Prof. J.-P. Hubaux

Mobile Networks

Module I – Part 2Securing Vehicular Networks

1

Outline

Motivation

Threat model and specific attacks

Security architecture

Security analysis

Certificate revocation

Data-centric trust

Conclusion

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What is a VANET(Vehicular Ad hoc NETwork)?

Roadside base station

Inter-vehicle communications

Vehicle-to-roadside communications

Emergency event

• Communication: typically over the

Dedicated Short Range Communications (DSRC) (5.9 GHz)

• Example of protocol: IEEE 802.11p

• Penetration will be progressive (over 2 decades or so)3

Vehicular communications: why?

Combat the awful side-effects of road traffic• In the EU, around 40’000 people die yearly on the roads;

more than 1.5 millions are injured

• Traffic jams generate a tremendous waste of time and of fuel

Most of these problems can be solved by providing appropriate information to the driver or to the vehicle

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Why is VANET security important?

Large projects have explored vehicular communications: Fleetnet, PATH (UC Berkeley),…

No solution can be deployed if not properly secured

The problem is non-trivial

• Specific requirements (speed, real-time constraints)

• Contradictory expectations

Industry front: standards are still under development and suffer from serious weaknesses

• IEEE P1609.2: Standard for Wireless Access in Vehicular Environments - Security Services for Applications and Management Messages

Research front

• A growing number of papers

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A modern vehicle

F o r w a r d r a d a r

C o m p u t i n g p l a t f o r m

E v e n t d a t a r e c o r d e r ( E D R )

P o s i t i o n i n g s y s t e m

R e a r r a d a r

C o m m u n i c a t i o n f a c i l i t y

D i s p l a y

(GPS)

Human-Machine Interface

A modern vehicle is a network of sensors/actuators on wheels !A modern vehicle is a network of sensors/actuators on wheels !

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Threat model

An attacker can be:

• Insider / Outsider

• Malicious / Rational

• Active / Passive

• Local / Extended

Attacks can be mounted on:

• Safety-related applications

• Traffic optimization applications

• Payment-based applications

• Privacy

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Attack 1 : Bogus traffic information

Traffic jam

ahead

Attacker: insider, rational, active8

Attack 2 : Generate “Intelligent Collisions”

SLOW DOWN

The way is clear

Attacker: insider, malicious, active9

Attack 3: Cheating with identity, speed, or position

Wasn’t me!

Attacker: insider, rational, active10

Attack 4: Jamming

Roadside base station

Jammer

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Attack 5: Tunnel

Physical tunnel or jammed area

Wrong information

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Attack 6: Tracking

A

* A at (x1,y1,z1)at time t1

* A communicates with B

* A refuels at time t2 and location

(x2,y2,z2)

1

2

AB

A

* A enters the parking lot at time

t3* A downloads from server X

3

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Our scope

We consider communications specific to road traffic:

safety and traffic optimization

• Safety-related messages

• Messages related to traffic information

We do not focus on more generic applications,

e.g., toll collect, access to audio/video files, games,…

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Security system requirements

Sender authentication

Verification of data consistency

Availability

Non-repudiation

Privacy

Real-time constraints

15

Security Architecture

16

Tamper-proof device

Each vehicle carries a tamper-proof device• Contains the secrets of the vehicle itself

• Has its own battery

• Has its own clock (notably in order to be able to sign timestamps)

• Is in charge of all security operations

• Is accessible only by authorized personnel

Tamper-proof device

Vehicle sensors(GPS, speed and acceleration,…)

On-boardCPU

Transmissionsystem

((( )))

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Digital signatures

Symmetric cryptography is not suitable: messages are

standalone, large scale, non-repudiation requirement

Hence each message should be signed with a DS

Liability-related messages should be stored in the EDR

Verifier

Signer

VerifierVerifier Safety message

Cryptographic material

{Position, speed, acceleration, direction,

time, safety events}

{Signer’s DS, Signer’s PK, CA’s certificate of PK}

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VPKI (Vehicular PKI)

A

B

PKI

Security servicesPositioning

ConfidentialityPrivacy

...

CA

PA PB

AuthenticationAuthentication

Shared session key

Each vehicle carries in its Tamper-Proof Device (TPD):

• A unique and certified identity: Electronic License Plate (ELP)

• A set of certified anonymous public/private key pairs

Mutual authentication can be done without involving a server

Authorities (national or regional) are cross-certified 19

The CA hierarchy: two options

Country 1

Region 1 Region 2

District 1 District 2

Car A Car B Car A Car B

Manuf. 1 Manuf. 2

1. Governmental Transportation Authorities

2. Manufacturers

The governments control certification

Long certificate chain

Keys should be recertified on borders to ensure mutual certification

Vehicle manufacturers are trusted

Only one certificate is needed

Each car has to store the keys of all vehicle manufacturers

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Secure VC Building Blocks Authorities

• Trusted entities issuing and managing identities and credentials

21

Secure VC Building Blocks

Authorities• Hierarchical organization

• ‘Forest’

22

Secure VC Building Blocks (cont’d)

Roadside Unit

‘Re-filling’ with or obtaining new

credentials

Providing revocation information

Roadside Unit

Wire-lineConnections

Identity and Credentials Management

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Anonymous keys

Preserve identity and location privacy

Keys can be preloaded at periodic checkups

The certificate of V’s ith key:

Keys renewal algorithm according to vehicle speed

(e.g., ≈ 1 min at 100 km/h)

Anonymity is conditional on the scenario

The authorization to link keys with ELPs is distributed

CAiSKiiV IDPuKSigPuKPuKCertCA

||

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What about privacy: how to avoid the Big Brother syndrome?

