthogonal to broad spectrum techniques, and can be used in conjunction with those. SIROCCO'13, Andrea Richa18

19. MAC Layer Jamming Defenses ●random backoff: –adaptive adversary too powerful for MAC protocols based on random backoff\tournaments (including the 802.11 standard [ Bayrataroglu, King, Liu, Noubir, Rajaraman, Thapa, INFOCOM’08 ]) ●[Gilbert, Guerraoui, Newport, OPODIS’06] : cannot handle adaptive adversaries with high jamming rate –more general scenario (adversary can also introduce malicious messages) –nodes know n –not energy efficient ●Others (channel surfing, coding strategy,etc.): also cannot handle adaptive adversary SIROCCO'13, Andrea Richa 19

20. Overview ●Adaptive adversary –Single-hop scenario –Simple (yet powerful) idea –MAC protocol ●Reactive adversary –Fairness ●Adaptive adversary in multi-hop networks ●Application: Leader Election ●Other adversarial models ●Future work SIROCCO'13, Andrea Richa20

21. SIROCCO'13, Andrea Richa21 Simple (yet powerful) idea ●each node v sends a message at current time step with probability p v ≤ p max, for constant 0 < p max << 1. p = ∑ p v (aggregate probability) q idle = probability the channel is idle q succ = probability that only one node is transmitting (successful transmission) ●Claim. q idle. p ≤ q succ ≤ (q idle. p)/ (1- p max ) if (number of times the channel is idle) = (number of successful transmissions) p = θ(1) q succ = θ(1) ! (what we want!) ~

22. SIROCCO'13, Andrea Richa22 Basic approach ●a node v adapts p v based only on steps when an idle channel or a successful message transmission are observed, ignoring all other steps (including all the blocked steps when the adversary transmits!) steps jammed by adversary idle steps successful transmissions steps where collision occurred but no jamming time

23. SIROCCO'13, Andrea Richa23 Basic approach ●a node v adapts p v based only on steps when an idle channel or a successful message transmission are observed, ignoring all other steps (including all the blocked steps when the adversary transmits!)! steps jammed by adversary idle steps successful transmissions steps where collision occurred but no jamming time

24. SIROCCO'13, Andrea Richa24 Naïve protocol Each time step: ●Node v sends a message with probability p v. If v does not send a message then –if the wireless channel is idle then p v = (1+ γ ) p v –if v received a message then p v = p v /(1+ γ) (Recall that γ = O(1/(log T + loglog n)). )

25. SIROCCO'13, Andrea Richa25 Problems ●Basic problem: Aggregate probability p could be too large. –all time steps blocked due to message collisions w.h.p. steps jammed by adversary idle steps successful transmissions steps where collision occurred but no jamming time

26. SIROCCO'13, Andrea Richa26 Problems ●Basic problem: Cumulative probability p could be too large. –all time steps blocked due to message collisions w.h.p. steps jammed by adversary idle steps successful transmissions steps where collision occurred but no jamming time

27. SIROCCO'13, Andrea Richa27 Problems ●Basic problem: Cumulative probability p could be too large. –all time steps blocked due to message collisions w.h.p. ●Idea: If more than T consecutive time steps without successful transmissions (or idle time steps), then reduce probabilities, which results in fast recovery of p. ●Problem: Nodes do not know T. How to learn a good time window threshold? –It turns out that additive-increase additive-decrease is the right strategy!

28. SIROCCO'13, Andrea Richa28 MAC protocol ●each node v maintains –probability value p v, –time window threshold T v, and –counter c v ●Initially, T v = c v = 1 and p v = p max (< 1/24). ●synchronized time steps (for ease of explanation) ●Intuition: wait for an entire time window (according to current estimate T v ) until you can increase T v

29. SIROCCO'13, Andrea Richa29 MAC protocol In each step: ●node v sends a message with probability p v. If v decides not to send a message then –if v senses an idle channel, then p v = min{(1+ γ ) p v, p max } –if v successfully receives a message, then p v = p v /(1+ γ ) and T v = max{T v - 1, 1} ●c v = c v + 1. If c v > T v then –c v = 1 –if v did not receive a message successfully in the last T v steps then p v = p v /(1+ γ ) and T v = T v +1

30. SIROCCO'13, Andrea Richa30 Our results ●Let N = max {T,n} ●Theorem. Our MAC protocol is constant-competitive under any (T,1-ε)-bounded adversary if the protocol is executed for Ω(log N. max{T,log 3 N/(ε γ 2 )}/ ε) steps w.h.p., for any constant 0<ε<1 and any T.

