Attacks classification and security mechanisms in Wireless Sensor Networks

Abstract

This paper proposes a new classification model distinguishing four classes of attacks in Wireless Sensor Networks (WSNs) namely: attacks based on the protocol stack, on the capability of the attacker, on the attack impacts and on the attack target. Then, it presents
and classifies the most known attacks in WSNs based the proposed model. Simulations implemented under the NS3 simulator prove that the network lifetime can decrease by more than 45% in the presence of attacks. Afterwards, it discusses the main security methods and
protocols of management and distribution of encryption keys used to ward off different types of attacks. Obtained results confirm that these security methods must be adapted to the specific characteristics of WSNs to achieve the intended objectives.

Full text

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Attacks classification and security mechanisms in Wireless Sensor Networks
Amine Kardi1,*, Rachid Zagrouba2
1Faculty of Mathematical, Physical and Natural Sciences of Tunis, University of Tunis El Manar, 2092 El Manar, Tunisia
2College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam
31441, Saudi Arabia
A R T I C L E I N F O
A B S T R A C T
Article history:
Received: 12 September, 2019
Accepted: 16 November, 2019
Online: 05 December, 2019
This paper proposes a new classification model distinguishing four classes of attacks in
Wireless Sensor Networks (WSNs) namely: attacks based on the protocol stack, on the
capability of the attacker, on the attack impacts and on the attack target. Then, it presents
and classifies the most known attacks in WSNs based the proposed model. Simulations
implemented under the NS3 simulator prove that the network lifetime can decrease by more
than 45% in the presence of attacks. Afterwards, it discusses the main security methods and
protocols of management and distribution of encryption keys used to ward off different types
of attacks. Obtained results confirm that these security methods must be adapted to the
specific characteristics of WSNs to achieve the intended objectives.
Keywords:
Wireless Sensor Networks
Routing attacks
Cryptography
Security
NS3 simulator
1. Introduction
With the widespread use of WSNs[
1
][
2
], composed of a small
and low-powered communicating devices usually deployed in
hostile environments, and due to their resources constraints,
security factors become crucial and challenging with the
appearance of a variety of attacks targeting these networks
[
3
][
4
][
5
]. The main contribution of this paper is to provide a survey
of these attacks and of the security techniques which will facilitate
the design of WSNs for researchers and routing protocol
programmers.
The rest of the paper is organized as follows: Security
requirements for WSNs are discussed in Section 2. Section 3
introduces our proposed taxonomy and discusses each category of
attacks. Section 4 presents the main attacks in WSNs and analyzes
them using NS3 simulator. The basic security mechanisms in
WSNs are presented in Section 5 then followed by the analysis and
findings in section 6. Lastly; we conclude the paper and highlight
our future work in section 7.
2. Security requirements for WSNs
Due to the lack of a wired communication medium, the limited
resources of sensors and the properties of the deployment [
6
][
7
],
WSNs, deployed mostly in hostile environments with mission-
critical tasks, have several security challenges which are more
complex than with other types of networks. As an ad hoc network,
security requirements for WSNs include the standard security
metrics known as CIAA (Confidentiality, Integrity, Authentication
and Availability) in addition to the security requirements specific
to this type of network which aim to protect the information and
resources from attacks and misbehavior. In the following we
discuss the security properties and requirements we would like to
achieve in order to establish a reliable communication in WSNs
and to provide secure services [
8
].
2.1. Standard security requirements
As with other types of networks, standard security
requirements are needed in WSNs such as:
• Confidentiality: This is the most important issue in network
security which guards data from eavesdroppers. It ensures that
a given message remains hidden and cannot be used by
anyone other than the desired receiver. It protects packets
from undertaking traffic analysis, passive attackers and
modification. The standard approach for achieving this
requires use of encryption techniques [
9
].
• Integrity: Data integrity is needed to ensure the reliability of
data parquets. In fact, sent packets must be protected from
modification (adding, altering, deleting, damaging or losing)
by malicious intermediate nodes or by wireless channel
disturbance during the transmission [
10
].
ASTESJ
ISSN: 2415-6698
*Amine Kardi, Tunis, (+216.96.27.90.33),Email : amine.kardi@fst.utm.tn
Advances in Science, Technology and Engineering Systems Journal Vol. 4, No. 6, 229-243 (2019)
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Special Issue on Multidisciplinary Sciences and Engineering
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K. Amine et al. / Advances in Science, Technology and Engineering Systems Journal Vol. 4, No. 6, 229-243 (2019)
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• Authentication: all applications require data authentication
which ensures the reliability of the message by giving the
ability of each communication host to identify its origin and
to verify the other’s identity to counter to packet injection or
spoofing and to all malicious routing information. Critical
characteristics of sensor nodes and the wireless nature of the
communication medium in WSNs make extremely
challenging to ensure authentication in these networks [
11
].
• Availability: Availability affects several sides in the sensor
network. In fact, it determines whether a node can use the
resources if needed, whether data and services are available
for on-demand use and whether the network is always
available to ensure communication even in the presence of
malicious attacks. A loss of availability may have serious
impacts and threat the entire network, e.g. it may open a
backdoor for malicious invasion in some cases and sensed
information may become useless or of lower value, but also
providing availability can hurt the network lifetime especially
with limited energy resources [
12
].
2.2. Specific security requirements
Node characteristics and deployment environments make
WSNs vulnerable to special attacks and subsequently several
security requirements specific to this type of networks are needed
such as:
• Authorization: ensures that only authorized nodes can
manipulate data (provide, update...) in the network and
prevents unauthorized access to resources [
13
].
