# BC-IoDT: Blockchain-based Framework for Authentication in Internet of Drone
Things

Junaid Akram  The University of SydneySydneyAustralia<EMAIL_ADDRESS>,
Awais Akram  COMSATS University IslamabadVehariPakistan
<EMAIL_ADDRESS>,  Rutvij H. Jhaveri  Pandit Deendayal Energy
UniversityGujarat India<EMAIL_ADDRESS>,  Mamoun Alazab
Charles Darwin UniversityDarwinAustralia<EMAIL_ADDRESS>and  Haoran Chi
Universidade de AveiroAveiroPortugal<EMAIL_ADDRESS>
(2022)

###### Abstract.

We leverage blockchain technology for drone node authentication in internet of
drone things (IoDT). During the authentication procedure, the credentials of
drone nodes are examined to remove malicious nodes from the system. In IoDT,
drones are responsible for gathering data and transmitting it to cluster heads
(CHs) for further processing. The CH collects and organizes data. Due to
computational load, their energy levels rapidly deplete. To overcome this
problem, we present a low-energy adaptive clustering hierarchy (R2D) protocol
based on distance, degree, and residual energy. R2D is used to replace CHs
with normal nodes based on the biggest residual energy, the degree, and the
shortest distance from BS. The cost of keeping a big volume of data on the
blockchain is high. We employ the Interplanetary File System (IPFS), to
address this issue. Moreover, IPFS protects user data using the industry-
standard encryption technique AES-128. This standard compares well to other
current encryption methods. Using a consensus mechanism based on proof of work
requires a high amount of computing resources for transaction verification.
The suggested approach leverages a consensus mechanism known as proof of
authority (PoA) to address this problem . The results of the simulations
indicate that the suggested system model functions effectively and
efficiently. A formal security analysis is conducted to assess the smart
contract’s resistance to attacks.

IoDT, Access Control, security, consensus, Cluster Head

††journalyear: 2022††copyright: acmcopyright††conference: ACM MobiCom Workshop
on Drone Assisted Wireless Communications for 5G and Beyond; October 17, 2022;
Sydney, NSW, Australia††booktitle: ACM MobiCom Workshop on Drone Assisted
Wireless Communications for 5G and Beyond (DroneCom ’22), October 17, 2022,
Sydney, NSW, Australia††price: 15.00††doi: 10.1145/3555661.3560874††isbn:
978-1-4503-9514-4/22/10††ccs: Security and privacy Authentication

##  1\. Introduction

The Internet of drone things (IoDT) refers to the infrastructure currently
being developed to allow anyone to control and access drones over the internet
(Hussain et al., 2021). In reality, drones are becoming more common consumer
commodities, enabling any user to do a range of tasks in regulated airspace.
Despite the fact that technology has enabled mass manufacture of onboard UAV
components like CPUs, sensors, storage, and battery life, the performance
constraints of these components have decreased expectations(Javed et al.,
2021; Akram et al., 2018). With IoDT, drones and cloud mobility capabilities
may be paired, allowing for remote access and operation, scalability in
offloading, and cloud storage of data acquired from a great distance.

Because IoDT can gather environmental data, several companies, such as those
dealing with energy trading, surveillance, smart grids, etc, may profit from
it (Tahir et al., 2021; Malik et al., 2020; Wang et al., 2021). It connects to
the Internet and automates the monitoring infrastructure without assistance
from a third party. The drones of the IoDT network are responsible for
environmental monitoring. However, drones in IoDT encounter obstacles such as
non-repudiation, restricted resources, and the existence of malicious nodes.
Numerous solutions (Kar et al., 2021; Munawar et al., 2022) are presented as
potential solutions to the aforementioned problems. However, difficulties like
single point of failure (SPOF) and performance bottlenecks develop owing to
the centralized structure of these studies.

