Enhanced Secure Leach with Advanced Encryption Standard And

Attack Detection Scheme

SAGIR IBRAHIM, AISHA IBRAHIM GIDE

Department of Computer Science, Umaru Musa Yar’adua University,

Katsina State,

NIGERIA

Abstract: - Wireless Sensor Networks (WSNs) have become widely used in a variety of applications, ranging

from military surveillance to environmental monitoring, as a result of their quick development. However,

Standard Mechanism for the purpose of authenticating a sensor node as CH and ensure the security of data.

SLEAD algorithm was implemented using Python within a Jupyter Notebook environment. The simulation

result shows that SLEAD outperformed the traditional scheme in-terms of efficient energy utilization and data

privacy.

Key-Words: - WSN, SLEAD, Secure-LEACH, Cluster Head (CH), Authentication.

Received: March 15, 2024. Revised: August 25, 2024. Accepted: September 16, 2024. Published: October 17, 2024.

1 Introduction

power, and limited sensing and transmission range.

The energy stored in the battery of a node

determines the lifespan of the node. The stored

energy is used for various node operations such as

sensing, processing, and communication. The

batteries in sensor nodes are small and usually

cannot be replaced or recharged. There are various

energy harvesting methods, but they cannot

eliminate the need for energy management. Hence,

the most challenging job is the organization of the

monitoring physical or environmental parameters

like temperature, humidity, or motion. Due to

advancements in energy-efficient designs,

downsizing, and communication technologies,

WSNs have undergone tremendous evolution and

are now essential in a wide range of applications,

such as smart cities, healthcare, military operations,

and environmental monitoring (Rawat, 2021).

Sensor nodes which are able to sense, process, and

send data wirelessly are the backbone of WSN

Fig. 1: Wireless Sensor Clustering (Bhatia, 2020).

Applications for WSNs are numerous and include

smart agriculture, industrial control, environmental

monitoring, and health care. WSNs must contend

with a number of security issues, including scarce

resources, erratic communication, changing

topology, and physical attack susceptibility. In order

to secure a WSN and guarantee its operation,

integrity, and secrecy, it is imperative to implement

a few crucial measures (Lata, 2021).

1. Data Confidentiality

2. Data Integrity

In a WSN, data can be tampered with during

transmission, leading to inaccurate or misleading

information. For instance, in a military scenario,

altered sensor data could result in false alarms or

misinformed decisions (Gautam, 2021).

3. Availability of Network Services

WSNs must remain functional for continuous data

collection and transmission. Denial of Service

(DoS) attacks, such as jamming, can cripple the

unauthorized data access, injecting false data, or

misusing network resources. Without authentication,

malicious nodes can easily infiltrate the network.

5. Energy Efficiency

Sensor nodes in WSNs have limited battery life, and

security mechanisms must be efficient to avoid

draining the battery quickly. Attacks like routing

disruption or excessive message flooding can lead to

energy exhaustion, resulting in node failure and loss

of network functionality.

the following categories (Chris, 2023):

2.1 Hello flood attack

Some routing protocols in WSN require nodes to

broadcast hello messages to announce themselves to

their neighbors. A node which receives such a

message may assume that it is within a radio range

of the sender. However in some cases this

assumption may be false; sometimes a laptop-class

attacker broadcasting routing or other information

with large enough transmission power could

would be sending the packets into oblivion. Hence

the network is left in a state of confusion. Protocols

which depend on localized information exchange

between neighboring nodes for topology

maintenance or flow control are mainly affected by

this type of attack (Hamid, 2018). An attacker does

not necessarily need to construct legitimate traffic in

order to use the hello flood attack. It can simply re-

broadcast overhead packets with enough power to

be received by every other node in the network. Fig.

an enormous area and these nodes are very vitality

compelled. The power delivering batteries cannot be

consistently revived. Hence, it necessitates that

selected cluster heads and the corresponding relays.

Additionally, the fuzzy logic system allows the

nodes to adapt to the changing network conditions,

and the Capuchin search algorithm ensures that the

packets are routed in the most efficient way.

