![International Journal of Electrical and Computer Engineering (IJECE)
Vol. 13, No. 3, June 2023, pp. 3131∼3139
ISSN: 2088-8708, DOI: 10.11591/ijece.v13i3.pp3131-3139 ❒ 3131
Survey on data aggregation based security attacks in
wireless sensor network
Nikhath Tabassum 1
, Geetha D. Devanagavi2
, Rajashekhar C. Biradar1
, Chaya Ravindra1
1School of Electronics and Communication Engineering, REVA University, Bengaluru, India
2School of Computing and Information Technology, REVA University, Bengaluru, India
Article Info
Article history:
Received Aug 10, 2022
Revised Oct 16, 2022
Accepted Dec 2, 2022
Keywords:
Attacks in wireless sensor network
Black hole attack
Decryption
Encryption
Symmetric key
ABSTRACT
Wireless sensor network (WSN) has applications in military, health care, en-
vironmental monitoring, infrastructure, industrial and commercial applications.
The WSN is expected to maintain data integrity in all its network operations.
However, due to the nature of wireless connectivity, WSN is prone to various at-
tacks that alter or steal the data exchanged between the nodes. These attacks can
disrupt the network processes and also the accuracy of its results. In this survey
paper, we have reviewed various attacks available in the literature till date. We
have also listed existing methods that focus on data aggregation based security
mechanisms in WSN to counter the attacks. We have classified and compared
these methods owing to their encryption techniques. This paper intends to sup-
port researchers to understand the basic attacks prevalent in WSN and schemes
to counter such attacks.
This is an open access article under the CC BY-SA license.
Corresponding Author:
Nikhath Tabassum
School of Electronics and Communication Engineering, REVA University
Bengaluru, India
Email: nikhath.tabassum@reva.edu.in
1. INTRODUCTION
Wireless sensor network (WSN) is a collection of sensor nodes that collect the data from surround-
ings and communicate with each other. Such networks have applications in augmented reality under AI-5G
[1], thermoelectric powered smart building monitoring [2], marine environmental exploration and under water
military operations [3], civilian applications [4] and Internet of things [5]. Since the sensor nodes communicate
among themselves wirelessly and the sensor nodes are present in larger numbers and distributed over larger
area, they are prone to various attacks. Though the data is encrypted before transmission and decrypted after
reception, there are various attacks that can be launched on these sensor nodes to either corrupt the data that is
being transmitted or to capture/compromise the sensor node [6]. The corruption of data can be through addition
of fake packets, deletion of valid packets or by copying the information that is transmitted or hacking into the
encrypted message to alter the information contained in the packet. The nodes that are compromised include
those nodes whose identity has been stolen by malicious nodes [7]. Thus, the malicious nodes try to be a part
of the network with this stolen identity and disrupt the functions in the network [8]. The malicious nodes also
overwhelm the normal sensor nodes with fake packets so that the node’s memory is full and the valid packets
also gets dropped. Receiving the overwhelming amount of fake packets will also drain the battery of the nor-
mal nodes. The malicious nodes mislead the normal sensor nodes by pretending to be the closest neighbors or
convincing the nodes to choose malicious nodes in the pretext of having shortest route.
All these attacks by the malicious nodes have to be prevented by strengthening the encryption and
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decryption techniques, by identifying valid nodes and detecting compromised nodes by measuring packet drops
and battery depletion rate [9]. Electing trusted cluster head [10] who is aware of the position of its cluster
members [11] and secure routing path between cluster head and its members [12]. Also selecting secure
transmission path is important [13], [14].
In this survey paper, we have listed various security requirements in WSN, different types of attacks
and various methods/schemes that counter these attacks. We have classified these methods into different cat-
egories and compared them on the basis of encryption techniques and security requirements. The rest of the
paper is organized as follows: section 2 describes the attacks and schemes to counter the attacks, and section 3
concludes the review article.
2. ATTACKS AND SCHEMES TO COUNTER THE ATTACKS
In order for the WSN to work efficiently and correctly, the data collected and shared by the sensor
nodes must be protected. If a malicious node attacks a sensor node and corrupts the data, the results of the
operation for which the sensor nodes are deployed will be compromised. In this section, we discuss various
security requirements, data attacks and also some of the methods that counter these attacks.
2.1. Important security requirements in wireless sensor network (WSN)
Data gathered by sensor nodes is shared with the sink node or base station for further processing [15].
This process of data integration should be secure. It must not reveal the information of the sender or receiver
or the message content to unauthorised nodes. For WSN to be secure, it must satisfy the following security
requirements.
− Data confidentiality: The WSN must have data confidentiality. The unauthorized sensor node should not be
able to access the data shared between the authorized nodes [16].
− Availability: The data and services offered by the network should always be available to all the nodes [17].
− Data integrity: The data is expected to reach base station from sensor node in its original form without any
changes. Data integrity is crucial for decision making at the base station which receives the data from the
sensor nodes [18].
− Data privacy: There must be data privacy in wireless sensor network. The data of one sensor node must not
be disclosed to another neighboring node of the same network [19].
− Non repudiation: The sensor nodes must provide non repudiation as they cannot deny their participation in
the communication process [20].
− Data freshness: The WSN should maintain data freshness and discard the old and duplicate packets from
the network [21].