Using blockchain technology, researchers have developed a variety of solutions
to remove the need for intermediaries in IoDT, hence eliminating the
aforementioned difficulties. Blockchain technology is a secure, distributed
ledger that avoids, among other possible problems, centralized authority and
third-party participation. Additionally, blockchain’s usage of a distributed
and immutable ledger helps alleviate trust difficulties between organizations
that were previously unknown. As a critical component of the network
architecture, miners validate the legitimacy of all transactions conducted by
nodes. Miners use several consensus methods, including proof of work (PoW),
proof of authority (PoA), proof of stake, to validate the authenticity of
these transactions. Proof of work (PoW) and proof of authority (PoA) are two
examples. In the PoW method, each network node contributes to the solution of
the mathematical problem. The first node to answer the challenge is
responsible for transaction verification. First, the transactions are
validated for correctness before being added to the blockchain. Moreover,
blockchain makes use of smart contracts, the purpose of which is to finalize
all rules and conditions. In addition, it removes the need for an
intermediary. In addition, blockchain ensures network security by evaluating
the trust between nodes, and by detecting malicious nodes using the Merkle
tree (Goyat et al., 2020).

Multiple blockchain-based solutions for scalability concerns, high costs, and
single points of failure have been suggested (Cui et al., 2020). However,
blockchain is a highly expensive storage method, and all of these networks
store their data there. Currently, it costs $14,151.68 to store one megabyte
of data on a blockchain network. In addition, a proof-of-work consensus
mechanism is used in (Cui et al., 2020), which is inappropriate in a low-
resource context.

In the context of IoDT networks, routing refers to the process by which
individual nodes establish connections with one another and transfer data from
its source to its eventual destination. Different nodes within the IoDT,
including drones, cluster heads (CH), and base stations (BSs), supervise the
transfer of data . It is the responsibility of the CHs to do any required data
processing before transmitting it to the BSs (Haseeb et al., 2019; Mehmood et
al., 2018; Khan et al., 2021; Xu et al., 2021). However, there are no
authenticated network nodes. Since any node may get network access, any
harmful action is conceivable. Moreover, data storage on a blockchain is
costly since no cost-effective storage strategy is presented in (Haseeb et
al., 2019). Since blockchains are intended to record transactions in
perpetuity, the problem of inadequate capacity to store these data quickly
becomes apparent. In an IoDT configuration, an excessive energy drain on CHs
may also affect network performance. In (Cui et al., 2020), no new CH
selection processes are suggested. In order to add new blocks to the
blockchain and validate transactions, PoW needs miners to solve this problem.
This mining procedure is time-consuming due to the intricacy of the underlying
problem, which increases the network’s computational expenses over time.

The main contributions of this work are as follows:

  * •

IPFS is used for IoDT’s distributed storage requirements. A payment scheme is
recommended as an incentive for archival use of IPFS.

  * •

To exclude untrustworthy nodes, each node’s identification is verified. The
suggested LEACH technique, named ”R2D”, identifies and selects CHs from drones
using the least distance, highest degree, and maximum residual energy.

  * •

Blockchain technology is used for secure service provisioning systems, with
the suggestion that an advanced symmetric encryption technique with a 128-bit
key be employed to protect sensitive data.

  * •

For the purpose of determining the validity of the smart contract, a formal
security analysis is undertaken.

The paper moves on to the subsequent sections. In Section 2, the proposed
system model is provided. Section 3 presents the simulation outcomes and
system model validation. In Section 4, the formal security analysis is
addressed. The sixth section provides an overview of the accomplished
activities.

Figure 1. Drone nodes’ Authentication and Cluster Head Selection in IoDT based
on Blockchain.

##  2\. System Model

Figure 1 depicts the system model, which will be analyzed and reviewed below.
IoDT, end-users, the Interplanetary File System (IPFS), and a blockchain are
system components. The ultimate shift of drones’ backends to IoDT will be
enabled by technologies such as the Internet of Things, intelligent computer
vision, cloud computing, enhanced wireless connectivity, big data, and
cutting-edge security. A growing variety of industries are embracing the use
of drones, including agriculture and industry, government and commercial
organizations, and the monitoring of smart cities and rural areas. Each user
must register for the blockchain network and undergo the authentication
process to guarantee the network’s security. This objective is motivated by
the usage of registration and authentication procedures (Cui et al., 2020).
IPFS is a distributed system that utilizes data and information chunks for
storage and retrieval. Any time information is saved on IPFS, a hash is
generated. The 32-bit hash is a result of the IPFS technique for storing data.
The blockchain is then updated with this hash.

###  2.1. Initialization

A smart contract is a computerized contract whose conditions may be carried
out with little or no requirement for a third party. Blockchain technology
makes this capability possible. It is deployed on the transaction-controlling
BSs of the network. Utilizing blockchain technology, sensor node credentials
are kept in a blockchain for subsequent authentication, as part of the process
of enrolling nodes in the network. The credentials are sent using a message
like the equation shown below.

