Secure Localization Algorithms
for Wireless Sensor Networks
proposed by A. Boukerche, H. Oliveira, E. Nakamura, and A. Loureiro
(2008)
Maria Berenice Carrasco
Outline
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Motivation (from two perspectives)
Secure Localization
– Overview
– Known attacks
– Solutions
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Location Verification
Design considerations
Conclusions
Motivation
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Why is Localization important?
– Popularity of wireless sensor networks (WSN)
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Hostile environments
Monitoring & control applications
– Military fields, monitoring of structures, etc.
– The knowledge of sensor’s locations is required by
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Applications : Data fusion
– Locations and timestamps
Other communication protocols
– Routing, location-based authentication.etc.
Motivation
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Why is Security important?
– Vulnerability of WSN
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Remote environments
Broadcast nature of the channel
– What an attacker can potentially do?
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Physical manipulation
Jamming
Injecting code
GOAL: Make the node think it is
somewhere different from actual
location
– As a result…
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Wrong results: wrong decisions
Secure Localization
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Goal: To guarantee correctness despite of the
presence of intruders
Network model:
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Beacons: GPS or manual configuration
Common nodes: requesting
Relative
Localization
Classification:
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Range-based localization: Distance
Range-free localization: No connectivity information
Node-centric
Infrastructure-centric: BS, CA
Secure Localization
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General Process has two phases:
1. Information Collection: distance/angle measure
– # of hops, RSSI, ToA, AoA
Range-free ignores this phase
2. Location Computation: include reference points
Triangulation
Trilateration
Secure Localization
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Known Attacks
– Consider an insider Vs. an outsider
– Reply attack
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Jams the transmission
Waits (extra delay)
Replays the same packet pretending
to be the sender
Inaccurate location estimation
Secure Localization
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Known Attacks
– Range-change attack
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Special case of the Replay attack
Increase/decrease range measurements
– Impersonation
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Victims: mostly beacon nodes
– Sybil attack
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Claims multiple identities
Secure Localization
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Known Attacks
– Wormhole attack
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Tunnel
Jams packets
Replays packets through this tunnel
Secure Localization
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Solutions
– Cryptography
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Against impersonation and data corruption
Use of :
– Authentication
» Verify the sender
– Data integrity
» Data is unchanged
» Example: distance bounding (based on SEAD)
Secure Localization
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Solutions
– Cryptography (continued)
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Symmetric cryptography
– Common private key
– WSN are resource-constrained
Pre-deployed keys
Functions to derive keys: Storage Complexity
Compromised nodes defeat this mechanism
Secure Localization
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Solutions
– Misbehavior Detection and Block
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Against compromised nodes
Observe behavior of nodes
Detect and revoke misbehaving nodes
Some techniques
– RTT observation between two neighbors
» Assumption: extra delay of a replay attack
– Reputation-based mechanism
» Beacon monitors its neighborhood -> table
Secure Localization
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Solutions
– Robust Position Computation
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Filter erroneous information during computation
Assumption: Good nodes > Malicious nodes
Statistical techniques
– Least Squares Method
Location Verification
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BS also learn sensors’ locations
– Data Aggregation
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Must verify the location claimed is correct
– Did the event really happened there?
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An approach: The Echo Protocol
– Check if the node is inside the claimed region
– Two types of nodes: p (prover) and v (verifier)
– Consider c (speed of light) and s (speed of sound)
Location Verification
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An approach: The Echo Protocol (continued)
– Intuition (Simple Case)
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v only verifies provers inside R
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If p is able to return the packet in sufficient time, then v
is sure that p is within d(v,l) meters of v
Otherwise: p is further away or processing delay
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Design Considerations
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No system is totally safe
– Network model & adversary model
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Level of security Vs. Available resources
– Particular application
– Range-based :
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Distance bounding: HW with nanosecond precision
– Asymmetric cryptography
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More robust but energy consuming
Design Considerations
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Who initiates the secure localization process?
– On-demand
– Periodic process
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Useful domain for an intruder
– Use only beacon nodes
– Use beacon nodes and also nodes with known
positions as reference points
Conclusions
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It is not feasible to use tamper-resistant
hardware
– Low cost of sensor nodes
– Massive deployment
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Trade-off required
– Accuracy demanded by the application
– Available resources
– Environment
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Combination of techniques is desirable