− Authenticity: The access control to the sensor nodes must be authenticated to avoid any malicious nodes
accessing the data [22]. The sensor nodes must be authenticated before the transmission or reception of
data [23].
2.2. Different types of attacks in wireless sensor network (WSN)
The sensor nodes are deployed in large numbers for environmental monitoring, data aggregation and
target tracking in public places and in hostile environments. This makes them vulnerable to attacks. The sensor
nodes have low processing power and small memory, due to which complex mechanism to prevent the data
attacks is not feasible. The most common attacks are listed below.
− Black hole attack: It consumes all the packets sent by the sensor nodes and removes them in pretext of
having best routes [24].
− Sinkhole attack: It is similar to black hole attack. In this type, the malicious node knows the exact position
of sink node. It tries to deviate the sensor node packets to itself in the pretext of reaching the sink node with
shortest path [25].
− Wormhole attack: Two malicious nodes create a wormhole channel between them. They claim that this
channel between is the best route and trick the other sensor nodes too to take this path. Once, the sensor
nodes take this path, the malicious nodes are able to read the data bytes transferred on this channel and can
change the traffic flow [26].
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− Selective forwarding attack: In this attack, particular types of packets are eliminated or packets addressed
to particular destination are removed. Instead of these missing packets, some other packets are sent to the
destination [27].
− Sybil attack: This attack seizes many of the valid identifiers in the network. If a node finds a sybil neighbor
node then the sensor node thinks that it is its nearest neighbors and chooses the sybil node as the next hop
neighbor. This attack induces fake packets in the network and disrupts the functioning of the network [28].
− Flooding attack: In this attack the malicious node tries to flood the memory of the target node by sending
connection request messages. So, the valid node cannot take up genuine request as its memory is full [29].
− Eavesdropping attack: The attacker tries to eavesdrop on the secure data being transmitted to a sensor node.
It then tries to use this data to isolate the node from the network. So, if the data is not properly encrypted it
can easily fall prey to this attack [30].
− Traffic analysis attack: In this type of attack, the attacker collects all the information of a sensor node with
respect to the message type, message length, and message pattern [31], [32].
− Node replication attack: It is similar to sybil attack, but in the attack the attacker tries to copy the memory
of a sensor node. It then infuses fake packets and disrupts the network functionality by deleting, modifying
the packets [33].
− Packet injection attack: The attacker forges valid data packets and injects into the network. These forged
data packets are hard to distinguish from the original data packets if the original data packets have weak
encryption [34].
− Packet duplication attack: In this attack a valid packet is duplicated and sent to a node repeatedly to drain
all its resources, thereby disrupting the network [35].
The various types of attacks are classified as active or passive, external or internal as in Table 1.
The active attacks are the ones that try to change the nature of the data by altering or modifying it. But the
passive attacks do not change the content, it only tries to copy the data. The external attacks are launched by
sensor nodes that are external to the network i.e not a part of the network. The internal attacks are launched
by malicious nodes that capture sensor nodes that are part of the network. The Figure 1 shows lists the data
aggregation schemes that employ various strategies to overcome the attacks. These have been classified based
on the topology of the network and the type of encryption used. In the next section we discuss the measures
taken by these methods to overcome the attacks.
2.3. Counter measures against various attacks
The attacks faced by the sensor nodes have to be prevented for secure transmission of the data among
the nodes. There are various schemes that effectively overcome various threats and attacks by malicious nodes
in the network. We have listed the counter measures carried by different schemes for different attacks in this
section.
2.3.1. Eavesdropping
To prevent eavesdropping, multi-functional secure data aggregation (MFSDA) [36] method utilizes a
homomorphic encryption method. As the attacker cannot have all the keys to encrypt the messages exchanged
between sensors, it can prevent the attacks caused by eavesdropping. Fog-assisted secure healthcare data
aggregation (FASHDA) [37] makes use of symmetric encryption techniques to maintain the confidentiality of
the message even if the attackers are eavesdropping. light-weight structure based data aggregation routing
(LSDAR) [38] have symmetric encryption and it is passed from one neighbor to another or utilize random
pairwise key based symmetric encryption method as in cluster-based private data aggregations (CSDAs) [39].
There are methods such as data aggregation scheme for heterogenous wireless sensor network (DAHWSN) [40]
where the encryption is done before the sensor nodes are included in the network. The base station stores the
key derivation function (KDF) in the sensor nodes. So, the keys are known to base station and sensor nodes only.
Instead of having encryption for the entire data, energy-efficient adaptive slice-based secure data aggregation
(EASBSDA) [41] has sensor nodes split their data into slices. These slices are encrypted using symmetric key
cryptography separately and transmit to the target nodes. In this way even if the attacker get eavesdrop message,
it gets only a slice of the information which cannot be constructed to get a complete message. A random key
management method as in energy-efficient and privacy-preserving data aggregation algorithm (EEPDA) [42]
is utilised or an elliptic curve based method for encryption in queries privacy-preserving mechanism for data
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aggregation (QPDA) [43] can also be utilized to overcome eavesdropping attack.
2.3.2. Sybil
In FASHDA [37] the sensor nodes insert hash value in the message packets so that the aggregators
can differentiate between valid and fake packets. In a cluster based topology as in DAHWSN [40] when a
data packet is sent to cluster head, the sensor node utilizes the time stamp and its identifier to indicate fresh
and valid packets. The cluster head verifies the data packets with respect to the signature of the sensor node.