(1) $Message=Packet(ID_{N},MAC_{N},Rep_{N})$

Drone Node ID ($ID_{N}$), MAC addresses ($MAC_{N}$), and reputations
($Rep_{N}$) are utilized as part of the registration and authentication
procedure for nodes. $Rep_{N}$ is a measure of a node’s network standing that
takes into account the node’s past behaviors and its connections to other
nodes and the rest of the system. If the node’s reporting is not honest, its
reputation will decrease, but if it is, it will grow. The credentials are
recorded in an asymmetrical manner on a blockchain-based distributed ledger.
Their addresses are also recorded on the blockchain, which provides an
additional degree of security against fraudulent system usage. Throughout the
authentication procedure, the credentials are compared to the information
already on blockchain. When credentials do not match previously saved data,
the node in question is marked as malicious.

###  2.2. Cluster Head Selection

Drone nodes, cluster heads, and base stations make up the IoDT’s
infrastructure. The drone nodes transmit data to the CHs, where computations
are done. CHs must first gather drone node data before relaying it to base
stations (BSs). When BS wants to store data, it makes a request to IPFS, which
responds with a hash of the data. During data processing and storage, the
available energy of CHs is quickly depleted. Our suggested solution to this
problem is based on a technique known as R2D, which chooses CHs from regular
nodes. CHs is determined by three factors: available spare energy, proximity
to BSs, and maximum node degree. If there is a single node that meets all of
the given requirements, it will be classified as the CH. It is responsible for
combining all data packets before transmitting them. If many nodes are found
to match the requirements, CH will be chosen at random.

Algorithm 1 Cluster Head Selection

1:Inputs: Deployment of N nodes, BSs and CHs

2:Outputs: Cluster Head

3:Select maximum energy node from set N

4:Select the node having minimum distance from BS

5:Select maximum degree node from set N

6:for i=1 to N do

7: Select $(Max(S(i).Er),Max(S(i).Degree)andMin(S(i).Distance))$

8: if New selected $CH=Max(Degree,Er)$ && $Min(Distance)$ then

9: Selected node is CH

10: Check next node

###  2.3. Authentication

Drone nodes can only be trusted if they have been verified by the blockchain.
By identifying and eliminating malicious sensors, authentication guarantees
that only trustworthy nodes are used to provide services. The security of your
registration information is improved when you send it via an encrypted
connection. At the node level, the data is encrypted using the public key of
the Blockchain Storage node. The Blockchain Storage node will use its private
key to decode the information before adding it to the blockchain. There is no
new way for transferring encryption and decryption keys since they cannot be
canceled or altered. This ensures a steady functioning of the system. When a
node in the network does any kind of activity, the BS checks to make sure it
has the proper authorization to do so. Network-wide security may be guaranteed
using this method. Multiple research papers (Cao et al., 2021; Abdi Nasib Far
et al., 2021) depend on node authentication. The use of encryption for node
authentication is outlined in detail in (Cao et al., 2021). Centralized
authority results in bottlenecks and decreased productivity. To verify users,
(Abdi Nasib Far et al., 2021) employs a simple token system. The origin of
SPOF may be traced back to authoritative monopolies. The sink node is
acknowledged by the nodes as a means of authentication. The sink node is
identified by the nodes based on their position in the sequence. The use of
Proof-of-Work (PoW) for node authentication raises computational expenses.
Hybrid blockchain nodes are validated in (Cui et al., 2020). The use of PoA
raises the price of calculation. Keeping data on a blockchain network might be
rather expensive. For the sake of lowering the overall computational cost, the
system model we gave makes use of PoA consensus for node authentication. The
presented authentication model has been seen before. This authentication
framework provides a safe place to store sensor data and a robust method for
selecting a suitable CH. Since authentication processes are used in several
contexts, this approach represents a new combination (Cui et al., 2020; Abdi
Nasib Far et al., 2021). A lower total network cost is achieved via the use of
IPFS’s distributed data storage. Authentication takes place when the
credentials used by different nodes to access the blockchain are found to be a
match.