Simulation results reveal that CEDAR is superior to

comparative approaches regarding energy

consumption, delay, and network lifetime. Oliveira

et al., 2020 Proposed SecLEACH in which the sink

authenticates the cluster head nodes and the cluster

heads authenticate the joining nodes. In F-LEACH

themselves as cluster heads and from joining in any

cluster. According to (Lakshmanna et al., 2022)

introduced a novel cluster-based routing protocol.

The objective of this design is to ensure optimal

energy utilization and network lifetime. This is

optimization algorithm-driven clustering approach

to facilitate the selection of CHs and establishing

cluster structures. The suitability function takes into

account the number of hops that the data must take

to reach its destination, how far apart the nodes are

optimization algorithm then uses this information to

determine the best route for the data to take. As a

result, the network is more efficient and reliable,

method of regulating renewable energy usage in the

snsor networks is extremely effective. Buttyan et al.,

2019 proposed a cluster head election scheme which

conceals the election process from external nodes

using cryptographic techniques. However the

concealment works for only external attackers since

a compromised node can easily unveil the selection

result. Moreover, the compromised node can declare

itself as a CH even though it is not qualified.

According to (Sabrine, 2021) LEACH is a self-

spreading the load across multiple sensors rather

than continuously draining the power from a single

sensor. An elected CH broadcasts an advertisement

packet to inform the neighbouring non-CH nodes

about its selection. A non-CH node sends a join

request message to the CH from which the strongest

advertisement signal was received. After cluster

formation, the CH broadcasts a transmission

schedule in its cluster to allocate each cluster

member one data slot in a frame. A cluster member

contribute to the generation of a random value and a

CH is selected randomly using the random value.

SANE is classified into three sub-schemes

according to how to generate and distribute the

random value. They are Merkle’s puzzle based

scheme, commitment based scheme, and seed based

scheme. Moreover, LEC-MAC uses five parameters

to do its job. A PT value is used to distribute CHs in

the network uniformly. The PT value ensures that

no region in the target area is crowded with CHs.

An MCS value is used to prevent clusters from

cluster heads in each cluster are selected randomly.

The main disadvantage of LEACH is that if a sensor

lifetime (Rawat, 2021& Faheem Khan, 2020).

Multi-tier Multi-hop Routing in LEACH (MMR

LEACH) Protocol was proposed. This protocol uses

CH layering in the network by selecting two CHs.

The BS divides the entire network into several

multi-tiers. The main CH is responsible for

collecting, compressing, and transmitting data to the

BS as well as selecting the vice CH based on the

residual energy. In the process of data transmission,

the vice CH acts as an interface between the main

Methods

In wireless sensor networks (WSNs), clustering is a

popular energy-saving technique. However, the

effectiveness of this method greatly depends on

choosing the appropriate cluster head (CH). Because

there is more data to communicate between cluster

members and the sink node, improper CH selection

might result in high energy use. Using Advanced

Encryption Standard (AES) cryptography, this study

provides a unique cluster head selection method that

cryptography, AES also makes key management

simpler, which makes it more appropriate for WSNs

with limited resources. This method enhances

energy consumption while improving security,

which eventually enhances WSN lifetime and

overall performance.

4.1 Requirements for secure CH selection

The signal strength, which sensor nodes utilize to

broadcast hello messages, is the primary factor that

determines which cluster head (CH) to choose.

backup. In order to prevent this, malicious nodes are

often kept from being selected by the use of a

combination of random values and signal strength in

CH selection (Singh, 2021). An attacker can still

alter these conditions in spite of these protections,

which underlines the necessity for a more reliable

procedure can incorporate AES (Advanced

Encryption Standard) to safeguard this system. The

network could make sure that only trusted nodes—

rather than compromised or malicious ones—are

authentication using AES cryptographic Method

For Wireless Sensor Networks (WSNs), the SLEAD

(Secure LEACH) protocol is an enhancement on the

traditional LEACH (Low-Energy Adaptive

Clustering Hierarchy) protocol. It is intended to

improve energy efficiency and security during

cluster head (CH) selection and communication.