This signature is calculated by sensor node based on the timestamp and secret key. In another cluster based
scheme in secure authentication with protected data aggregation scheme (SAPDAS) [44], each cluster member
calculates an hybrid medium access code (HMAC) value and includes this in the packet before transmitting
it to the cluster head. The cluster head in turn transmits these packets to the base station. The base station
then checks this HMAC value to validate the packets which can neutralize the attack. In reliable and secure
end-to-end data aggregation (RSDA) [45] data slicing and digital signature is used. It is very effective locally
but not effective for centralized process for authentication. Drawback is that since it is a centralized method,
locally the nodes cannot detect fake packets. So, in SCBFDA [46] a secondary message authentication code
(SECMAC) (message authentication code) value is calculated at each sensor node. On reception, the receiving
node also calculates the SECMAC value and verifies it. So it is easy to detect fake packets.
Table 1. Classification of different attacks
Number Method Active Passive External Internal
1 Black hole attack ✓ × ✓ ×
2 Sinkhole attack ✓ × ✓ ×
3 Wormhole attack ✓ × ✓ ×
4 Selective forwarding attack ✓ × ✓ ×
5 Sybil attack ✓ × ✓ ×
6 Flooding attack ✓ × ✓ ×
7 Eavesdropping attack × ✓ ✓ ×
8 Traffic Analysis attack × ✓ ✓ ×
9 Node replication attack ✓ × × ✓
10 Packet injection attack ✓ × ✓ ×
11 Packet duplication attack ✓ × ✓ ×
Tree based topology
FASHDA
SDAWS
RSDA
SCBFDA
QSDA
SAPDAS
LSDARS
EEPPDA
CSDAS
MFSDA
Cluster based
Tree cluster
based topology
End to end
Hop by hop
encryption
End to end
encryption
encryption
EASBSDA
DAHWSN
Hop by hop
encryption
topology
Classification of Data Aggregation Schemes
Figure 1. Classification of data aggregation schemes with respect to topology and encryption
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2.3.3. Node replication
In FASHDA [37] technique, the attackers can only access the secret key of the affected node and not
other nodes keys. So, it has a localized effect on network. But if it attacks the aggregator node, then it may
effect the functioning of the other nodes connected to the aggregator node and disrupt the network at a larger
scale. Therefore, the compromised node should be isolated which is not done effectively by FASHDA [37].
But if the aggregator node is a cluster head and it is attacked as in DAHWSN [40], the cluster head cannot send
fake packets to the base station because cluster member keys are not known to the cluster head but this attack
can very well delete all the packets that are received at cluster head therefore compromising the availability
of the packets. In recoverable concealed data aggregation scheme (RCDAS) [47] the attack is nullified as it is
uses digital signatures for authentication that identifies and blocks the fake malicious nodes.
2.3.4. Traffic analysis
In MFSD [36] the sinknode has the decryption keys, so it cannot access information such as message
length and pattern. In FASHDA [37], the encryption key is with the server and the attacker however can know
the aggregator node and server node identity and its location. But it can use this information to launch sinkhole
and sybil attacks. Each valid node calculates the signature based ID and inserts into the data packets as in
DAHWSN [40]. It utilizes homomorphic end to end encryption technique that will not allow the attacker to
know the content and hence the traffic in the network. In EASBSDA [41] and SAPDA [44] even if the attacker
almost accesses pairwise keys, it cannot have all the secret keys shared between the sensor nodes and hence
cannot detect traffic. Each node knows only its keys. Another way is to slice the data and encrypt it separately
as in CSDAS [39] and SAPDAS [44] have random pairwise keys shared between the neighboring nodes. Due
to data slicing and random key for ciphering, the traffic analysis becomes difficult. But, if there are cluster
heads changing constantly, so getting to know the cluster head and attacking will take long time and difficult to
analyze traffic.
2.3.5. Black hole attack
In this attack either the malicious node deletes all the packets directed towards it or it makes the nodes
believe that it is part of the best route and introduces fake packets in bulk such that the valid router drops the
packets as it will be overwhelming for it to handle. In, DAHWSN [40], the network topology has clusters.
The cluster head verifies the identity of its cluster members by signature verification. So the malicious nodes
will not be able to send fake packets. The clsuter head when it sends the packets to the base station, the base
station verifies the identity of the cluster head by batch verification signature. So, the malicious nodes can be
detected if it sends fake packets. In RSDA [45] the data is segregated into 4 slices, each slice is encrypted
separately. The transmitting node sends 2 encrypted packets each to two aggregators with digital signatures.
So, if a malicious node persuades the aggregator to share the data, the data received at the base station by the
second aggregator will be incomplete without the first aggregator data. So the base station knows if the data
is fake. For authentication, in FASHDA [37] each node has a valid hash value inserted in the packets, so that
the aggregator nodes can detect the authentic packets and discard fake packets. In SAPDA [44] it generates
a hybrid medium access code (HMAC) value depending on the original data and time stamp and in SDAWS
[48] this scheme utilizes water marking scheme to validate the nodes. In a cluster head based topology as
in SAPDAS [44] the cluster heads communicate with the other trusted cluster head only. The gateway node
authenticates the cluster heads. The base station receives the data only from authenticated cluster heads. The
base station generates KDF as in DAHWSN [40] and embeds in each sensor nodes memory. The base station
also generates private key and secret key along with new identifier for each sensor node. This is known only
to the sensor node and base station. A sensor node when it transmits a packet to the cluster head, it calculates
a signature based on secret key time stamp and its ID, which is again verified by cluster head to confirm the
validity of the sensor node.