To perpetrate crimes, an attacker node may move information across the network
once it has been taken over. All valid nodes have verified their identity with
BSs, and their registration information is recorded in the distributed ledger.
Since authentication information is not recorded in the blockchain, any
malicious node that is part of the data transfer may be quickly identified and
kicked from the network. This prevents malicious nodes from taking over any
other node in our network and doing criminal acts. After being disconnected
from the network, a rogue node can no longer send or receive information.
Because the blockchain is loaded on them, BSs are able to confirm transactions
and cut off the rogue node’s access. The suggested architecture employs Proof
of Authority (PoA) for transaction mining. It requires less processing power
than proof-of-work consensus methods. PoA miners are chosen nodes in the
network in advance. As soon as an authentication request is made, registered
nodes are checked. The blockchain record consist of three attributes:
$ID_{N}$, $MAC_{N}$, and $Rep_{N}$. In order to determine whether or not two
nodes are compatible, the blockchain checks the credentials of each node
against the credentials that have already been entered in the blockchain. If
the credentials are correct, the nodes may be trusted and their legitimacy can
be announced. They may be misunderstood as malicious or insincere. Algorithm 2
describes the procedure in detail.

###  2.4. Data Storage

As a result of the high cost of keeping data on a blockchain, this huge volume
of data cannot be kept there. Data is sent from BSs and stored in IPFS with
hash values and the credentials of blockchain nodes. All financial dealings
are recorded chronologically on a blockchain ledger. This ledger is shared
across all entities in the network. Each node plays a vital role in
maintaining the network’s integrity. After a transaction occurs, all ledgers
are immediately synced. When a malicious node tries to alter a ledger’s
transaction record, it’s easy to spot since the altered ledger won’t be
consistent with any other ledgers. IPFS saves information in blobs. Data
stored on IPFS is not kept permanently. If data is to be kept on IPFS for an
extended period of time, cost has to be paid. Data storage on the IPFS is
incentivized by monetary rewards for participating peer nodes. The blockchain
keeps a record of hashes. For security reasons, the given hash may be used by
only approved nodes. IPFS is a temporary storage solution. We provide IPFS an
incentive to keep data around for a while.

To authenticate and register nodes, we use a hosted private blockchain.
Requests to register as a user are recorded on the blockchain. Then,
blockchain verifies the nodes’ registrations. When a user is registered, the
system ignores their request. If not, then node registration is permitted. The
authentication procedure is described in detail in Algorithm 2.

Algorithm 2 Drone Authentication

1:Inputs: $ID_{N},MAC_{N},Rep_{N}$

2:Outputs: Nodes authentication message

3:Registration← Input ($ID_{N},MAC_{N},Rep_{N}$)

4:if $ID_{N},MAC_{N},Rep_{N}$ stored in blockchain then

5: Node authenticated

6:if $ID_{N},MAC_{N},Rep_{N}$ are not stored in blockchain then

7: Node not authenticated

8:Recommend for registration

###  2.5. Service Provisioning

Blockchain can verify the legitimacy of a user’s identification documents.
Transactions cannot take place until a user’s identity has been verified on
the blockchain. For each node, the blockchain verifies the credentials to make
sure they are not duplicates. If the provided credentials are consistent with
those on file, then the user is considered to be legitimate. If they don’t
match, the node is considered malicious and is removed from the network. After
verifying the user’s identity, we next make sure the amount of ethers being
purchased is sufficient. The request will be denied and the hash of the data
will not be sent if the user does not have enough ethers. users will have
access to network services upon authentication. When asked, BS will encrypt
the service using the customer’s private key and give the ciphertext.

Network security is handled via 128 bit AES encryption. Data integrity is
protected by both AES encryption and SHA-256 hashing. The BS will generate the
hash using SHA-256 and add it to the blockchain. The BS encrypts the
information using the client’s private key and transmits the result.
Information is encrypted and sent, then the user uses the sender’s private key
to decrypt the information. The user decrypts the data, then computes the hash
using SHA-256 and checks it against the hash stored on the blockchain.
Together, SHA-256 and AES ensure the integrity and privacy of your data. Our
primary focus is on providing timely information to users, and AES 128-bit
encryption allows for efficient encryption and decryption.