31. SIROCCO'13, Andrea Richa31 Proof sketch ●Show competitiveness for time frames of F = θ( (log N. max{T,log 3 N/(ε γ 2 )}/ ε) many steps If we can show constant competitiveness for any such time frame of size F, the theorem follows ●Use induction over the number of sufficiently large time frames seen so far. We subdivide each frame: I I’ f = θ(max{T,log 3 N/(ε γ 2 )}) F = (log N / ε). f

32. SIROCCO'13, Andrea Richa32 Proof sketch ●p > 1/(f 2 (1+γ) 2√f ) and T v < √F, in each subframe I’ w.h.p. ●p 1/12 within subframe I’ with moderate probability (so that adaptive adversarial jamming not successful) ●Constant throughput in I’ with moderate probability ●Over a logarithmic number of subframes, constant throughput in frame I of size F w.h.p.

33. 33 Continuous jamming ●Moreover, under a more powerful adversary that can perform continuous jamming (after Ω(T) steps): ●Lemma. The total energy consumption (sending out messages) during an entire continuous jamming attack is O(√T), independent of the length of the attack. ●Exhaust adversary’s energy resources ~ ~ 33 SIROCCO'13, Andrea Richa

34. Overview ●Adaptive adversary –Single-hop scenario –Simple (yet powerful) idea –MAC protocol ●Reactive adversary –Fairness ●Adaptive adversary in multi-hop networks ●Application: Leader Election ●Other adversarial models ●Future work SIROCCO'13, Andrea Richa34

35. Reactive adversary ●[R.,Scheideler, Schmid, Zhang, ICDCS’11] ●Fully adaptive adversary that in addition can quickly observe the channel at the current time step, before deciding to jam –i.e., the adversary has some knowledge about the random choices at current time step –Distinguishes between idle and non-idle time steps, but cannot distinguish between successful transmissions and collisions (e.g., if packets are encrypted) SIROCCO'13, Andrea Richa35

36. AntiJam: Reactive jamming- resistant MAC protocol ●Need to “synchronize” transmission probabilities p v, as well as counters c v and T v –Piggyback p v, c v, T v to a message sent by v –Better understanding on how aggregate probability changes every time step –Achieve fairness for free (basically all nodes have the same transmission probability)! ●Once nodes are synchronized (plus some other smaller changes), one can show that the basic protocol is also robust against reactive adversaries SIROCCO'13, Andrea Richa36

37. 37 Our results Theorem. The AntiJam protocol achieves: ●fairness: the channel access probabilities among nodes do not differ by more than a factor of (1+γ) after the first message was sent successfully. ● e θ(1/ ε ) -competitiveness w.h.p., under any (T,1-ε)- bounded reactive adversary if the protocol is executed for Ω(T/ε) steps w.h.p., for any constant 0<ε<1 and any T (constant in throughput now depends on ε ) ~ 2 SIROCCO'13, Andrea Richa

38. 38 Proof sketch: Fairness ●Fact: –Right after u sends a message successfully along with the tuple (p u,c u,T u ), (p v, c v, T v ) = (p u / (1+ γ), c u,T u ) for all receiving nodes v, while the sending node values stay the same. In particular, for any time step t after a successful transmission by node u, (c v, T v ) = (c w, T w ) for all nodes v and w V –This implies that after a successful transmission, the access probabilities of any two nodes in the network will never differ by more than a factor in the future. SIROCCO'13, Andrea Richa

39. AntiJam: Throughput for ε = 0.5 ε = 0.5 39SIROCCO'13, Andrea Richa

40. AntiJam: Convergence Time 40SIROCCO'13, Andrea Richa

41. AntiJam: Fairness 41SIROCCO'13, Andrea Richa

42. AntiJam vs. Non-reactive protocol: Fairness 42SIROCCO'13, Andrea Richa

43. AntiJam vs 802.11 43SIROCCO'13, Andrea Richa

44. Overview ●Adaptive adversary –Single-hop scenario –Simple (yet powerful) idea –MAC protocol ●Reactive adversary –Fairness ●Adaptive adversary in multi-hop networks ●Application: Leader Election ●Other adversarial models ●Future work SIROCCO'13, Andrea Richa44

45. Multihop wireless networks SIROCCO'13, Andrea Richa45 Powerful jammer Physical interference Jammed

46. Signal-to-Interference-Noise- Ratio (SINR) SIROCCO'13, Andrea Richa46 ●A message sent by node u is received at node v iff - N: Gaussian variable for background noise - S: set of transmitting nodes -  : constant that depends on transmission scheme - d(x,y): Euclidean distance between x and y ●Well-accepted model (in theory, at least ) for physical interference P/d(u,v)  N +  w in S P/d(w,v)  > 

47. Multihop Adversarial Model ●(B,T)-bounded adaptive adversary: has an overall noise budget of BT that it can use to increase the noise level at node v and that it can distribute among the time steps as it likes. ●At any point in time, the adversary makes independent decisions for each node on whether to jam it (provided it does not exceed its noise budget over a window of size T). ●many noise phenomena can be covered under this model SIROCCO'13, Andrea Richa47

48. Throughput in multihop networks ●[Ogierman, R., Scheideler, Schmid, Zhang, 2013]: SINR model ●Also achieve constant throughput : Throughput = (Earlier, [R., Scheideler, Schmid, Zhang, DISC’10]: unit-disk graph model.) SIROCCO'13, Andrea Richa48