2.3.6. Flooding attack
In the flooding attack, duplicate packets are generated in bulk to drain the sensor node of its battery
and memory. To avod this, in FASHDA [37] and SAPDAS [44] when a aggregator node receives data from
sensor node, it checks for the time stamp to confirm whether it is a fresh packet or a duplicate packet. If it is a
duplicate packet, it is discarded and if the packet happens to be a fresh packet, then it is stored.
Survey on data aggregation based security attacks in wireless sensor network (Nikhath Tabassum)](https://image.slidesharecdn.com/7529226emfupdate-230320062733-6b80b168/85/Survey-on-data-aggregation-based-security-attacks-in-wireless-sensor-network-5-320.jpg)
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2.3.7. Packet alteration, packet injection and packet duplication
In FASHDA [37] fake packets are detected by the sensor node. If the attacker resends old packets,
it is identified through time stamp checking and in DAHWSN [40], it will check for cluster head in the valid
sensor list which is maintained by the base station and can overcome packet alteration sent by malicious nodes.
The Table 2 compares various algorithms based on the different security requirements. Almost all the methods
preserve the data confidentiality and privacy of data. The various schemes have been classified depending
on the type of the encryption utilized as in Table 3. Symmetric encryption has the same key for encryption
and decryption [49], [50]. The key must be transmitted securely between the sensor nodes. In asymmetric
encryption [51] there are two keys namely the public key and secret key. If the public key is used for encryption,
then the secret key will be used for decryption.
Table 2. Comparison of different schemes with respect to security requirements
Number Method Availability Non repudiation Privacy Data freshness Authentication Access control Data integrity Data
Confidentiality
1 MFSDA × × ✓ × × × × ✓
2 FASHDA × × ✓ ✓ × × ✓ ✓
3 DAHWSN ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
4 SDAWS × × ✓ × × × ✓ ✓
5 RSDA ✓ ✓ ✓ × ✓ ✓ ✓ ✓
6 EASBSDA × × ✓ × × × × ✓
7 SCBFDA × × ✓ × ✓ ✓ ✓ ✓
8 SAPDAS ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
9 EEPPDA × × ✓ × × × × ✓
10 QPDA × × ✓ × × × × ✓
11 LSDAR × × ✓ × × × × ✓
12 CSDAS × × ✓ × × × × ✓
Table 3. Comparison of cryptography techniques for different schemes
Number Method Symmetric key encryption Asymmetric key encryption
1 MFSDA × ✓
2 FASHDA ✓ ×
3 DAHWSN ✓ ×
4 SDAWS × ✓
5 RSDA × ✓
6 EASBSDA ✓ ×
7 SCBFDA × ✓
8 SAPDAS ✓ ×
9 EEPPDA ✓ ×
10 QPDA × ✓
11 LSDAR ✓ ×
12 CSDAS ✓ ×
2.3.8. Discussions
The symmetric key cryptographic technique is simpler and has less computation overhead. But the
security provided is less compared to asymmetric key cryptographic technique. The asymmetric key cryptog-
raphy has high computation overhead, complex and consumes more energy. To conserve the battery power, the
topology of the network is also a contributor. The tree topology is structured and has a fixed hierarchy, but has
higher packet loss and drains the battery power of the sensor nodes as the paths are fixed. In case of cluster
based topology all the cluster members communicate with cluster head only. The cluster head should have high
energy and must be able to handle greater computational overhead. So, a hybrid tree-cluster based topology
will be more desirable to overcome the disadvantages of tree based and cluster based topologies.
3. CONCLUSION
The security in wireless sensor networks often gets compromised due to the constraints like limited
battery power, smaller memory and lesser computational capacity to carry out complex, encryption and de-
cryption techniques. With these limitations, there are schemes that efficiently overcome the various attacks that
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sensor nodes encounter. We have discussed various attacks in WSN. We have also discussed and classified the
aggregation schemes based on their topology and encryption techniques.
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BIOGRAPHIES OF AUTHORS
Nikhath Tabassum received her Ph.D. in 2021. She is currently working as Assistant
Professor in REVA University. She has published papers in reputed international journals and confer-
ences. Her research interest include wireless sensor networks, ad-hoc networks and network security.
She can be contacted at email: nikhath.tabassum@reva.edu.
Geetha D. Devanagavi received her Ph.D in 2014. She is currently a Professor at REVA
university. She has 26 years of teaching experience. Her research interest include wireless sen-
sor networks, network security, and computer networks. She has good number of publications in
reputed international journals. She has guided 4 Ph.D. scholars. She can be contacted at email:
dgeetha@reva.edu.in.