##  3\. Results and Discussion

The simulated networks have three kinds of nodes: 100 drone nodes, 4 cluster
heads (CHs), and 2 base stations (BSs), all of which are distributed
throughout a 1000x1000$m^{2}$ area. In addition, our system’s model includes
the user’s address with the sensed data and the data index. Drone nodes
dispersed across the network are responsible for data collection. The
information obtained by these sensors is sent to cluster heads for processing.
After initial processing, the data is sent to the BSs for further analysis.
The BS stores both the data and the index to that data. BSs store the data
index and the discovered information as part of their service. In addition,
the user’s address is the Ethereum address that is assigned to the transaction
at the time it enters the network. After registering, nodes are screened to
verify they are not malicious and can contribute to the network.

Figure 2(a) depicts the total transaction costs incurred throughout the
registration and authentication procedures. A transaction fee is paid for each
use of a smart contract. The findings indicate that the transaction cost
increases as the number of packets grows. The transaction charge will grow
according to the network’s size. Registration information must be validated
during the authentication process in order to save transaction costs. Figure
2(b) displays a comparison between the Proof-of-Work and Proof-of-Authority
consensus procedures as they pertain to the delivery of services and the
storage of data. The proposed system uses a private blockchain, which makes it
possible to perform the PoA consensus procedure. This helps to the overall
cost reduction of the proposed system. The Gwei-based computing expenses of
the two consensus techniques are evaluated. Proof of Authority is superior to
Proof of Work in terms of performance. According to PoA, mining nodes are not
needed to do any difficult mathematical computations. In PoA, miners are pre-
selected, and it is their duty to check the validity of all transactions. This
explains why PoW incurs far higher computational costs than PoA. Figure 2(b)
depicts the creation of a smart contract based on the PoA consensus technique
when users want blockchain services. This happens when a client launches a
blockchain deployment. Comparing the two service delivery methods reveals that
PoA uses less computing resources. Figure 2(b) demonstrates how the average
IPFS transaction cost is determined when data is stored in a distributed file
system. As previously noted, the average transaction cost of PoW is higher
than that of PoA.

(a)

(b)

Figure 2. (a) Node registration and authentication Transaction cost. (b) IPFS
data storage and service provisioning transaction costs.

Figure 3(a) compares the total number of rounds to the total amount of energy
used. We examine the energy efficiency of the LEACH protocol and R2D. The
nodes of R2D will continue to use energy throughout the length of 1400 cycles.
In LEACH, the nodes continue to consume energy until the completion of the
1000th cycle. LEACH’s overall energy usage is high due to its random selection
of CHs. There is a possibility that the sensor nodes closest to the base
station (BS) will not join the network or be designated as cluster head. When
selecting which CHs to employ, the R2D considers three criteria: maximum
degree, minimum distance, and minimum energy usage. Figure 3(b) demonstrates
that the initial network throughput for both protocols is zero. The throughput
of the network increases with rounds. Since each node contributes to R2D, the
quantity of data delivered from ordinary nodes to base stations continues to
increase. It starts to stagnate at 1500 rounds. When R2D is used to choose
CHs, throughput increases and the number of available nodes for data packet
transmission is maximized.

(a)

(b)

Figure 3. (a) Energy consumption. (b) Network throughput.

##  4\. Security Analysis

A formal examination of network security may identify potentially dangerous
nodes. Using this authentication technique, malicious nodes may be identified
and eventually eliminated. The network’s toughness is measured using attacks
like Sybil and Man in the Middle (MITM). Oyente is a tool that examines the
identification data of network nodes as recorded in the blockchain. Below are
evaluations of attacks.

Sybil attack: Removal of malicious nodes is carried out by the authentication
process. A network node’s registration and authentication is done by the
authentication system which is a prerequisite for the drone to perform any
operation. Drone data is recorded and stored in a blockchain. The blockchain
keeps track of the verified identities of each node in the network and their
respective identifiers. This attack is impossible in the proposed framework
because of the two-way nature of the authentication.

MITM attack: Network conversion is vulnerable when MITM attack is induced to
R2D . Because of how the nodes handle authentication, attacks like these are
impossible. Credentials saved in a blockchain are used by nodes to join the
network. These nodes need to be validated before they may begin interacting.
The authenticity of the node is verified by comparing it against registration
data stolen by the adversary. The registration process generates a random key
for each node. This key is used for authentication purposes. The given key can
be found on the blockchain. A malicious node trying to join the network would
have to submit the same credentials as a legitimate one. During the
registration process, the attacker node is removed. The attacker node needs
the unique identity stored on blockchain in order to authenticate. In order to
ensure the accuracy of its information, the attacker must use the key.