• Nonrepudiation: it prevents a node from denying sending a
message it has previously sent through the network [
14
].
• Data freshness: implies that used data are recent and valuable
and cannot be replayed by a malicious actor, under any
circumstances, after abandonment to prevent, i.e. overloading
the network by sending previously captured packets.
Timestamps and time-related counters can be used to ensure
data freshness [
15
].
• Transparency: after leaving the network a sensor node
should not be able to replay old packets or to read any future
messages in the same way as a joining node should not be able
to reload or to read any previously transmitted message in
order to protect the network from malicious injected nodes
[
16
].
• Self-Organization: In the absence of an overall network
management infrastructure, sensor nodes which have the
ability of self- organization may encounter several hazards
and risks threatening the safety and operation of the entire
network [
17
].
Time Synchronization: due to its limited energy resources,
sensor nodes may be turned off for periods of time in the form
of a smart sleep in order to conserve energy and, in some
application, the end-to-end delay of some packets is of a great
extent that is why collaborative sensor nodes require a
synchronization system which must be ensured by a secure
synchronization protocol to deal with attacks that attempt to
affect proper synchronization between nodes [
18
].
• Secure Localization: In several applications, sensor networks
are designed to locate faults. Consequently, the network must
be able to accurately and automatically locate each sensor
node that is why location information must be handled in a
secure manner to avoid attacks taking advantage of the
security weaknesses of this information [
19
].
• Anonymity: malicious actors do not have to decrypt the
source node of a packet in order to secure nodes and the
sensing area which can be affected by erroneous data [
20
].
• Survivability: Network services and functionalities must be
maintained even with the low levels required in the case of
failures, attacks and compromised or destroyed nodes [
21
].
According to these security requirements, it's obvious that
attacks in WSNs can be of different types and can affect the entire
network system such as nodes, packets, data, paths, routing etc.
The following section presents our proposed taxonomy.
3. Taxonomy of attacks in WSNs
Because of its specific characteristics, WSNs are vulnerable to
various types of attacks. These attacks are of different mechanisms,
techniques and goals which makes necessary to find and adopt a
well-defined taxonomy in order to facilitate design and
development of WSNs for researchers and protocol programmers.
According to the security requirements mentioned above, and
taking into account the mechanisms and parameters of attacks; we
propose a new taxonomy which divides attacks in WSNs into four
major classes namely: attacks based on the protocol stack, based
on the capability of the attacker, based on the attack impacts
and based on the attack target as shown in figure 1.
A detail overview of each security attack class is discussed in
the rest of this section.
3.1. Attacks based on protocol stack
The protocol stack used by nodes in a wireless sensor network
consists of the Physical Layer, Data Link Layer, Network Layer,
Transport Layer, Application Layer, power management plane,
mobility management plane and task management plane as shown
in figure 2. It ensures the energy efficiency in the network,
manages the use of the wireless medium with the routing task and
facilitates synchronization and cooperative efforts between sensor
nodes.
Each level on the protocol stack takes on a set of tasks and
guarantees a set of services. Therefore, it will be targeted by
several attacks.
• Physical Layer:
This layer ensures the data transmission services which encompass
the selection of access channels, radiofrequency regulation and
deflection, signal processing and data encryption to increase the
communications reliability. The importance of this layer exposes
it to a variety of attacks targeting data privacy, resource depletion,
signal and communications interruption, and so on [
22
].
• Data Link Layer:
This layer is responsible of physical addressing, error detection
and/or correction, data streams multiplexing, medium access and

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Figure 1: Security attacks in WSNs: A taxonomy
flow control as well as ensuring reliable point-to-point and point-
to-multipoint connections in the network. The medium access
control (MAC) protocol must support mobility and be able to
handle collisions and to achieve energy efficiency in the network.
The importance of this layer makes it vulnerable to several types
of attacks sources of collisions, resource exhaustion, and network
destruction [
23
].
• Network Layer:
This layer is in charge of routing the data supplied by its upper
layer. It is very important task encompasses packets routing and
forwarding, addresses assignment and energy management. These
axial and fundamental tasks attract several attacks aimed at
absorbing the network traffic, disrupting communication,
exhausting resources, intercepting paths and injecting malicious
packets [
24
].
• Transport Layer:
The transport layer ensures the management of end-to-end
reliable delivery of packets connections and the establishment of
end-to-end connection in addition to flow and congestion control.
It is especially needed when the system is planned to communicate
with external networks. Several attacks target this layer in order to
reduce the network's availability, to degrade or even prevent data
exchange and to waste energy [
25
].
• Application Layer:
This layer contains user applications which oversee the sensing
tasks. It manipulates user data with a set of application protocols,
and it is a target of attacks aiming at affecting the synchronization
of communications and data confidentiality.
The power management plane and the mobility management
plane are responsible, respectively, for the management of energy
resources and the mobility of nodes in order to achieve maximum
energy efficiency and stability of communications. The task
management plane manages the sensing tasks and ensures
synchronization between sensor nodes [
26
].
Figure 2: The protocol stack of sensor networks
3.2. Attacks based on the capability of the attacker
Based on the capability of the attacker, attacks in WSNs can be
subdivided into two classes: Location capability and Attacking
Taxonomy
of attacks in
WSNs
Based On
the
Protocol
Stack
Physical
Layer
Data Link
Layer
Network
Layer
Transport
Layer
Application
Layer
Based on
the
capability
of the
attacker
Location
capability
Outsider
attacks
Insider
attacks
Attacking
devices's
capability
Mote-class
attacks
Laptop-
class
attacks
Based on
the attack
impacts
Interruption
Interception
Modification
Fabrication
Reloading
Packets
Resources
depletion
Based on
the attack
target
User
Hardware
Software
Information
Physical Layer
Data Link Layer
Network Layer
Transport Layer
Application
Layer
Power management plane
Mobility management plane
Task management plane

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device’s capability. Each of these classes is further divided into
two broad subclasses according to the relative capabilities of the
attacker which are respectively: Outsider/ Insider attacks and
Mote-class/ Laptop-class attacks. In the following we detail each
of these subclasses.