Rajashekhar C. Biradar is currently working as Pro Vice Chancellor at REVA university,
India. He has 32 years of teaching experience. His research interest include Ad-hoc networks, sensor
networks, mesh networks, network security, and wireless sensor networks. He has good number of
publications in reputed international journals. He has published 65 papers in peer reviewed national
and international journals, 73 papers in reputed national and international conferences and 4 book
chapters. He has guided 7 Ph.D. scholars. He received “Best Ph.D. Thesis Supervisor Award, 2021”
by BITES, Govt. of Karnataka, India. He has been listed in Marquis’ Who’s Who in the World (2012
Edition), USA and Top 100 Engineers by IBC, UK. As per Google Scholar, he has more than 1,900
citations with h-index of 23. He can be contacted at email: provc@reva.edu.in.
Chaya Ravindra is assistant professor in REVA University. She has completed Ph.D.
in the year 2021. She has published 15 international journals and 4 international conference papers.
Her research interest are in optical communication and wireless sensor network. She is a member of
UACEE and IETE. She can be contacted at email: chaya@reva.edu.in.
Survey on data aggregation based security attacks in wireless sensor network (Nikhath Tabassum)](https://image.slidesharecdn.com/7529226emfupdate-230320062733-6b80b168/85/Survey-on-data-aggregation-based-security-attacks-in-wireless-sensor-network-9-320.jpg)
Survey on data aggregation based security attacks in wireless sensor network
- 1. International Journal of Electrical and Computer Engineering (IJECE) Vol. 13, No. 3, June 2023, pp. 3131∼3139 ISSN: 2088-8708, DOI: 10.11591/ijece.v13i3.pp3131-3139 ❒ 3131 Survey on data aggregation based security attacks in wireless sensor network Nikhath Tabassum 1 , Geetha D. Devanagavi2 , Rajashekhar C. Biradar1 , Chaya Ravindra1 1School of Electronics and Communication Engineering, REVA University, Bengaluru, India 2School of Computing and Information Technology, REVA University, Bengaluru, India Article Info Article history: Received Aug 10, 2022 Revised Oct 16, 2022 Accepted Dec 2, 2022 Keywords: Attacks in wireless sensor network Black hole attack Decryption Encryption Symmetric key ABSTRACT Wireless sensor network (WSN) has applications in military, health care, en- vironmental monitoring, infrastructure, industrial and commercial applications. The WSN is expected to maintain data integrity in all its network operations. However, due to the nature of wireless connectivity, WSN is prone to various at- tacks that alter or steal the data exchanged between the nodes. These attacks can disrupt the network processes and also the accuracy of its results. In this survey paper, we have reviewed various attacks available in the literature till date. We have also listed existing methods that focus on data aggregation based security mechanisms in WSN to counter the attacks. We have classified and compared these methods owing to their encryption techniques. This paper intends to sup- port researchers to understand the basic attacks prevalent in WSN and schemes to counter such attacks. This is an open access article under the CC BY-SA license. Corresponding Author: Nikhath Tabassum School of Electronics and Communication Engineering, REVA University Bengaluru, India Email: [email protected] 1. INTRODUCTION Wireless sensor network (WSN) is a collection of sensor nodes that collect the data from surround- ings and communicate with each other. Such networks have applications in augmented reality under AI-5G [1], thermoelectric powered smart building monitoring [2], marine environmental exploration and under water military operations [3], civilian applications [4] and Internet of things [5]. Since the sensor nodes communicate among themselves wirelessly and the sensor nodes are present in larger numbers and distributed over larger area, they are prone to various attacks. Though the data is encrypted before transmission and decrypted after reception, there are various attacks that can be launched on these sensor nodes to either corrupt the data that is being transmitted or to capture/compromise the sensor node [6]. The corruption of data can be through addition of fake packets, deletion of valid packets or by copying the information that is transmitted or hacking into the encrypted message to alter the information contained in the packet. The nodes that are compromised include those nodes whose identity has been stolen by malicious nodes [7]. Thus, the malicious nodes try to be a part of the network with this stolen identity and disrupt the functions in the network [8]. The malicious nodes also overwhelm the normal sensor nodes with fake packets so that the node’s memory is full and the valid packets also gets dropped. Receiving the overwhelming amount of fake packets will also drain the battery of the nor- mal nodes. The malicious nodes mislead the normal sensor nodes by pretending to be the closest neighbors or convincing the nodes to choose malicious nodes in the pretext of having shortest route. All these attacks by the malicious nodes have to be prevented by strengthening the encryption and Journal homepage: http://ijece.iaescore.com
- 2. 3132 ❒ ISSN: 2088-8708 decryption techniques, by identifying valid nodes and detecting compromised nodes by measuring packet drops and battery depletion rate [9]. Electing trusted cluster head [10] who is aware of the position of its cluster members [11] and secure routing path between cluster head and its members [12]. Also selecting secure transmission path is important [13], [14]. In this survey paper, we have listed various security requirements in WSN, different types of attacks and various methods/schemes that counter these attacks. We have classified these methods into different cat- egories and compared them on the basis of encryption techniques and security requirements. The rest of the paper is organized as follows: section 2 describes the attacks and schemes to counter the attacks, and section 3 concludes the review article. 