Extending OMNeT++ Simulator to Secure Vehicular Communication

under Blackhole Attack

Gerardo Mario Marotta and Floriano De Rango

Institute DIMES Dept., University of Calabria, Via P. Bucci, Rende (CS), Italy

Keywords: VANET, Security, OMNeT++, Black-hole Attack, Vehicular Communications.

Abstract: Vehicular Ad Hoc Networks (VANET) are gaining a lot of interest in these last years. Connected and

autonomous vehicles are becoming a reality and security aspects need to be considered in the vehicle’s

communication and architecture in order to support critical services. In this paper, an additional security

module has been proposed and added in OMNeT++ to support security features in vehicle communications.

Cryptography and authentication services have been introduced to protect VANET by black-hole attacks.

Some attack scenarios have been considered and security features have been proposed to mitigate or avoid

these security attacks. Security features increase a little bit the protocol overhead, but they are able to maintain

good performance under attack scenario. Performance evaluation has been led out considering as metrics the

number of dropped packets, number of sent packets and the end-to-end delay.

1 INTRODUCTION

VANET (Vehicular Ad-Hoc Network) is a kind of

Mobile Ad-Hoc Networks (MANETs) where the

nodes involved in the communication are vehicles.

The messages exchanged among the vehicles concern

accidents on roads, roadblocks, speed control,

unrestricted way for ambulances and concealed

obstacles etc.

The importance of exchanged data makes

VANET security a primary aspect in this scope.

VANET is prone to several vulnerabilities and

attacks. These vulnerabilities deteriorate the

functioning of the network, introducing severe

problems in the network and pose potential security

threats. The danger of attacks is linked to the purpose

of the attack and its impact on the victim.

An attacker in vehicular network could steal,

modify or drop the end-user personal information

transmitted in the network, compromising

confidentiality, integrity, authentication and

availability. Security is a critical issues in many field

such as emphasized in (Fazio et al., 2020)(De Rango

et al., 2020)( M.Mehic, 2016),(De Rango et al.,

2006)( F. Rezac, 2011). However, VANET and

autonomous vehicles can increase the importance of

https://orcid.org/0000-0002-3882-1678

the security considering the possible consequence

that a security attack can determine. The vast

vehicular set and the rapid change in the position

increase the complexity for securing the vehicular

networks. (Arif et al., 2019).

Routing protocols (Singh et al., 2020) are parts of

VANET scenarios interested by security threats.

Thus, vehicles in VANET work like routers for

transmitting data between nodes. Malicious node

could lead to various attacks, such as Black Hole.

Simulation frameworks do not offer features to

implement security solutions to VANET’s attacks.

The main contribution of this paper is to integrate

OMNeT++ simulator with Crypto++ library to

evaluate some security mitigations introduced to stem

Black Hole attack in VANET context.

Sumo has been used to realize traffic simulation,

whereas Veins allows the communication between

the previous frameworks.

The paper is organized as follows: section 2

presents some works related to routing over VANET;

section 3 presents the tools used to implement the

attacks and the mitigations, and to evaluate them;

section 4 describes mitigations’ details; section 5

shows the results collected during the simulations

and, finally, conclusions are summarized in the last

section.

378

Marotta, G. and De Rango, F.

Extending OMNeT++ Simulator to Secure Vehicular Communication under Blackhole Attack.

DOI: 10.5220/0010568703780385

In Proceedings of the 11th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2021), pages 378-385

ISBN: 978-989-758-528-9

2 RELATED WORK

In this section some works related to routing over

VANET and security issues in the reference context

are presented.

2.1 VANET Routing

Routing protocols applied in VANET gained a lot of

interests in these last years, especially, considering

the specific characteristics of VANET technologies

such as high and constrained mobility, not energy

limited nodes and partial infrastructure that is

possible to use. A lot of work has been done in the

MANET context regarding dynamic and efficient

routing. Some protocols applied in MANET could be

applied with some modifications and extensions also

to the VANET. In particular, for the specific case, we

have to consider that routing strategies need to

quickly discover the path from source to destination

considering the frequent route breakage that can

happen in a highly dynamic scenario. Moreover, it is

suitable to not maintain always updated the topology

if there is not traffic between vehicles. Many routing

strategies have been proposed for VANET and they

are classified in two main macro-categories

(Devangavi and Gupta, 2017):

 topology driven routing;

 location-based routing.

The first one uses the network state info and

routing protocols build a table where IP addresses of

nodes, next hop node and path metric are considered.