• Outsider/ insider attacks
Based on the location capability of attackers, attacks in WSNs
can be classified into Insider and Outsider attacks. We are talking
about insider attacks when a legitimate nodes belonging to the
network and which are actually part of it are compromised and
participates in unintended and/or unauthorized ways in the attack
contrary to outsider attacks which are launched only from outside
the networks application environment and performed by external
nodes which do not belong to the WSN. Insider attacks are more
severe when compared with outside attacks since compromised
nodes contains secret information and may not be detected due to
the possesses privileged access rights they had. These attacks
target the entire network and affect the resources, data,
communications and even the existence of the network. Some
papers refer to internal and external attacks [
27
].
• Mote-class/ laptop-class attacks
Based on the Attacking device’s capability, attacks in WSNs
can be classified into Mote-class and laptop-class attacks. In mote-
class attacks, attackers use malicious nodes with similar techniques
capabilities and hardware proprieties to the network nodes in order
to execute malicious codes aiming to affect the network
functionalities (data, routing, paths, energy management...).
Contrariwise, attackers use more powerful devices with great
transmission range, processing power, and energy supply than the
network's sensor nodes in laptop-class attacks e.g., a laptop which
results in launching more serious attacks and consequently lead to
more serious damage to the target network [
28
].
3.3. Attacks based on the attack impacts
Based on the attack impacts, attacks in WSNs can be
subdivided into six classes: Interruption, Interception,
Modification, Fabrication, Reloading Packets and Resources
depletion. In the following we detail each of these four classes.
• Interruption
The attacker aims, through some techniques, to interrupt the
network’s functionalities. These attacks are varied and can target
nodes, sinks, paths, routing task, resources depletion etc. which
threaten services availability. Even in the presence of an attack, the
network must be capable of maintaining its functionalities without
interruption [
29
].
• Interception
These attacks are used when the attacker intended to eavesdrop
on the network information. This threatens message confidentiality,
network services availability and may result in the depletion of
resources [
30
].
• Modification
These attacks threaten data integrity. Attackers intend to
eavesdrop to information and to tamper with it in various ways:
Injection, removal, modification etc. in order to disrupt the
network functionalities and threaten the accuracy of services and
treatments [
31
].
• Fabrication
These attacks are manifested by the injection of erroneous data
into the WSN. Attacker aims to threaten message authenticity and
network availability through the depletion of the energy resources
of the network especially with wireless communications which are
very energy intensive [
32
].
• Reloading Packets
In some cases, the attacker seeks to reload and read previously
transmitted packets from a compromised node or from buffers of
active nodes which threatens data confidentiality and packets
transparency. These packets can be injected back into the network,
which threatens messages freshness and wastes energy [
33
].
• Resources depletion
In a WSN, resources depletion leads to the complete collapse
of the network. Attackers aim to waste limited energy resources of
nodes using various processing and transmission tasks [
34
].
3.4. Attacks based on the attack target
Attacks in a WSN can target different actors and components
of the network which are users, hardware, software and
information [
35
]. In the following we detail each of these targets.
• User
Various users of a WSN like humans, robots etc. can be
targeted by malicious attacks aiming to have an authorized access
to the network system through legitimate compromised identifiers.
These attacks seek to take control of the network, to use it for
personal tasks, to use information or to destroy it.
• Hardware
Attacks targeting hardware in WSNs tend to compromise
nodes for malicious intent, waste limited energy resources or
destroy equipment. A compromised node may contain secret
information and may be used for unauthorized access to the
network.
• Software
Attacks targeting software in WSNs aim to eavesdrop
information, control the network and disrupt the services and
functionalities.
• Information
Attacks targeting information in WSNs are various e.g. the
attacker can falsify the data supposed to be sensed in the sensing
area, in other cases, sensed data can be targeted by attacks, packets
in transit, authentication parameters etc. Attackers aim at affecting
the network functionalities, services availability and data
confidentiality.
Each of these classes helps to analyze and study attacks in
WSNs from different perspectives. We detail, in the following
section, the most known attacks and countermeasures to counter
their effects.
4. Attacks in WSNs
Generally, attacks under these four classes, can be either active
or passive. A passive attack is an attack that aims to gets exchanged

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data in the network without interrupting the communication to
remains hidden and not be discovered. Passive attackers listen and
collect data that can be used later to start other types of attacks.
While active attacks involve some modifications in the data stream.
In fact, it seeks to modify, fabricate, inject a false stream or
intercept the data or the communication to disrupt the normal
functionality of the network. In the active mode the attacker is
more aggressive and aims to damage the entire network [
36
].