2. ATTACKS AND SCHEMES TO COUNTER THE ATTACKS In order for the WSN to work efficiently and correctly, the data collected and shared by the sensor nodes must be protected. If a malicious node attacks a sensor node and corrupts the data, the results of the operation for which the sensor nodes are deployed will be compromised. In this section, we discuss various security requirements, data attacks and also some of the methods that counter these attacks. 2.1. Important security requirements in wireless sensor network (WSN) Data gathered by sensor nodes is shared with the sink node or base station for further processing [15]. This process of data integration should be secure. It must not reveal the information of the sender or receiver or the message content to unauthorised nodes. For WSN to be secure, it must satisfy the following security requirements. − Data confidentiality: The WSN must have data confidentiality. The unauthorized sensor node should not be able to access the data shared between the authorized nodes [16]. − Availability: The data and services offered by the network should always be available to all the nodes [17]. − Data integrity: The data is expected to reach base station from sensor node in its original form without any changes. Data integrity is crucial for decision making at the base station which receives the data from the sensor nodes [18]. − Data privacy: There must be data privacy in wireless sensor network. The data of one sensor node must not be disclosed to another neighboring node of the same network [19]. − Non repudiation: The sensor nodes must provide non repudiation as they cannot deny their participation in the communication process [20]. − Data freshness: The WSN should maintain data freshness and discard the old and duplicate packets from the network [21]. − Authenticity: The access control to the sensor nodes must be authenticated to avoid any malicious nodes accessing the data [22]. The sensor nodes must be authenticated before the transmission or reception of data [23]. 2.2. Different types of attacks in wireless sensor network (WSN) The sensor nodes are deployed in large numbers for environmental monitoring, data aggregation and target tracking in public places and in hostile environments. This makes them vulnerable to attacks. The sensor nodes have low processing power and small memory, due to which complex mechanism to prevent the data attacks is not feasible. The most common attacks are listed below. − Black hole attack: It consumes all the packets sent by the sensor nodes and removes them in pretext of having best routes [24]. − Sinkhole attack: It is similar to black hole attack. In this type, the malicious node knows the exact position of sink node. It tries to deviate the sensor node packets to itself in the pretext of reaching the sink node with shortest path [25]. − Wormhole attack: Two malicious nodes create a wormhole channel between them. They claim that this channel between is the best route and trick the other sensor nodes too to take this path. Once, the sensor nodes take this path, the malicious nodes are able to read the data bytes transferred on this channel and can change the traffic flow [26]. Int J Elec & Comp Eng, Vol. 13, No. 3, June 2023: 3131-3139
- 3. Int J Elec & Comp Eng ISSN: 2088-8708 ❒ 3133 − Selective forwarding attack: In this attack, particular types of packets are eliminated or packets addressed to particular destination are removed. Instead of these missing packets, some other packets are sent to the destination [27]. − Sybil attack: This attack seizes many of the valid identifiers in the network. If a node finds a sybil neighbor node then the sensor node thinks that it is its nearest neighbors and chooses the sybil node as the next hop neighbor. This attack induces fake packets in the network and disrupts the functioning of the network [28]. − Flooding attack: In this attack the malicious node tries to flood the memory of the target node by sending connection request messages. So, the valid node cannot take up genuine request as its memory is full [29]. − Eavesdropping attack: The attacker tries to eavesdrop on the secure data being transmitted to a sensor node. It then tries to use this data to isolate the node from the network. So, if the data is not properly encrypted it can easily fall prey to this attack [30]. − Traffic analysis attack: In this type of attack, the attacker collects all the information of a sensor node with respect to the message type, message length, and message pattern [31], [32]. − Node replication attack: It is similar to sybil attack, but in the attack the attacker tries to copy the memory of a sensor node. It then infuses fake packets and disrupts the network functionality by deleting, modifying the packets [33]. − Packet injection attack: The attacker forges valid data packets and injects into the network. These forged data packets are hard to distinguish from the original data packets if the original data packets have weak encryption [34]. − Packet duplication attack: In this attack a valid packet is duplicated and sent to a node repeatedly to drain all its resources, thereby disrupting the network [35]. The various types of attacks are classified as active or passive, external or internal as in Table 1. The active attacks are the ones that try to change the nature of the data by altering or modifying it. But the passive attacks do not change the content, it only tries to copy the data. The external attacks are launched by sensor nodes that are external to the network i.e not a part of the network. The internal attacks are launched by malicious nodes that capture sensor nodes that are part of the network. The Figure 1 shows lists the data aggregation schemes that employ various strategies to overcome the attacks. These have been classified based on the topology of the network and the type of encryption used. In the next section we discuss the measures taken by these methods to overcome the attacks. 2.3. Counter measures against various attacks The attacks faced by the sensor nodes have to be prevented for secure transmission of the data among the nodes. There are various schemes that effectively overcome various threats and attacks by malicious nodes in the network. We have listed the counter measures carried by different schemes for different attacks in this section. 