49. Overview ●Adaptive adversary –Single-hop scenario –Simple (yet powerful) idea –MAC protocol ●Reactive adversary –Fairness ●Adaptive adversary in multi-hop networks ●Application: Leader Election ●Other adversarial models ●Future work SIROCCO'13, Andrea Richa49

50. Leader Election in Adversarial (Single-hop) Networks ●[R., Scheideler, Schmid, Zhang, MobiHoc’11] ●Our goal: select a leader among the nodes ●Challenges: we may start in any state; there is adaptive adversary 50SIROCCO'13, Andrea Richa leader

51. 51 Self-stabilizing Leader Election ●Goal: design a self-stabilizing protocol that elects a single node as the leader, irrespective of the jamming activity ●Challenges: –a leader node should let the others (followers or other leaders) know that he is still around –the followers should be able to notice when there is no leader in the network SIROCCO'13, Andrea Richa

52. Leader Election Why is leader election difficult under an adaptive jammer? Example: exponential/polynomial backoff 0 time channel activity (expected) : jamming activity : messages constant success probability 52SIROCCO'13, Andrea Richa

53. Why is leader election difficult under an adaptive jammer? Example 1: exponential/polynomial backoff 0 time : jamming activity : messages constant success probability channel activity (expected) 53SIROCCO'13, Andrea Richa

54. Why is leader election difficult under an adaptive jammer? Example 2: reserved leader slot to notify nodes about leader 0 time channel activity (expected) : jamming activity : leader message 54SIROCCO'13, Andrea Richa

55. Why is leader election difficult under an adaptive jammer? Example 2: reserved leader slot to notify nodes about leader 0 time channel activity (expected) : jamming activity : leader message 55SIROCCO'13, Andrea Richa

56. Other adversarial modeling in wireless networks ●Adversary: used to model external world ●More bening: –Control packet injection rates –Control mobility ●Intentionally disruptive: –jammers ●More disruptive: malicious adversaries –Undermine security –Control Byzantine nodes (introduce fake messages) SIROCCO'13, Andrea Richa56

57. Other adversarial modeling in wireless networks ●Adversarial packet injection/queueing: –[Chlebus, Kowalski, Rokicki, PODC’06], [Andrews, Jung, Stolyar, STOC’07], [Anantharamu, Chlebus, Rokicki, OPODIS’09], [Chlebus, Kowalski, Rokicki, Distributed Computing’09], [Lim, Jung, Andrews, INFOCOM’12] ●Multi-channel access with adversarial jamming: –[Dolev, Gilbert, Guerraoui, Newport, DISC’07], [Anantharamu, Chlebus, Kowalski, Rokicki, SIROCCO’11], [Dolev,Gilbert, Khabbazian, Newport, DISC’11], [Daum, Gilbert, Kuhn, Newport, PODC’12], [Ghaffari, Gilbert, Newport, Tan, OPODIS’12] SIROCCO'13, Andrea Richa57

58. Other adversarial modeling in wireless networks ●Broadcasting\Gossiping with adversarial jamming: –[Dolev, Gilbert, Guerraoui, Newport, DISC’07], [Dolev,Gilbert, Khabbazian, Newport, DISC’11], [Daum, Gilbert, Kuhn, Newport, PODC’12], [Ghaffari, Gilbert, Newport, Tan, OPODIS’12] ●Capacity Maximization with adversarial jamming: [Dams, Hoefer, Kesselheim, unpublished] ●Malicious adversary: –[Dolev, Gilbert, Guerraoui, Newport, DISC’07], [Gilbert, Young, PODC’12] ●Infection spreading with adversarial mobility: [Wang,Krishnamachari, ] ●Etc. SIROCCO'13, Andrea Richa58

59. 59 Future work: Adversarial Jamming ●Jamming-resistant protocols with power control: –Increasing power increases chance that signal will overcome jamming activity, however… –Increasing power also generates more interference… –Also adapt noise threshold level? ●How about reactive jammers in multihop environments, under SINR? ●Can the protocols be modified so that no rough bound on n and T are required? –stochastic/oblivious jammers: Simpler to handle? E.g., a constant gamma seems to work fine here. ●Other applications of the MAC protocol (e.g., broadcast)? SIROCCO'13, Andrea Richa

60. Future Work ●What would be your application of an adversary in wireless communication? SIROCCO'13, Andrea Richa60

61. Collaborators ●Baruch Awerbuch (John Hopkins); Stefan Schmid (TU Berlin\Telekom Labs); Christian Scheideler and Adrian Ogierman (U. of Paderborn); Jin Zhang (Google) ●Papers available from my webpage (for recent – and maybe not so recent -- submissions, please send me email) at www.public.asu.edu/~aricha aricha@asu.eduwww.public.asu.edu/~aricha SIROCCO'13, Andrea Richa61

62. SIROCCO'13, Andrea Richa62 Thank you! Questions?

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