The second category, instead, uses node location or

geographic area to decide where to forward data

packets and no network topology is maintained

among nodes. The first category has been extensively

applied in VANET because many of table-driven

protocols have been standardized and are well-known

in literature. Table-driven routing can be furtherly

classified in two categories (Hayat et al., 2019):

 proactive: they maintain periodically the

routing table through a continuous protocol

packet exchange.

 reactive: they create a route only when there

are data to transmit among vehicles. This

approach tries to avoid to overload the network

of control packets even in situation where there

is no data traffic.

 hybrid: they use both techniques presented

above combining in some part of the network a

proactive approach and in other part pf the

network the reactive strategy.

In our case we focused on a well know reactive

protocol such as presented in (Santamaria et al, 2019).

However, we considered some possible security

threats that is present in the classical AODV version.

2.1.1 AODV Protocol

AODV (Perkins et al., 2003) is an on-demand table-

driven routing protocol. It makes use of three routing

protocol packets such as referred below:

 Route Request (RREQ)

 Route Reply (RREP)

 Route Error (RERR)

The path is discovered only when the source has data

to send. AODV is composed by two phases:

 Route Discovery: it is started when the source

has data to send towards the destination;

 Route Maintenance: it is applied where there

is a route breakage in order to remove broken

link and start again the route discovery.

AODV uses the minimum hop count as path

metric and it uses source and destination sequence

number to avoid loop formation in the network. The

RREQ is the message generated by source to discover

the path toward the destination and it includes the

source sequence number. Typically, this sequence

number is incremented by one for each new RRE

generated by the source. When the RREQ arrives at

the destination, a RREP is generated and forwarded

on the reverse path forwarding. The RREP carries the

destination sequence number set as the maximum

between the DSN (Destination Sequence Number)

included in the RREQ and the value maintained in the

node routing table. Every node associates a sequence

number to each destination in order to maintain

always updated the route. The higher destination

value means a more recent info. Manipulating the

DSN value can affect the network performance and it

is possible to perform some network attacks.

2.2 Security Attacks over VANET

A VANET is a network where it is possible to apply

attacks similar to those applied in MANET context.

In the following some possible attacks are recalled

and a focus on the blackhole considered in this work

has been also presented.

2.2.1 Attacks Classification

It is possible to see different network attack types

over VANET (Phull and Singh, 2019):

Extending OMNeT++ Simulator to Secure Vehicular Communication under Blackhole Attack

379

 Network Attack (NA): they have the target to

limit or block the network resources such as

bandwidth, transmission opportunity;

 Application Attack (AA): it has the objective to

change the content of messages at application

layer in order to create accidents or congestion.

 Timing Attack (TA): it consists in the time slot

modification to produce a transmission delay.

 Monitoring Attack (MA): they make use of

monitoring system to violate the secret of

messages exchanged in V2I and V2V way.

On the basis of the attack classes it is possible to

consider different kinds of attackers (Goyal et al.,

2019):

1. Active: attacker is hided in the network with the

objective to manipulate messages of legacy

users;

2. Passive: it can act without modifying messages

but sniffing or monitoring packets exchanged

among legacy users;

3. Internal: attacker authenticated and authorized

in the network that can change its behavior to

produce damages knowing some specific

network vulnerability;

4. External: it can act externally to the network

performing attacks to limit network resources

or discover secret keys;

5. Rational: external or internal entity that

performs active attack to obtain specific

benefits;

6. Malicious: external or internal entity

performing attacks to produce damage on the

network.

2.2.2 Black Hole Attack in VANET

AODV (Ad-hoc On-demand Distance Vector) is one

of routing protocols that has been applied in the

VANET context. It is proactive and on-demand and it

can work under dynamic conditions such as vehicles

moving in an urban or sub-urban context. However,

AODV present in its basic version some vulnerability

related to the route discovery procedure and protocol

message exchange. Moreover, it does not guarantee

integrity to messages. This means that an attacker can

modify messages fields or it can generate false

messages.

Among many possible security attacks that is

possible to apply on AODV, the attention is focused

on the Black Hole attack. This last one has the

objective to act in the route discovery from source and

destination to alter the legacy path (Fiade et al.,

2020). Moreover, it can act on the RREP packet in the

reverse path forwarding. The attack considers two

phases:

• Route Discovery Alteration: after receiving the

RREQ packet, the attacker performing the

black-hole create a RREP where it sets to an

high value the Destination Sequence Number

and it sets the Hop Count to a zero value. This

packet modification determines that the

originator of the RREQ will include the

attacker in the path because it considers this

path the best;

• Packet Dropping: after performing

successfully in the previous phase, the attacker

can act internally dropping some packets

forwarded on the legacy path from source to

destination.