4.1. The most known attacks:
Among the most known attacks in WSNs we find:
• Jamming:
Jamming attack [
37
] takes advantages of the sensitivity of the
wireless medium to interferences and results in a denial of service
in the network. Attacker identifies the radio frequencies used by
the targeted WSN and tries to disrupt or block communications by
emitting signals (unnecessary information) in the same frequencies
that inhibit communication (messages transmission and/or
reception) between nodes. This interference may be temporary,
intermittent or permanent and can affect all or part of the network
depending on the radio range of the jamming source which can
have the same characteristics as the network nodes as it can be
more powerful. Jamming can be of different types: it can be
constant if it targets and corrupts data packets in transit, deceptive
when sending a constant data stream in the network, random when
injected data streams are dispersed over time and reactive if the
jamming source sends a jam signal following the detection of
traffic. Jamming can target different layers: It can interfere with
radio frequency signals at the physical layer, as it can take
advantages of the medium access control protocol causing
malicious collisions at the link layer as it can target the network
layer by injecting malicious packets. Defense techniques
[
38
][
39
][
40
] against Jamming attack involve spread-spectrum
techniques for radio communication such as frequency hopping to
switch between many frequency channels, authentication
mechanisms to detect malicious and replayed packets, the use of
secure medium access control protocols etc.
• Tampering or destruction [
41
]:
WSNs are highly vulnerable to physical attacks as they are
often deployed in unprotected areas. A Tampering attack will be
triggered after physically capturing the node and aims to retrieve
cryptographic material as encryption keys and the program code
stored within a node which can be used later to trigger other types
of attacks such as modifying routing information, creating
duplicate data packets, tampering routing services etc. or to
manipulate the captured node by installing a new code causing an
abnormal behavior of the compromised sensor, controlled by the
attacker, in order to disrupt the network. Destruction attack
consists of removing the sensor from the network by destroying it
resulting in isolated areas and even the destruction of the entire
network. Defense techniques against this attack are based on the
principle of considering the situation in which sensor nodes are
compromised such as tamper-proofing the physical package of
nodes.
• Continuous Channel Access (Exhaustion):
Exhaustion [
42
] belongs to DoS attacks. It aims to exhaust the
batteries of the nodes in order to reduce the network lifetime. It
consists to disrupt the Media Access Control protocol, by
continuously injecting unnecessary packets in the network and
requesting or transmitting data over the channel entail the waste of
node energy in unnecessary retransmissions. A possible solution
to this attack is the Rate Limiting at the MAC admission control
which allows ignoring corrupted packets and excessive malicious
requests [
43
] [
44
].
• Collision:
Collision attack [
45
], similar to the continuous channel attack,
can be caused by malicious nodes by transmitting packets in the
network in order to block / delay the communication between
nodes which results, in addition to the throughput, in a waste of
energy and a loss of data. It is difficult to detect Collision attack in
WSNs because it is a short time attack using malicious packets
which are similar to legitimate packets. Researches, such as [
46
],
proposed several Collision detection techniques such as error-
correcting codes.
• Unfairness:
Unfairness attack [
47
] is a partial or a weak form of DOS
attack that can result in marginal performance degradation. Based
on other attacks such as collision and exhaustion, collision attack
decreases significantly the utility and efficiency of services. In fact,
attackers request continuously to access to the channel which
results in undermining communication and limiting channel
capacity. One of the countermeasures to such an attack is time-
division multiplexing [
48
] allowing each node to transmit only in
a specific time slot.
• Interrogation [
49
]:
To soften the problem of frame collisions introduced by the
hidden node problem, several MAC protocols use the RTS/CTS
handshake [
50
]. Attackers take advantages of this synchronization
mechanism by repeatedly sending RTS packets leading to CTS
responses from neighboring nodes. To counter this type of attack,
nodes can use several mechanisms such as anti-replay protection
and link layer authentication [
51
].
• Sybil Attack [
52
]:
As shown in figure 3 Sybil Attacks allow malicious nodes to
have multiple identities by using the identities of the nodes targeted
by the attack in order to participate in distributed algorithms such
as election to take advantage of legitimate nodes to endorse the
creation of several routes passing through the malicious node. This
attack is located between the link and the network layers and it
aims to degrade the integrity of data, the security level of and the
use of resources. Among these attacks we can found Data
Aggregation attacks aiming to falsify the aggregated message and
Voting attacks affecting routing path and node selection. Several
researches, such as [
53
] [
54
], sought to counter this attack using
different mechanism such as public key cryptography and digital
signatures.
• Sinkhole:
Sinkhole attack [
55
] belongs to DoS attacks in WSNs. As
shown in figure 4, the attacker (malicious node) must appear to
other nodes as being very attractive by presenting optimal routes
in order to attract packets as much as possible to control most of

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the data circulating in the network. Consequently, malicious node
acts as a base station by attracting data packets and preventing
them from continuing their path creating a kind of well or black
hole in the network. The attacker, having a strategic routing
location in the network, manipulates packets as desired, causing
the suspension of the network routing service and the depletion of
critical resources of nodes. Geo-routing protocols, using localized
information and routing traffic through the physical location of
nodes, are resistant to sinkhole attacks.
Figure 3: Sybil Attack
Figure 4: Sinkhole attack
• Hello Flood [
56
]:
The presence of laptop-class attackers and the limited
transmission range of sensors led to the appearance of the Hello
flood attacks. This attack takes advantages of the powerful signal
of the attacking device to broadcast the information of an optimal
route to all the nodes which will update their local tables. When a
targeted node wants to communicate, it will not be able to use this
route because the attacker, which is the imaginary neighbor, is out
of range which results in the waste of energy from the sensors
which leads to a malfunction of the network. Security mechanisms
such as cryptography and source authentication, used to verify the
bidirectionality of a path before taking action received over it, are
used to counter this type of attacks.
• Node Capture:
In most applications, sensor nodes are highly vulnerable to
physical attacks as they are often deployed in open areas easily
accessible to attackers which raise the possibility of node capture
to be used in tampering attacks. Researches such as [
57
] show that
even a single node capture led to take over the entire network by
attackers which makes the resilience against node capture attacks
one of the most challenging issues in WSNs [
58
].