Man-in-the-middle attacks occur when an adversary in the communication chain
either delivers false data or makes unauthorized changes to a legitimate data
packet. When malicious actors intervene, information routed from drones to CHs
or from CHs to BSs is lost. A constant stream of malicious packets is sent to
the victim by the attackers. Each drone node is assigned a different key ID.
The connected nodes in a network must first verify the identity of each other
via authentication. The attacker node in a Sybil attack pretends to be other
nodes in the network. During an attack, only malicious packets are transmitted
to the target, which significantly degrades the network’s performance. If
rogue users can be identified by mutual registration and authentication,
network performance can be enhanced.

Attacks on a network use a higher amount of energy. Sending malicious packets
to the target site consumes more resources. Following registration and
validation, the network comprises only trusted nodes. The IoDT network can
save energy when there are no threats to deal with. As a means of attacking
other nodes in a network, attackers in the network may often send out
corrupted data packets. They also consume a lot of power. This prevents valid
nodes’ data packets from reaching their intended destinations. Authentication
will result in the removal of malicious nodes. Since genuine nodes consume
less energy, they live longer. In the attacker model, malicious nodes quickly
die because they run out of energy while sending out the corrupted data
packets.

Table 1. Smart contract vulnerability analysis using oyente tools Vulnerability | Result
---|---
EVM Code Coverage | 99.5%
Integer Underflow | False
Integer Overflow | False
Parity Multisig Part 2 | False
Callstack Depth Attack | False
Transaction-Ordering Dependence | False
Time Stamp Dependency | False
Re-entrancy | False

###  4.1. Smart Contract Analysis

Table 1 depicts the Oyente tool’s study of the node registration and
authentication smart contracts’ security. The table demonstrates that the
smart contract can survive the attacks outlined in the article. These results
disprove every one of the presented attacks against the smart contract.

Strategies that helped us to tackle smart contract vulnerabilities are as
follows.

  * •

Re-entrancy attack: A malicious network node will invoke the external function
whenever the smart contract is executed. Due to this, the true function will
not operate as effectively. Our smart contract is resistant to this kind of
attack since all network nodes must first be authorized. The blockchain
records the verifiable identities of each network node. Consequently, invalid
nodes are gradually eliminated from the network since they cannot offer
relevant data.

  * •

No double spending: In our prototype system, clients verify their identities
using a private key that we provide. No malicious node can access the
network’s information, hence the network is safe.

  * •

Denial of service attack: Our system model is resistant to a denial-of-service
attack because the users are authenticated by delivering the communication’s
secret keys and because they are required to exchange the keys before
obtaining data.

  * •

Single point of failure: IPFS’s decentralized nature is essential to the
architecture of our system. The inflexibility of the centralized data store
prevents it from responding rapidly. Our suggested remedy makes this attack
obsolete with IPFS, a decentralized file-sharing system. The technology is
quick and responsive while storing and retrieving data.

##  5\. Conclusion

We propose a blockchain and IoDT-based network aimed to reduce the malicious
activities while reducing the required resources. Authentication mechanisms
are used to guarantee that only authorized nodes can communicate. Only nodes
with network access credentials are permitted to submit data for processing to
CHs. CHs collect and analyze data. We propose the R2D protocol in which CHs
are chosen among regular drone nodes based on their highest degree, smallest
distance from BS, and largest residual energy. CHs with low energy are
replaced with nodes that meet the above requirements. Additionally, the
collected data are saved in the IPFS database. Blockchain technology is used
for long-term storage. Services are sent via a secure connection utilizing a
128-bit AES-encrypted protocol. We may infer, based on the simulation
findings, that data storage and service supply can be achieved with minimal
computational cost. Moreover, the transaction costs associated with
registration and verification are small. Comparing LEACH to R2D, researchers
discovered that LEACH delivers higher energy efficiency, longer network life,
and higher throughput. The results demonstrate that R2D greatly outperforms
LEACH. A formal security analysis is conducted to assess the smart contract’s
resistance to assaults. To demonstrate the network’s security, it is also
subjected to the Man-in-the-Middle attack (MITM) and the Sybil attack. Future
initiatives will use a machine learning method to identify malicious drone
nodes.

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