In brief, a malicious node cheats the routing protocol

such as it presents itself for having a short route for

forwarding the packet to the destination (Arif et al.,

2019).

3 TOOLS

In order to analyze some security threats such as black

hole attack, some well-known tools such as

OMNeT++, INET, Veins e SUMO (Haidari and

Yetgin, 2019) have been used. All these tools have

been integrated with the Crypto++ library in order to

integrate some security features applying

cryptographic techniques, directly in the INET

modules, like shown in Figure 1.

Figure 1: Tools integration.

3.1 OMNeT++

OMNeT++ is a well-known discrete time network

simulator (OMNeT++, 2021). It is composed by the

following components:

• A set of NED files useful to define the network

scenario, simulation parameters, network

interfaces and modules connections. It allows

to define node types and to connect specific

network protocol to nodes and interfaces;

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• A file called omnetpp.ini to manage

configurations and model parameters. It is

possible also to plan more simulations with

different parameters;

• A set of files .msg to model communications

and packets. It is composed by attributes and

data structure defined in C++ language;

• Source file compiled in C++; these files include

all classes defined to characterize nodes,

protocols and other network features.

3.1.1 INET

INET (INET, 2021) is an open-source library used in

OMNeT++. It offers telecommunication protocols,

agents and other models. INET is composed by

modules communications between them through

messages. These modules can be combined to realize

new components. It is used to design and validate new

protocols.

3.2 SUMO

SUMO (SUMO, 2021) is an open-source simulation

suite to generate vehicular traffic. It has been released

in 2001 and it allows the inter-modal traffic modeling

considering vehicles, public transportation system

and pedestrians. SUMO provides a broad set of tools

to create, set and evaluate traffic simulations, path

computation, CO2 emissions computation etc.

SUMO can be extended with customized models and

it provide API to control simulations. It offers plug-

in able to generate vehicles path, to show vehicles and

streets in a graphical interface and the possibility to

import real maps using external program such as

OpenStreetMap.

The environment can be defined and implemented

through the filling of some specific files such as

presented below:

 .node.xml and .edg.xml files that provide

vehicles network info;

 .rou.xml file including traffic and vehicles

route information;

 .con.xml and .typ.xml with additional

information of rules defining vehicle

movement on the streets;

 Optional additional file created by the

polyConvert application, to describe with more

details path in urban environment to model

more realistic scenarios.

SUMO provides applications to create scenario in the

.xml format to simplify the representation.

NETCONVERT is an example of these applications

able to convert files in specific SUMO formats.

3.3 Veins

Veins (Documentation Veins, 2021) is an open-

source framework to simulate vehicles networks and

VANET models. These models are executed by

OMNeT++ that can interact also with SUMO. Some

Veins components can also configure, execute and

monitor the simulation.

Both simulators are connected through a TCP

sockets. The protocol adopted for this communication

is standardized and called Traffic Control Interface

(TraCI). This connection allows a joint simulation

between vehicular traffic and network traffic.

Vehicles movement on the streets is reflected as

nodes movement in OMNeT++. Nodes can interact

with vehicle traffic at runtime.

Veins instantiates a network node for each vehicle

instantiated in SUMO. Every instantiated node is

related to an OMNeT++ module that can contain a

mobility sub-module of TraCIMobility. At periodical

interval the manager can use this module to let SUMO

simulation time go on updating the node mobility info

such as position, speed and direction in the basis of

the vehicle behavior.

3.4 Crypto++

Crypto++ (Crypto++, 2021) is an C++ open-source

library, that provides security API to create security

policies. It provides cryptographic schemes such as

AES, RSA, ECC etc. AES and RSA have been used

in our proposal and simulations.

In particular, the use of AES as a symmetric cipher

ensures the confidentiality of the communication

between VANET nodes.

RSA, on the other hand, through the mechanism of

digital signatures, guarantees the authenticity of the

of specific fields of protocol’s packets exchanged

among vehicles.

The choice of this library is linked to the program

language used by OMNeT++ developers to

implement simulator’s modules. So Crypto++ make

easier to integrate security mechanism in OMNET++.

4 BLACK HOLE ATTACK

MITIGATIONS

In this section some mitigation techniques to

blackhole attack will be presented.

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4.1 Mitigation 1: Solution

A first mitigation solution can make use of the

cryptography applied to a known filed of the RREQ

packet. This ciphered field can testify the node

identity because it is based on a pre-shared key

between source and destination. In this solution the

destination node generating the RREP that is also the

receiver of the RREQ can cipher the specific field

using the key pre-shared with the source. Moreover,

the Source Address included in the RREQ is included

in the created RREP forwarded on the reverse path

forwarding. In this way the attacker node performing

the black hole attach, cannot easily create a false

RREP at the destination because it should forge the

crypted string included in the RREP packet. This

cannot happen if the attacker does not know the pre-

shared key between the source and the destination.

