Resiliency of Wireless Sensor Networks: Definitions and Analyses

Resiliency of Wireless Sensor

Networks: Definitions and

Analyses

Orange Labs & CITI Labs INSA-Lyon

O.Erdene-Ochir, M. Minier, F. Valois, A. Kountouris February 10, 2010, presentation to CITI seminar

Thesis context

•

Research area: Sensor Networking (routing in particular)

Focus: Security beyond cryptography (protocol resiliency)

–

Our goal: Analyze and create inherently resilient protocols

against internal (insider) attacks

•

CRE between

–

Orange Labs (TECH/MATIS/CITY) and

–

CITI Laboratory of INSA-Lyon (ANR VERSO ARESA2)

•

Advisors (academic): M. Minier, F. Valois

Advisor (Orange Labs): A. Kountouris

Contents



Context

Motivation



Related works



Simulation and analysis

Conclusion and future

directions

Worldsens, a small sensor node developed in the CITI lab

Context: Wireless Sensor Networks

• Why sensor networks ? –Rapid deployment

–Cheap

–Self organized

–Fault-tolerant

Wireless Sensor Networks • Applications of WSNs: – scientific data collection – military applications – environmental monitoring (temperature, pollution, pressure…) – home, building, industrial automation (electricity, water metering…) • Challenges – Scalability – Adaptability

Motivations (1/2)

•

Why not use traditional cryptography-based security ?

–

limited resources (memory, energy, computation power …)

–

an open and hostile environment (physical attacks)

–

not always a solution against multiple internal attacks

stemming from node compromise

Our goal: Analyze and create inherently resilient protocols against

internal (insider) attacks

Our definition:

Resiliency

is the ability of a network to continue to

operate in presence of

k

compromised nodes, i.e. the capacity of a

network to endure and overcome internal (insider) attacks.

Motivations (2/2)

Definition of

Survivability

[ELLM1999]

:

Survivability in information systems is defined as the ability of the

network computing system to provide essential services in the

presence of attacks and/or failures, and recover full service in a

timely manner.

Definition of

Robustness

[SKHJ2002]

:

Robustness is defined as the requirement to accommodate

hardware and software failures, asymmetric and unidirectional

links, or limited range of wireless communication.

[KW2003], [WS2002]

•

Hardware

attacks (node compromise) [BBD2006]

•

Physical

layer attacks

–

Jamming [WSS2003]

•

Link

layer attacks

–

Collision

–

Exhaustion

–

Link layer jamming [LPHDHH2009]

•

Routing

layer attacks

–

Sybil [NSSP2004]

–

Node replication [PPG2005]

–

Selective forwarding

–

Blackhole

–

Sinkhole

–

Wormhole [HE2004], [HPJ2003]

Related works: Attacks and Defenses (2/3)

•

Routing

layer attacks

–

Sybil [NSSP2004]

–

Node replication [PPG2005]

Related works: Attacks and Defenses (3/3)

•

Routing

layer attacks

–

Blackhole

–

Sinkhole

Related works: Routing layer security (1/5)

•

Goal

:

find a route between source

and destination

•

Routing layer responsibility:

–

Naming and addressing

–

Neighborhood discovery

–

Multi-hop routing

•

Specific secure protocols:

–

SRP [PH2002]

–

ARIADNE [HPJ2005]

–

ARAN [SDLSB2002]

–

SPINS (SNEP+μTESLA)

[PSW2001] …



Use cryptography

Related works: WSN routing protocols (2/5)



Multi-hop routing

–

different ways to find the route

–

message traverse many hops

–

intermediate nodes can be compromised

Study of existing routing protocols

–

enumerate the various routing mechanisms

–

classification is required for efficient choice

–

analysis of some routing protocols under multiple attacks

Related works: Choice of routing protocols

(4/5)

•

Dynamic source routing [JM1996]

–

Flooding based

Route discovery

•

Gradient based routing [MS2001]