2.3.1. Eavesdropping To prevent eavesdropping, multi-functional secure data aggregation (MFSDA) [36] method utilizes a homomorphic encryption method. As the attacker cannot have all the keys to encrypt the messages exchanged between sensors, it can prevent the attacks caused by eavesdropping. Fog-assisted secure healthcare data aggregation (FASHDA) [37] makes use of symmetric encryption techniques to maintain the confidentiality of the message even if the attackers are eavesdropping. light-weight structure based data aggregation routing (LSDAR) [38] have symmetric encryption and it is passed from one neighbor to another or utilize random pairwise key based symmetric encryption method as in cluster-based private data aggregations (CSDAs) [39]. There are methods such as data aggregation scheme for heterogenous wireless sensor network (DAHWSN) [40] where the encryption is done before the sensor nodes are included in the network. The base station stores the key derivation function (KDF) in the sensor nodes. So, the keys are known to base station and sensor nodes only. Instead of having encryption for the entire data, energy-efficient adaptive slice-based secure data aggregation (EASBSDA) [41] has sensor nodes split their data into slices. These slices are encrypted using symmetric key cryptography separately and transmit to the target nodes. In this way even if the attacker get eavesdrop message, it gets only a slice of the information which cannot be constructed to get a complete message. A random key management method as in energy-efficient and privacy-preserving data aggregation algorithm (EEPDA) [42] is utilised or an elliptic curve based method for encryption in queries privacy-preserving mechanism for data Survey on data aggregation based security attacks in wireless sensor network (Nikhath Tabassum)
- 4. 3134 ❒ ISSN: 2088-8708 aggregation (QPDA) [43] can also be utilized to overcome eavesdropping attack. 2.3.2. Sybil In FASHDA [37] the sensor nodes insert hash value in the message packets so that the aggregators can differentiate between valid and fake packets. In a cluster based topology as in DAHWSN [40] when a data packet is sent to cluster head, the sensor node utilizes the time stamp and its identifier to indicate fresh and valid packets. The cluster head verifies the data packets with respect to the signature of the sensor node. This signature is calculated by sensor node based on the timestamp and secret key. In another cluster based scheme in secure authentication with protected data aggregation scheme (SAPDAS) [44], each cluster member calculates an hybrid medium access code (HMAC) value and includes this in the packet before transmitting it to the cluster head. The cluster head in turn transmits these packets to the base station. The base station then checks this HMAC value to validate the packets which can neutralize the attack. In reliable and secure end-to-end data aggregation (RSDA) [45] data slicing and digital signature is used. It is very effective locally but not effective for centralized process for authentication. Drawback is that since it is a centralized method, locally the nodes cannot detect fake packets. So, in SCBFDA [46] a secondary message authentication code (SECMAC) (message authentication code) value is calculated at each sensor node. On reception, the receiving node also calculates the SECMAC value and verifies it. So it is easy to detect fake packets. Table 1. Classification of different attacks Number Method Active Passive External Internal 1 Black hole attack ✓ × ✓ × 2 Sinkhole attack ✓ × ✓ × 3 Wormhole attack ✓ × ✓ × 4 Selective forwarding attack ✓ × ✓ × 5 Sybil attack ✓ × ✓ × 6 Flooding attack ✓ × ✓ × 7 Eavesdropping attack × ✓ ✓ × 8 Traffic Analysis attack × ✓ ✓ × 9 Node replication attack ✓ × × ✓ 10 Packet injection attack ✓ × ✓ × 11 Packet duplication attack ✓ × ✓ × Tree based topology FASHDA SDAWS RSDA SCBFDA QSDA SAPDAS LSDARS EEPPDA CSDAS MFSDA Cluster based Tree cluster based topology End to end Hop by hop encryption End to end encryption encryption EASBSDA DAHWSN Hop by hop encryption topology Classification of Data Aggregation Schemes Figure 1. Classification of data aggregation schemes with respect to topology and encryption Int J Elec & Comp Eng, Vol. 13, No. 3, June 2023: 3131-3139
- 5. Int J Elec & Comp Eng ISSN: 2088-8708 ❒ 3135 2.3.3. Node replication In FASHDA [37] technique, the attackers can only access the secret key of the affected node and not other nodes keys. So, it has a localized effect on network. But if it attacks the aggregator node, then it may effect the functioning of the other nodes connected to the aggregator node and disrupt the network at a larger scale. Therefore, the compromised node should be isolated which is not done effectively by FASHDA [37]. But if the aggregator node is a cluster head and it is attacked as in DAHWSN [40], the cluster head cannot send fake packets to the base station because cluster member keys are not known to the cluster head but this attack can very well delete all the packets that are received at cluster head therefore compromising the availability of the packets. In recoverable concealed data aggregation scheme (RCDAS) [47] the attack is nullified as it is uses digital signatures for authentication that identifies and blocks the fake malicious nodes. 2.3.4. Traffic analysis In MFSD [36] the sinknode has the decryption keys, so it cannot access information such as message length and pattern. In FASHDA [37], the encryption key is with the server and the attacker however can know the aggregator node and server node identity and its location. But it can use this information to launch sinkhole and sybil attacks. Each valid node calculates the signature based ID and inserts into the data packets as in DAHWSN [40]. It utilizes homomorphic end to end encryption technique that will not allow the attacker to know the content and hence the traffic in the network. In EASBSDA [41] and SAPDA [44] even if the attacker almost accesses pairwise keys, it cannot have all the secret keys shared between the sensor nodes and hence cannot detect traffic. Each node knows only its keys. Another way is to slice the data and encrypt it separately as in CSDAS [39] and SAPDAS [44] have random pairwise keys shared between the neighboring nodes. Due to data slicing and random key for ciphering, the traffic analysis becomes difficult. But, if there are cluster heads changing constantly, so getting to know the cluster head and attacking will take long time and difficult to analyze traffic. 