• Selective Forwarding:
Routing protocols assume that nodes will faithfully relay the
packets that pass through them. We talk about Selective
Forwarding attack when attacker may create malicious nodes and
can violate this rule by removing all or some of these incoming
packets randomly (neglectful node) or by giving high priority to its
own messages (greedy node). Multipath routing, braided paths and
random selection of paths to destination are a possible defense
against this type of attack [
59
] [
60
].
• Black Hole Attack:
This attack can be considered as a form of selective forwarding
attack dropping all incoming packets, it consists of inserting a new
node or compromising a network node which falsifies the routing
information to broadcast itself as the shortest path to oblige a
maximum of neighbors to modify their routing tables in order to
force the data to pass through it. This information will be destroyed
which makes the malicious node as a well or black hole in the
network. When attacker is placed on a strategic routing location in
the network such as sinks or base stations the attack cause a
network partition, packets loss, resource exhaustion and even the
suspension of the routing services of the entire network. Black hole
attack often targets hierarchical architectures and more specifically
aggregator nodes. Multiple paths routing presents a defense against
black hole attack [
61
] [
62
].
• Wormhole Attacks [
63
]:
Also known as tunneling, it is one of the most severe attacks.
As shown in Figure 5, it requires at least two malicious nodes
linked by a powerful radio link or by a wire link. In a wormhole
attack, information received by a malicious node in one side of the
network are encapsulated and relayed to be reintroduced by
another malicious node on the other side of the network, revealing
that the message originates from a close node. Encapsulation can
be done in two ways: "Multi-hop encapsulation" aiming to hide
intermediate nodes located between the two attackers to make the
paths through the malicious node appear shorter which facilitates
the creation of sinkholes with protocols using the number of hops
as main metric of paths selection and "direct communication" in
which paths going through the attackers are faster because they are
composed of a single hop and can be used against protocols using
the first discovered path and those based on paths latency. This
type of attacks can considerably disrupt a location system by
introducing erroneous reference points. It can be further divided
into three classes: Half Open Wormhole, Closed Wormhole, and
Open Wormhole. Several mechanisms for detecting and defending
against wormhole attacks are presented such as WRHT [
64
].
Figure 5: Wormhole attack

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• Spoofed, Altered, or Replayed Routing Information [
65
]:
routing information in transit are targeted by several attacks,
they can be spoofed, altered, or replayed. Malicious nodes can
attract or repel the network traffic, inject false and misleading
packets, overflow routing tables and create routing loops which
result in disrupting the network traffic, partitioning the
communication system and even destruction on the entire network.
Several researches, such as [
66
], aim to counter these attacks using
counters, timestamps, encryption and various authentication
techniques.
• Misdirection [
67
]:
This active attack consists in misdirecting the data packets. In
fact, instead of sending the packets in a correct direction, malicious
nodes redirect them in a wrong direction through which the right
destination is unreachable. Targeted node, flooded without any
useful information, suffers from a waste of resources. Some
security mechanisms [
68
] such as smart sleep [
69
] avoids this
attack.
• Homing [
70
]:
This attack aims to locate critical nodes in the network
providing essential services such as cluster heads and key
managers by monitoring and analyzing the network traffic and
nodes activities in order to eavesdrop their activities, take control
of the network and extract sensitive data. To prevent homing
attacks, protocols designers use different types of cryptographic
schemes, algorithms and hide management messages [
71
] [
72
].
• Flooding [
73
]:
This attack aims to provoke a denial of service in order to
decreases network lifetime. Indeed, one or several malicious nodes
propagate many connection requests and carry out a regular
massive sending to a strong emission power until exhausting the
resources required the connection or reaching a maximum limit in
order to saturate the network and prevent legitimate nodes from
establishing communications which exhaust the resources
(memory and energy) and reduce availability. One proposed
solution to this attack is to demonstrate the commitment to this
connection or to put a limit on the number of connections from a
particular node [
74
] [
75
].
• De-synchronization Attacks [
76
]:
It is a part of the resource depletion attacks. The attacker causes
missed frames by distorting, changing or increasing the sequence
number of exchanged packets between end points. By receiving
the modified packets, the destination deduces that the packets have
been lost and requests the forwarding of these packets to the
senders which disrupts the synchronization of communications
and led to a considerable waste of energy of legitimate sensors by
attempting to recover from errors which never really existed.
Packets authentication is one of the main solutions to counter this
attack [
77
] [
78
].
• Overwhelm attack [
79
]:
It is a part of QoS attacks. It consumes network bandwidth
causing resource depletion by forwarding large amounts of data
packets due to an exaggerated stimulation of sensors. A good
adjustment of sensors and stimulation parameters, rate-limiting
and efficient data-aggregation algorithms help to counter this
attack [
80
].
• Path-based DOS attack [
81
]:
In this attack malicious nodes inject spurious or replayed
packets in the network which waste energy resources and
bandwidth on the path to the base station. Hence, legitimate nodes
are prevented from sending packets to the base station.
Authentication techniques and anti-replay protection counter this
attack [
82
].
• Deluge (reprogram) attack [
83
]:
This attack uses one or more compromised nodes that the attacker
reprograms them and then reinsert them on the network as
malicious nodes working in his service. Deluge attack aims to
disrupt the network and the application by causing an abnormal
behavior of nodes. Indeed, these nodes run malicious codes in
order to steal secret or sensitive information, attempt to disrupt the
normal operation of the entire system and take control of large
portions of a network. Several researches such as [
84
], introduce
various techniques to counter this type of attacks.