Applying the mitigation explained, the source node

can accept the RREP only if the decrypted test

presents the same IP address. This proposed

technique can be effective if the only node that can

answer to a RREQ is the destination node and this

means that under this mitigation technique it is not

allowed a partial reply by intermediate node. The

cryptographic operations adopted for this case are

AES with 128 bits pre-shared keys.

4.1.1 Mitigation 1: Considerations and

Issues

The mitigation 1 does not resolve completely the

black hole attack. If the intermediate node answering

wants to be activated to reduce the control overhead

in the route discovery procedure, the Mitigation 1 can

fail in protecting by black hole attack. Intermediate

nodes do not have the capability to discriminate a

legacy RREP by a forged RREP because they cannot

access to the crypted field because they do not know

the pre-shared keys. This means that they can process

the RREP generated also by attackers and they can

update their routing table on the basis of false

information contained in forged RREP. In this case,

forged RREP with some fields modified by the

attacker can arrive at the source node that will

forward the data towards the attacker that can apply

DoS attack dropping data packet. In this case, the

attacker will avoid to alter the RREQ but in a smarter

way it will try to modify the RREP changing some

important field such as the hop count and destination

sequence number in order to let the source to believe

that the best path can pass through the attacker node.

In this case the attacker will be inside the legacy path

and it can attack internally the network applying

black-hole or gray-hole attacks.

4.2 Mitigation 2: Solution

The objective of this mitigation solution is to avoid

that attacker can modify the Destination Sequence

Number. To perform this task the RSA algorithm with

the use of a private and public keys is considered. To

guarantee the RREP DSN integrity, the node

generating the RREP should cipher the field in the

RREP using its private key including its cyphered text

in a field. In this way the node receiving the RREP

should verify the RREP DSN content applying a

decryptography with the public key of node

generating the RREP. This means that the attacker

cannot simply change the value of a field inside the

RREP, but it needs to cipher the text with a private

key of the node generating the RREP. This is not a

trivial job because it should know the private key of

the RREP generator. The application of the

asymmetric cryptography can face the problem of the

alternation of the RREP at intermediate nodes.

In order to activate the answering by intermediate

nodes to a RREQ, the intermediate node should be

able to build correctly the cyphertext and it should

know the private key of the destination. This is

necessary because if it will try to forge the RREP it

should sign the packet with a private key. In this case

the source node, when receiver the false RREP is able

to detect the forged packet because it cannot decrypt

it. Moreover, it is not so easy for the intermediate

node to know the private key of the destination

considering the robustness of the applied

cryptography. In order to integrate the proposed

mitigation technique inside the AODV protocol some

modifications should be performed:

 When a receiver node receives for the first time

a RREP from a node X that it does not know, it

updates its routing table and it maintain also the

ciphered DSN inside the RREP packet.

 For the next RREQ towards X, that node does

know yet, the intermediate node will generate

RREP taking care to include in the ciphertext

field of the RREP, the ciphered text stored in

the previous point.

It is important to notice that the RREQ contributes

to update the node routing table on the basis of the

Source Sequence Number (SSN) fixed by the source

generating the RREQ. An intermediate node

receiving the RREQ compare the SSN with the DSN

associated to the source and stored in its routing table

and if it is higher an update is performed. To

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guarantee the SSN integrity, it is necessary to cypher

it through its private key. Also, this ciphered SSN

should be stored by intermediate node in the routing

table and it can be used later when intermediate node

has to answer to the RREQ.

5 ATTACKS MITIGATION

ANALYSIS

The reference scenario adopted in our simulation is

related to a square 1Km

area in the Cosenza city such

as shown in Figure 2. A number of vehicles equals to

32 is considered where nodes can be source,

destination, intermediate node and some of the, can

be attackers. Two different attacks are performed.

The first one where destination node try to alter the

RREP (Attack 1) and the second one where

intermediate node try to forge the RREP.

Figure 2: Simulated City Map Area.