–

Flooding based

Gradient setup

Greedy forwarding [KK2000]

Geographical

Location information

required

•

Random walk routing [SB2002]

–

Probabilistic routing

•

DATA packet oriented attacks

–

Selective forwarding

–

Sinkhole

•

CONTROL packet oriented

attacks

–

Blackhole

•

HELLO packet oriented attacks

–

Sybil



Simulator:

WSNet

[HCG2008]

http://wsnet.gforge.inria.fr

Assumptions:

–

Sensors can be

compromised

–

A unique sink at the

center of the network

–

Sensor nodes are

static

–

Ideal MAC/PHY: no

interferences, no

collisions, (consider

only impact of

Simulations and analysis (1/8)

Parameter

Value

Number of nodes

300

Area size

100X100m

Transmission

range

20m

Topology tested

Uniformly and

randomly

distributed

Traffic generation Poisson

distribution

with λ = 1 packet

per sec, per node

Simulations and analysis (2/8)

•

We tested three different evaluation metrics:

–

Average delivery ratio:

•

success of routing function (reliability )

•

percentage of successfully received packets

–

Average degree of nodes:

•

detect neighborhood abnormalities

•

average number of neighbors

–

Average path length:

Simulations and analysis (3/8)

Case 1:

•

10% compromised nodes of

300 are

uniformly

and

randomly distributed across

the

whole network

Case 2:

•

10% compromised nodes of

300 are

uniformly

and

randomly distributed

around

the sink

Simulations and analysis (4/8)

Scenario 1:

• Uniformly distributed across the whole network (case 1)

• Selective forwarding (drop all DATA packets)

Scenario 2:

• Uniformly distributed around the sink

(case 2)

• Sinkhole attack (drop all DATA packets)

• Impact of attacks is more important than scenario 1

• Average delivery ration decreases when percentage of compromised

Simulations and analysis (5/8)

Scenario 1:

• Uniformly distributed across the whole network (case 1)

• Selective forwarding (drop all DATA packets)

• When path length is high, the number of intermediate

Scenario 2:

• Uniformly distributed around the sink

(case 2)

• Sinkhole attack (drop all DATA packets)

Simulations and analysis (6/8)

Scenario 1:

• Uniformly distributed across the whole network (case 1) • Selective forwarding (drop all DATA packets)

• Double sent of each DATA packet

Simulations and analysis (7/8)

Scenario 3 :

• Uniformly distributed across the whole network (case 1) • Sybil attack (false HELLO packets, multiple identities)

Simulations and analysis (8/8)

Scenario 4 :

• Uniformly distributed across the whole network (case 1) • Blackhole attack (false CONTROL packets, attract the DATA

traffic)

• Impact of attacks is much more important than in previous attacks

Conclusion and future directions

•

Preliminary study for WSNs security of the routing layer.

•

The more the protocol is statefull, the more it will be vulnerable

to attacks targeting this information.

•

Requirements for Resiliency :

–

Graph representing WSNs should be connected (reliability)

–

Degree of the nodes must be high (increases the number of

candidates for next hop)

–

Route must be diversified in order to exploit the structural

redundancy (randomness on their behavior)

–

Redundant sent of packets

•

In the future,

–

Extending our simulations; taking into account energy

consumption (tradeoff energy consuming-resiliency)

–

Quantify a measure of resiliency: which metric?

References

[KW2003] C. Karlof and D. Wagner, “Secure routing in wireless sensor networks:

attacks and countermeasures,” Ad Hoc Networks, vol. 1, no. 2-3, pp. 293– 315, August 2003.

[WS2002] Anthony D. Wood and John A. Stankovic. Denial of service in sensor

networks. Computer, 35(10):54_62, 2002.

[BBD2006] Alexander Becher, Zinaida Benenson, and Maximillian Dornseif. Tampering

with motes: Real-world attacks on wireless sensor networks. In Sicherheit, pages 26_29, 2006.