The Advanced Encryption Standard (AES)

cryptographic techniques are integrated into this

protocol to enable secure and verified cluster head

are legitimate under the proposed SLEAD protocol,

tampering. In order to verify that only valid CHs are

permitted, each node authenticates the CH by

confirming its AES-encrypted communications, so

malicious nodes were added to the network to

simulate common network attacks: the reply attack,

sinkhole attack, and HELLO flood. For secure

packet delivery ratio. The approach improved the

successful delivery of packets to their intended

destination by using AES cryptography to secure the

CH selection process. This confirmed that legitimate

nodes were in charge of routing data. In situations

with active attacks, where rogue nodes would often

prevent data flow, this gain was particularly

noticeable. PDR is defined as (packets

received/packets generated) * 100. Figure 3.1

illustrates Enhanced HFS-LEACH (SLEAD) packet

5.2.3 Delay

AES encryption and CH authentication, the

Enhanced HFS-LEACH (SLEAD) technique

delivery was used to calculate the delay, and

most WSN applications. Delay is calculated as

Delay = ∑ (received time – send time) / ∑ (number

of connections). Figure 3.1 illustrates Enhanced

HFS-LEACH (SLEAD) delay while maintaining an

attack and without an attack.

5.2.4 Overhead

When the Enhanced HFS-LEACH (SLEAD)

approach was implemented, the simulation

demonstrated a reduction in network overhead.

Malicious nodes flooded the network with control

overhead while maintaining an attack and without

an attack.

5.2.5 Energy Consumption

By preventing malicious nodes from turning into

CHs, AES cryptography helped the network

preserve energy. Since they were not required to

react to communication triggered by an attack,

legitimate sensor nodes were able to function more

effectively under normal circumstances.

Consequently, the overall energy usage was

LEACH (SLEAD) energy consumption while

Fig 7. Figures illustrating simulation results

In conclusion, the simulation results demonstrated

that by using AES-based authentication for CH

selection, the Enhanced HFS-LEACH (SLEAD)

method effectively reduced a range of attacks and

enhanced network performance. With significant

improvements in throughput, packet delivery, and

energy conservation, the small rise in the processing

latency was worth the trade-off.

When the HFS-LEACH and SLEAD protocols are

conservation is a primary concern, SLEAD is an

effective option considering its energy efficiency

advantage. When it comes to network performance,

SLEAD significantly outperforms HFS-LEACH in

terms of throughput and packet delivery ratio

(PDR). Figure 8. illustrates Performance

Comparison of HFS-LEACH and SLEAD Protocols

in Wireless Sensor Networks (WSN).

total efficiency is also enhanced by maintaining a

substantially lower overhead throughout the

and communication costs. Because of these

characteristics, SLEAD is more suited for situations

where low overhead and speedy data delivery are

crucial.

6. Conclusion

Given an emphasis on energy efficiency and secure

communication, the proposed SLEAD protocol

improves upon traditional cluster-based routing

algorithms in Wireless Sensor Networks (WSNs).

management while providing strong security in

comparison to asymmetric cryptographic

techniques. In order to preserve network integrity

and data security, the AES integration prevents

unauthorized nodes from assuming CH roles.

Plotting the results shows that proposed algorithm

performs better than the existing HFS-LEACH in a

number of crucial areas. It is more effective in

energy-constrained scenarios because it exhibits

noticeably lower energy consumption, reduced

better throughput and Packet Delivery Ratio (PDR),

reduced overhead and faster data transmission

(lower delay) which demonstrate that it is suitable

models, which may also allow for the real-time

detection of possible anomalies or attacks.

Furthermore, by taking into account variables like

node energy levels, traffic patterns, and mobility,

improvements in adaptive Cluster Head (CH)

selection techniques such as integrating machine

learning for real-time decision-making can

maximize network performance.

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