At 3:00- Vehicle A spotted at position P1

At 3:15- Vehicle A spotted at position P2

Keys change over time

Liability has to be enforced

Only law enforcement agencies should be allowed to retrieve the real identities of vehicles (and drivers) 25

DoS resilience

Vehicles will probably have several wireless technologies onboard

In most of them, several channels can be used To thwart DoS, vehicles can switch channels or

communication technologies

In the worst case, the system can be deactivated

Network layer

DSRC UTRA-TDD Bluetooth Other

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Data verification by correlation

Bogus info attack relies on false data

Authenticated vehicles can also send wrong data (on purpose or not)

The correctness of the data should be verified => data-centric trust

Correlation can help

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Security analysis

How much can we secure VANETs?

Messages are authenticated by their signatures

Authentication protects the network from outsiders

Correlation and fast revocation reinforce correctness

Availability remains a problem that can be alleviated

Non-repudiation is achieved because:

• ELP and anonymous keys are specific to one vehicle

• Position is correct if secure positioning is in place

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Certificate revocation in VANETs

The CA has to revoke invalid certificates:

• Compromised keys

• Wrongly issued certificates

• A vehicle constantly sends erroneous information

Using Certificate Revocation Lists (CRL) or online status

checking is not appropriate

There is a need to detect and revoke attackers fast

29

System model

There is a CA (Certification Authority)

Each vehicle has a public/private key pair, a TC (Trusted Component = TPD), and an EDR (Event Data Recorder)

Safety messages:• Are broadcast and signed

• Include time and position

Several possible communication channels:• DSRC

• Cellular

• WiMax

• Low-speed FM30

Adversary model

The adversary can be:

• Faulty node

• Misbehaving node

Example attack: false information dissemination

Adversaries have valid credentials

Honest majority in the attacker’s neighborhood

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Message validation

TPD(Tamper-Proof Device)

RTC(Rev. of the

Trusted Component )

LEAVE(Local Eviction of Attackers by Voting Evaluators)

MDS(Misbehavior Detection System)

Evidence Collection

Revocation Information

CA (Certification Authority) and Infrastructure Functionality

Fail(ID)

Revocation Decision

RC2RL(Rev. by Compressed

CRLs)

Node ID

Vehicle Functionality

CA PoliciesLocal Warning

Messages

Revocation Command

Scheme overview

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Revocation protocols

We propose 2 protocols to revoke a vehicle’s keys:

• Rev. of the Trusted Component (RTC): CA revokes all keys

• Rev. by Compressed CRLs (RC2RL): if TC is not reachable

Local Eviction of Attackers by Voting Evaluators

(LEAVE):

• Initiated by peers

• Generates a report to the CA, which triggers the actual

revocation by RTC/RC2RL

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Revocation of the Trusted Component (RTC)

34RSU: Road Side Unit; PuK = Public Key; T = Timestamp

Revocation by Compressed CRLs (RC2RL)

CRLs are compressed using Bloom filters

Bloom filter: space-efficient probabilistic data-structure• Can be queried to check if an element is in a set or not

• Configurable rate of false positives (but no false negatives)

1 2 3 m

vector with m bits

element “a”k different hash functionswith range 1…m

…

H1(a) H2(a) Hk(a)…

111 0 0 000 0 0

35

Local Eviction of Attackers by Voting Evaluators(LEAVE)

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Data-Centric Trust

37

Data Trust

Decision on event

What is Data-Centric Trust?

Data-Centric Trust in Networks

Packet forwarding

Security associations

Reputation

AM

B

Data dissemination

Insufficient

Hard

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Traditional ad hoc networks

Ephemeral networks

Data Trust = Entity Trust Data Trust = F(Entity Trust, context)

Event-specific trust

Dynamic trust metricSecurity status

)),(( jkvf ),( jkl v )( kvs

)),(),),((),(( jkljkk vvfvsF

AC

B

M

General FrameworkTrust Computation

Weights (data-centric trust levels)

( )kv is the default trustworthiness

LocationTime

Event reports of type

from nodes jkv

jke

AC

B

M

General FrameworkEvidence Evaluation

( )jBF e

Decision Logic

Decision on Reported Event

Report contents

Event reportsof type

from nodes jkv

jke

( )jCF e ( )jMF e

Decision Logics

Most trusted report

Weighted voting

Bayesian inference• Takes into account prior knowledge

Dempster-Shafer Theory• probability is bounded by belief and plausibility

• Uncertainty (lack of evidence) does not refute nor support evidence

Conclusion

Vehicular communications could lead to the largest mobile ad hoc network (around 1 billion nodes)

The security of that network is a difficult and highly relevant problem Car manufacturers seem to be poised to massively invest in this area Slow penetration makes connectivity more difficult Security leads to a substantial overhead and must be taken into

account from the beginning of the design process The field offers plenty of novel research challenges Pitfalls

• Defer the design of security

• Security by obscurity

More information at http://ivc.epfl.ch

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