Table 1 classifies the previously detailed routing attacks on
WSNs according to our taxonomy proposed in the previous section.
4.2. Simulation results
4.2.1. Network model
To show the effect of these attacks on WSNs, we used the NS3
simulator to simulate the effect of Jamming and Hello Flood
attacks on a WSN using LEACH protocol [
85
].
As indicated in Table2, the adopted network model consists of 100
nodes randomly deployed in 100m * 100m area with unlimited
power sink centered in the field as shown in Figure 6.
Figure 7: Nodes distribution
4.2.2. Results and discussion
In this section, the following metrics are used to evaluate the
effect of Jamming and Hello Flood attacks:
- Network lifetime (Alive nodes Versus Rounds + Dead nodes
Versus Rounds)
- Stability /instability periods
- Remaining energy Versus Rounds
We start with the evaluation of the network lifetime.

K. Amine et al. / Advances in Science, Technology and Engineering Systems Journal Vol. 4, No. 6, 229-243 (2019)
www.astesj.com 236
Table 2: Network parameters
Parameters
Values
Network size
100m * 100m
Number of nodes
100
Sink location
50,50
Packet size
4000 bits
Initial energy
0.5 J
Energy Dissipation (Efs)
10 pJ/bit/m²
Energy for transmission (ETx)
50 nJ
Energy for reception (ERx)
50 nJ
Data Aggregation
5 nJ/bit/report
Number of rounds
2000
• Network lifetime
The network lifetime is one of the main metrics to be
considered to evaluate the efficiency of the network. It is the period
between the beginning of the network and the death of last node.
The two complementary Figures 8.a) and 8.b) respectively show
the evolution of the number of alive and dead nodes in the network
using LEACH protocol with and without the presence of attacks.
As shown in Figure 8, the network lifetime using LEACH
protocol without undergoing attacks is about 1560 rounds, while it
does not exceed 1080 rounds in the presence of Hello Flood attack
and 820 rounds with Jamming attack. Using a powerful signal,
Hello flood attack broadcast the information of an optimal
imaginary route according to which the sensors update their local
Types
Attacks
Based On
Protocol Stack
Based on the
capability of
the attacker
Based on the
attack impact
Based on
the attack
target
Pas
sive
/acti
ve
P
L
D
L
L
N
L
T
L
A
L
LC
DC
I
R
P
I
T
C
M
F
R
P
R
D
U
H
S
I
P
A
O
I
M
L
Jamming
*
*
*
*
*
*
*
*
*
*
*
Tampering or
destruction
*
*
*
*
*
*
*
*
*
Continuous
Channel Access
(Exhaustion)
*
*
*
*
*
*
*
*
Collision
*
*
*
*
*
*
*
*
*
*
Unfairness
*
*
*
*
*
*
*
*
*
*
Interrogation
*
*
*
*
*
*
*
*
Sybil Attack
*
*
*
*
*
*
*
*
*
*
*
*
Sinkhole
*
*
*
*
*
*
*
*
*
*
*
*
*
Hello Flood
*
*
*
*
*
*
*
*
*
*
Node Capture
*
*
*
*
*
*
*
*
*
*
*
*
*
*
Selective
Forwarding
*
*
*
*
*
*
*
*
*
*
*
Black Hole Attack
*
*
*
*
*
*
*
*
*
*
*
Wormhole Attacks
*
*
*
*
*
*
*
*
*
*
Spoofed, Altered,
or Replayed
Routing
Information
*
*
*
*
*
*
*
*
*
*
*
*
*
*
Misdirection
*
*
*
*
*
*
*
*
*
*
Homing
*
*
*
*
*
*
Flooding
*
*
*
*
*
*
*
*
*
De-
synchronization
Attacks
*
*
*
*
*
*
*
*
*
*
Overwhelm attack
*
*
*
*
*
*
*
*
Path-based DOS
attack
*
*
*
*
*
*
*
*
*
*
*
Deluge
(reprogram) attack
*
*
*
*
*
*
*
*
*
*
*
*
*
PL: Physical Layer
DLL: Data Link Layer
NL: Network Layer
TL: Transport Layer
AL: Application Layer
LC: Location
Capability
O: Outsider
I: Insider
DC: Device Capability
M: Mote Class
L: Laptop Class
IRP: Interruption
ITC: Interception
M: Modification
F: Fabrication
RP: Reloading Packets
RD: Resources
Depletion
U: Users
H: Hardware
S: Software
I: Information
P: Passive
A: Active
Table1: Comparison table of routing attacks in WSNs

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www.astesj.com 237
tables. This technique led to a waste of energy and to a malfunction
of the network. As explained earlier in this survey, deceptive
Jamming attack, used in this simulation, consist in sending a
constant data stream in the network which leads to overloading the
antennas of the sensors and therefore to a great loss of energy and
the disappearance of the network in a short time.
Figure 8-a: Alive nodes VS. rounds
Figure 8-b: Dead nodes VS. rounds
Figure 8: Network lifetime
• Stability / instability period
A stability period triggers with the beginning of the network
until the death of the first node which declares the beginning of an
instability period. This instability period extends until the death of
all nodes in the network. Figure 9 shows the stability and instability
periods of the network using LEACH protocol with and without
the presence of attacks.
As shown in Figure 9, the stability period almost reached
790rounds without attacks, but it does not exceed 320 rounds in
the presence of Hello flood attack and 255 rounds with Jamming
attack. In the same way, the instability period is about 773 rounds
in the absence of attacks but does not surpass 760 rounds with
Hello flood attack and 565 rounds in the presence of Jamming
attack. This is obviously explained by the effect of the attacks on
the consumption of energy.