5.1 Performance Evaluation Metrics

In order to evaluate the effects on the network under

security attacks, some countermeasures have been

implemented and tested. The following performance

metrics have been considered:

1. RREQ Sent: RREQ number generated and

forwarded by a node;

2. Sent RREP: RREP number generated and

forwarded by a node;

3. Sent RERR: RERR number generated and

forwarded by a node;

4. Received RREQ: RREQ number received by a

node;

5. Received RREP: RREP number received by a

node;

6. Mean Discovery Time (MDT): average time

between RRRQ forwarding by source and the

reception of the relative RREP;

7. Mean Hop Count: average hop count number

related to the discovered paths;

8. RREQ E2E Delay: RREQ delay computed in

the propagation from source to destination;

9. E2E RREP Delay: RREP delay computed in

the propagation from destination to source;

10. AODV Encryption Time: total encryption time

computed on every AODV packet;

11. AODV Decryption Time: total decryption time

computed for each decryption operation

applied on every packet.

Let us analyze now the performance evaluation of the

network under different situations with and without

blackhole attacks.

The following scenario have been studied:

 Scenario 1: a simple scenario where all nodes

are legacy and no attack is performed;

 Scenario 2: scenario where the first type of

attack is performed but no countermeasure is

applied.

 Scenario 3: scenario with the first type of

attack and where the fist mitigation is

considered.

 Scenario 4: scenario where the second type of

attack (Smart Black Hole) is applied and only

the Mitigation 1 is applied.

 Scenario 5: scenario where some type 2 attack

is performed and where the Mitigation 2 is

considered.

5.2 Performance from Sender

Perspective

In this sub-section it is analyzed the performance of

nodes generating the RREQ for the route discovery

and the nodes generating RERR and RREP to see

what happens in the different scenario listed above.

The MDT is evaluated in Figure 3 to see as it can

change is an attack is performed. It is possible to see

as in scenario 2 the MDT presents the lowest value.

This could apparently seem to be a good result but it

is only due to the collateral effect that intermediate

nodes can forge the RREP reducing the MDT but

creating unsuitable paths. On the contrary the

scenario 5 that is the most secure the MDT increases

because heavier cryptography approach (asymmetric

crypto) is applied. In scenario 3 the MDT is lower

because a lighter cryptography (symmetric) is

applied. However, in scenario 3 there is the possible

vulnerability to attack of type 2.

Obviously the E2E RREP Delay is observed to be

lower in comparison with the MDT but it is expected

because this metric in included in the MDT.

Extending OMNeT++ Simulator to Secure Vehicular Communication under Blackhole Attack

383

Figure 3: MDT sender.

Figure 4: AODV sender packets.

Concerning the AODV protocol packets, as shown in

Figure 4, in scenario 2 it is observed a high value of

RREP received at the source, this is due to the attack

of type 1 that is not mitigated. It is possible to see also

as the number of RREQs is proportional to the

number of RERRs and this is due to the route

breakage related to the node mobility.

5.3 Performance from Receiver

Perspective

Figure 5: Receiver packets.

The number of packets received, as shown in Figure 5,

by nodes change on the basis of the considered

scenarios. It can have a value between 405 and 2148.

The first value represents the lowest value obtained in

the scenario under attack and without mitigation. The

higher values such as 2148 and 1897 are obtained for

scenario under attacks where the mitigation can reduce

or block the attackers effect. The lowest value or

received packets testify as the blackhole attack tries to

drop packets reducing the number of received packets.

Such as expected, the highest value is registered in the

scenario 1 where without attacks a higher number of

packets can be received without malicious dropping.

5.4 Black Hole Nodes

The number of sent and received packets generated

by black hole nodes is zero such as expected because

they do not generate new packets, but they will drop

received packets. In scenarios without mitigation

solutions the number of dropped packets is higher

such as shown in Figure 6.

Figure 6: Black Hole packets.

Concerning the packets generated during black hole

attack, as shown in Figure 7, it is possible to see as

the most important packets to analyze are RREP

packets because they are used and forged in the first

part of the attack. The highest sent RREP packets are

observed in scenario 2 and scenario 3 because RREPs

are generated by malicious node whereas in scenario

4 and scenario 5 RREP are not generated by malicious

nodes but they are only forwarded.

Figure 7: AODV Black Hole packets.

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6 CONCLUSIONS

This work analyses some routing threats over

VANET. The black hole attack has been evaluated

proposing two possible attacks: one simple attack

applied at the destination and another one that can be

applied by intermediate nodes that can forge a RREP

packet and then can perform an inside attack dropping

data packets. To face these security issues, it is

necessary to use cryptography to provide integrity to

some field in the RREQ and RREP packets or to use

a more complex asymmetric cryptography to

authenticate the RREQ and RREP packets providing

both authentication and integrity. Both security

solutions have been evaluated considering different

scenarios where attackers can perform the simplest

attack or the smarter black hole attack. The second

mitigation technique has been shown to be more

effective increasing a little bit more the AODV

protocol complexity.

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