2.3.5. Black hole attack In this attack either the malicious node deletes all the packets directed towards it or it makes the nodes believe that it is part of the best route and introduces fake packets in bulk such that the valid router drops the packets as it will be overwhelming for it to handle. In, DAHWSN [40], the network topology has clusters. The cluster head verifies the identity of its cluster members by signature verification. So the malicious nodes will not be able to send fake packets. The clsuter head when it sends the packets to the base station, the base station verifies the identity of the cluster head by batch verification signature. So, the malicious nodes can be detected if it sends fake packets. In RSDA [45] the data is segregated into 4 slices, each slice is encrypted separately. The transmitting node sends 2 encrypted packets each to two aggregators with digital signatures. So, if a malicious node persuades the aggregator to share the data, the data received at the base station by the second aggregator will be incomplete without the first aggregator data. So the base station knows if the data is fake. For authentication, in FASHDA [37] each node has a valid hash value inserted in the packets, so that the aggregator nodes can detect the authentic packets and discard fake packets. In SAPDA [44] it generates a hybrid medium access code (HMAC) value depending on the original data and time stamp and in SDAWS [48] this scheme utilizes water marking scheme to validate the nodes. In a cluster head based topology as in SAPDAS [44] the cluster heads communicate with the other trusted cluster head only. The gateway node authenticates the cluster heads. The base station receives the data only from authenticated cluster heads. The base station generates KDF as in DAHWSN [40] and embeds in each sensor nodes memory. The base station also generates private key and secret key along with new identifier for each sensor node. This is known only to the sensor node and base station. A sensor node when it transmits a packet to the cluster head, it calculates a signature based on secret key time stamp and its ID, which is again verified by cluster head to confirm the validity of the sensor node. 2.3.6. Flooding attack In the flooding attack, duplicate packets are generated in bulk to drain the sensor node of its battery and memory. To avod this, in FASHDA [37] and SAPDAS [44] when a aggregator node receives data from sensor node, it checks for the time stamp to confirm whether it is a fresh packet or a duplicate packet. If it is a duplicate packet, it is discarded and if the packet happens to be a fresh packet, then it is stored. Survey on data aggregation based security attacks in wireless sensor network (Nikhath Tabassum)
- 6. 3136 ❒ ISSN: 2088-8708 2.3.7. Packet alteration, packet injection and packet duplication In FASHDA [37] fake packets are detected by the sensor node. If the attacker resends old packets, it is identified through time stamp checking and in DAHWSN [40], it will check for cluster head in the valid sensor list which is maintained by the base station and can overcome packet alteration sent by malicious nodes. The Table 2 compares various algorithms based on the different security requirements. Almost all the methods preserve the data confidentiality and privacy of data. The various schemes have been classified depending on the type of the encryption utilized as in Table 3. Symmetric encryption has the same key for encryption and decryption [49], [50]. The key must be transmitted securely between the sensor nodes. In asymmetric encryption [51] there are two keys namely the public key and secret key. If the public key is used for encryption, then the secret key will be used for decryption. Table 2. Comparison of different schemes with respect to security requirements Number Method Availability Non repudiation Privacy Data freshness Authentication Access control Data integrity Data Confidentiality 1 MFSDA × × ✓ × × × × ✓ 2 FASHDA × × ✓ ✓ × × ✓ ✓ 3 DAHWSN ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ 4 SDAWS × × ✓ × × × ✓ ✓ 5 RSDA ✓ ✓ ✓ × ✓ ✓ ✓ ✓ 6 EASBSDA × × ✓ × × × × ✓ 7 SCBFDA × × ✓ × ✓ ✓ ✓ ✓ 8 SAPDAS ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ 9 EEPPDA × × ✓ × × × × ✓ 10 QPDA × × ✓ × × × × ✓ 11 LSDAR × × ✓ × × × × ✓ 12 CSDAS × × ✓ × × × × ✓ Table 3. Comparison of cryptography techniques for different schemes Number Method Symmetric key encryption Asymmetric key encryption 1 MFSDA × ✓ 2 FASHDA ✓ × 3 DAHWSN ✓ × 4 SDAWS × ✓ 5 RSDA × ✓ 6 EASBSDA ✓ × 7 SCBFDA × ✓ 8 SAPDAS ✓ × 9 EEPPDA ✓ × 10 QPDA × ✓ 11 LSDAR ✓ × 12 CSDAS ✓ × 2.3.8. Discussions The symmetric key cryptographic technique is simpler and has less computation overhead. But the security provided is less compared to asymmetric key cryptographic technique. The asymmetric key cryptog- raphy has high computation overhead, complex and consumes more energy. To conserve the battery power, the topology of the network is also a contributor. The tree topology is structured and has a fixed hierarchy, but has higher packet loss and drains the battery power of the sensor nodes as the paths are fixed. In case of cluster based topology all the cluster members communicate with cluster head only. The cluster head should have high energy and must be able to handle greater computational overhead. So, a hybrid tree-cluster based topology will be more desirable to overcome the disadvantages of tree based and cluster based topologies. 3. CONCLUSION The security in wireless sensor networks often gets compromised due to the constraints like limited battery power, smaller memory and lesser computational capacity to carry out complex, encryption and de- cryption techniques. With these limitations, there are schemes that efficiently overcome the various attacks that Int J Elec & Comp Eng, Vol. 13, No. 3, June 2023: 3131-3139
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