Figure 9: Stability and instability periods
Figure 10: Residual Energy VS. Time
• Remaining energy
The residual energy, shown in Figure 10, results from the
evolution of the number of nodes in the network. The curves show
0
10
20
30
40
50
60
70
80
90
100
0500 1000 1500 2000
Alive nodes
Rounds
LEACH without attacks
LEACH with Hello flood attack
LEACH with Jamming attack
0
10
20
30
40
50
60
70
80
90
100
0500 1000 1500 2000
Dead nodes
Rounds
LEACH without attacks
LEACH with Hello flood attack
LEACH with Jamming attack
0
100
200
300
400
500
600
700
800
900
Stability instability
LEACH
LEACH with Hello flood attack
LEACH with Jamming attack
0
5
10
15
20
25
30
35
40
45
50
0500 1000 1500 2000
Residual Energy
Rounds
LEACH without attacks
LEACH with Jamming attack
LEACH with Hello flood attack

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the acute effect of the attacks on the residual energy of the network
where half of the energy is consumed before reaching 500 rounds
in the presence of attacks. The evolution of energy in this way
leads to the formation of several isolated areas and subsequently
affects the efficiency of the network.
In the following section, we present the main security
mechanisms used to counter these attacks.
5. Basic security mechanisms in WSNs
In the absence of strong security architecture, WSNs are targets
of several attacks that we presented previously in this paper. Most
of these attacks take advantage of cryptographic system failures to
derive the initial data (clear) or to find the used keys. We are
talking here about cryptanalysis. In this section, we talk about
cryptography and the cryptographic systems used to secure the
WSNs [
86
] [
87
].
Indeed, the cryptanalysis targets the encryption keys which are
based on cryptographic systems. These systems, that can be either
symmetric, asymmetric or hybrid, take care of the management
and distribution of the encryption keys [
88
] [
89
]. In the following,
we detail each of these classes.
5.1. Symmetric Cryptography in WSNs
Symmetric cryptography, shown in Figure 11, is the oldest
form of encryption where the same key is used between two
communicating nodes to encrypt and decrypt the data using a
symmetric encryption algorithm. In modern security techniques,
even symmetric encryption algorithms can be public. The major
disadvantage of this solution is that the pre-loaded key in the nodes
could lead to compromise the entire network through
compromised nodes. One of the proposed solutions to overcome
this limit is to establish symmetric encryption schemes based on
pair-wise keys rather than a single global key [
90
] [
91
].
Figure 11: Symmetric cryptography
5.2. Asymmetric Cryptography in WSNs
Contrary to symmetric cryptography, asymmetric
cryptography, also known as public-key cryptography, too heavy
used in WSNs, uses a pair of keys instead of one (public and
private). Asymmetric keys are generated in pairs. The message
encrypted by the public key will be decrypted by the private key.
Indeed, the public key of a node B, published between two
communicating nodes is used by the node A to encrypt a message
that will be decrypted by the node B through its secret private key
as shown in Figure 12 and vice versa. This encryption mechanism
allows not only the encryption of information but also the
guarantee the authentication of the nodes by using the signatures
and digital certificates. Slowness and resources consumption are
the major drawbacks of this encryption mechanism [
92
].
Figure 12: Asymmetric cryptography
5.3. Hybrid Cryptography in WSNs
Hybrid cryptography is a cryptographic system that combines
and benefits from the two cryptographic systems: asymmetric and
symmetric. Generally, asymmetric encryption, greedy in time and
resources, is used only to exchange a secret key in order to use
symmetric encryption afterwards.
5.4. Elliptic curve cryptography in WSNs
Elliptic Curve Cryptography (ECC) is becoming increasingly
popular as a security solution for WSNs. This technique is an
approach of public-key cryptography, it is based on elliptic curve
theory to create faster, smaller and more efficient encryption keys
with quite less key size and very low computational overhead. In
fact, the ECC generates keys through the properties of the elliptic
curve equation and the discrete logarithm of an elliptic curve must
be calculated for the decryption process which is much more
difficult than factoring.
5.5. Comparison of symmetric and asymmetric cryptographic
systems
Encryption algorithms can be evaluated in different parameters.
Table 3, provided by National Institute of Standards and
Technology NIST compares the encryption key size for RSA, ECC
(asymmetric) and AES (symmetric) shows the development of key
size compared to the security of an 80-bit symmetric key [
93
].
Table 3: Comparison of key length (bits) of the well-known symmetric and
asymmetric techniques [NIST]
Symmetric (AES)
RSA
ECC
80
1024
160
112
2048( x 2 )
224( x 1.4)
128
3072( x 3 )
256 ( x 1.6 )
192
7680( x 7.5 )
384( x 2.4 )
256
15360( x 15 )
521( x 3.2 )
Researchers agree that symmetric methods are faster and
require small keys e.g. a key size of 3072 bits with RSA, which is
equivalent to 256 bits with ECC, offers the same level of security
as a key of only 128 bits with AES. However, for a network of N
nodes, N-1 symmetric keys must be stored in each node, which
exceeds the memory capacity of sensors in networks that can
contain thousands of nodes as well as the key distribution problem.
Figure 13, developed from experiments done using MATLAB
R2015a [92] compares the energy consumed by RSA-1024 and
ECC-160 for signatures generation and verification, and the energy
cost of key exchanges excluding authentication and certificate
verification. It shows that RSA is characterized by a very
expensive signature operation and a small verification cost
contrary to ECDSA signatures which are significantly cheaper
than RSA. In the same way, key exchanging costs are significantly
cheaper with ECDSA than with RSA.