[WSS2003] Anthony D. Wood, John A. Stankovic, and Sang H. Son. Jam: A jammed-area

mapping service for sensor networks. In 24th IEEE Real-Time Systems Symposium, pages 286_297, 2003.

[HE2004] L. Hu and D. Evans, “Using directional antennas to prevent wormhole

attacks,” in Network and Distributed System Security Symposium. San Diego, USA: The Internet Society, February 2004, pp. 1–11.

[HPJ2003] Y.-C. Hu, A. Perrig, and D. B. Johnson, “Packet leashes: A defense against wormhole attacks in wireless networks,” in 22nd Annual Joint Conference of the IEEE Computer and Communications Societies, San Fransisco, USA, April 2003, pp. 1976–1986.

[LPHDHH2009] Yee Wei Law, Marimuthu Palaniswami, Lodewijk Van Hoesel, Jeroen Doumen,

Pieter Hartel, and Paul Havinga. Energy-efficient link-layer jamming attacks against wireless sensor network mac protocols. ACM Trans. Sen. Netw., 5(1):1_38, 2009.

References

[PPG2005] B. Parno, A. Perrig, and V. Gligor, “Distributed detection of node replication attacks in sensor networks,” in IEEE Symposium on Security and Privacy. Oakland, USA: IEEE Computer Society, May 2005, pp. 49–63.

[JM1996] D. B. Johnson and D. A. Maltz, “Dynamic source routing in ad hoc wireless

networks,” in Mobile Computing, S. US, Ed., vol. 353, 1996, pp. 153–181. [MS2001] C. S. Mani and M. B. Srivastava, “Energy efficient routing in wireless sensor

networks,” in Military Communications Conference roceedings on

Communications for Network-Centric Operations: Creating the Information Force, vol. 1, McLean, USA, October 2001, pp. 357–361.

[KK2000] B. Karp and H. T. Kung, “Gpsr: greedy perimeter stateless routing for

wireless networks,” in Proceedings of the 6th annual international

conference on Mobile computing and networking, Boston, USA, August 2000, pp. 243–254.

[SB2002] S. D. Servetto and G. Barrenechea, “Constrained random walks on random

graphs: routing algorithms for large scale wireless sensor networks,” in Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications, Atlanta, USA, September 2002, pp. 12–21.

[HCG2008] E. Hamida, G. Chelius, and J.-M. Gorce, “Scalable versus accurate physical layer modeling in wireless network simulations,” in 22nd _{Workshop on}

References

[PH2002] P. Papadimitratos and Z. Haas, “Secure rotuing for mobile ad hoc networks,”

in Communication Networks and Distributed Systems Modeling and Simulation Conference, San Antonio, Texas, 2002, pp. 27–31.

[HPJ2005] Y. C. Hu, A. Perrig, and D. B. Johnson, “Ariadne: a secure on-demand routing protocol for ad hoc networks,” Wireless Networks, vol. 11, no. 1-2, pp. 21– 38, January 2005.

[SDLSB2002] K. Sanzgiri, B.Dahill, B. N. Levine, C. Shields, and E. M. Belding-Royer, “A secure routing protocol for ad hoc networks,” in IEEE International

Conference on Network Protocols. Paris, France: IEEE Computer Society, November 2002, pp. 78–89.

[PSW2001] A. Perrig, R. Szewczyk, V. Wen, D. E. Culler, and J. D. Tygar, “Spins: security protocols for sensor netowrks,” in Seventh Annual International Conference on Mobile Computing and Networks, Rome, Italy, July 2001, pp. 189–199. [ELLM1999] R. J. Ellison, R. C. Linger, T. Longstaff, and N. R. Mead, “Survivable network

system analysis: A case study,” IEEE Software, vol. 16, no. 4, pp. 70–77, July 1999.

[SKHJ2002] J. P. G. Sterbenz, R. Krishnan, R. Hain, A. Jackson, D. Levin, R. Ramanathan, and J. Zao, “Survivable mobile wireless networks: issues, challenges, and