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As a result, the ECC has emerged as it offers keys that can be
much smaller than those required by the RSA algorithm, and at the
same time of size close to symmetrical solutions. These
characteristics make this technique more suitable for WSNs and
IoT applications but not optimal in its general form [
94
] [
95
].
Figure 13: Energy cost of digital signature and key exchange using RSA-1024
and ECDSA-160
Figure 14: Methods of management and distribution of encryption keys in WSNs
5.6. Management of encryption keys in WSNs
Key management in WSNs is one of the most difficult aspects
when configuring a security cryptographic system whether in a
symmetric, asymmetric or hybrid-based method. This task
includes the generation, distribution, verification and storage of
encryption keys so that each node will be equipped with a set of
secret keys or private/public pair of keys according to the adopted
system in a secure, private and safe manner.
Several management classifications and key distribution have
been proposed in the literature based on various technical and
functional criteria [
96
]. We propose in this work a new
classification based on the three previously proposed encryption
methods (symmetric, asymmetric and hybrid) as shown in Figure
14. In the following we detail each of these key distribution
methods.
5.7. Management of encryption key in symmetric patterns
The establishment of a common key between nodes in a WSNs
to securely communicate in a symmetric cryptographic-based
model is as follows: Before the nodes are deployed, the memory
of each node is initially equipped with several keys in a Key Pre-
distribution phase then it is the routing protocol that deals with the
common key management between the nodes after the deployment
in a key discovery process which makes it possible to constitute
secure paths between nodes. The pre-distribution of these keys can
be random or through an intermediary trust element of the network.
5.7.1. Random keys
The random pre-distribution of keys can be guaranteed by
probabilistic, deterministic or hybrid methods. In the following we
detail each of these methods
5.7.1.1. Deterministic methods
Deterministic methods require a large storage capacity because
several encryption keys deterministically generated are stored in
the memory of each node. They allow each node to establish a
unique key known as “pair-wise key” with any other node of the
network to establish a secure communication. Among the
proposed mechanisms we quote the deterministic method
proposed by Liu et al. [
97
] which is based on virtual spaces (logical
grids) containing the identifiers of the nodes. Thus, many groups
of sensor nodes are formed based on the positions of the nodes.
The pre-distribution of two encryption keys is thus necessary: “in-
group pre-distribution” making it possible to establish a unique
shared key (pair-wise key) between two nodes of the same group
and “cross-group pre-distribution” to establish a unique shared key
between two different groups.
5.7.1.2. Probabilistic methods
In probabilistic methods, each node in the network is equipped
with several encryption keys randomly chosen by the network
administrator before being deployed. Common keys are thus
installed in the memories of the nodes with a certain probability.
In [
98
], Jones et al. propose a secure probabilistic architecture
based on a probabilistic key distribution method. Indeed, each
sensor is loaded with a set of “m” encryption keys, randomly
selected from a set of “k” keys with a probability of matching "p"
between nodes. After deployment, the BS splits the network into
independent sectors and secret keys are distributed by the BS to
ensure secure communication.
0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
320
Signature
generation
Signature
Verification
Client Key
Exchange
Server Key
Exchange
Energy (mJ)
RSA-1024 ECDSA-160
Methods of
management
and
distribution
of
encryption
keys in
WSNs
Symmetric
Trust Center
(Trusted key)
Random keys
Deterministic
Probabilistic
Hybrid
Asymmetric
Pubic Key
Infrastructure
(PKI)
Node identity
Hybrid

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5.7.1.3. Hybrid methods
Hybrid pre-distribution methods combined and benefits from
the two previous methods, depending on the application to increase
connectivity between nodes while ensuring secure communication.
5.7.2. Trust Center
In this key pre-distribution model, a Trust Center e.g. the BS is
used either to store a copy of pre-loaded keys or to derive
encryption keys from a trusted key pre-loaded into the nodes. In a
Zigbee topology managed by the protocol stack known as ZigBee
[
99
] based on the IEEE 802.15.4 standard, the nodes can play three
roles: coordinator, routers, and sensors. The coordinator, placed in
a particular position in the network, plays the role of a Trust Center
(TC) and distributes keys that can be Link Key (LK), Network Key
(NK) or Master Key (MK) shared by one node respectively with
another node, with the entire network and for the establishment of
the key LK.
5.8. Management of encryption key in asymmetric patterns
Another way to establish a common key between two nodes or
a group of nodes in a WSN to secure communications is to use
schemes based on asymmetric systems as already explained. In the
following we detail the most know methods.
5.8.1. Public Key Infrastructure
Public Key Infrastructure (PKI) based specifically on
cryptography, are a set of protocols and services aiming to secure
communication in a network through various techniques such as
authentication, digital certificates, digital signatures etc. The Micro
Public Key Infrastructure (micro-PKI) method proposed by
Munivel et al. [
100
] for WSNs is based on two keys: a public key
loaded in each node before the deployment used to identify with
the BS and a private key used by the BS to decrypt the data sent by
the nodes. The PKI in this method ensures identification between
the nodes as well as with the BS.
5.8.2. Node identity
These methods seek to provide the same cryptographic services
as a PKI based solely on the node identity information in the
creation and establishment of cryptographic keys shared between
each pair of nodes in the network. These methods are known in
cryptography as the Identity-Based Non-Interactive Key
Distribution Scheme (ID-NIKDS) [
101
]. Among these methods
we quote the method proposed by Oliveira et al. [
102
] where each
node of the network has a unique identifier and a private key. A
unique secret key shared with another node of the network is
derived by knowing only its identifier.
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