INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
Enhancing RSAAlgorithm Performance in Resource-Constrained  
IoT Networks.  
Prof. G.E. Okereke (PhD)1, Chinatu M. Anyanwu (MSc)2*, Stephen Uche Edeh (MSc)3, Onuoha M.  
Thomas (MSc)4  
1,3Department of Computer Science, University of Nigeria, Nsukka  
2,4Department of Computer Science, Maduka University, Ekwegbe, Enugu State  
*Corresponding Author  
DOI : https://doi.org/10.51583/IJLTEMAS.2025.1411000077  
Received: 13 November 2025; Accepted: 19 November 2025; Published: 15 December 2025  
ABSTRACT  
The Internet of Things (IoT) introduces new security considerations because connected devices typically have  
limited computational resources, making traditional cryptographic algorithms inefficient. RSA, a widely used  
public-key cryptosystem, is particularly resource-intensive due to its large key sizes and heavy arithmetic  
operations. This study investigates the inefficiency of standard RSA in resource-constrained IoT environments  
and evaluates optimization strategies aimed at improving performance without compromising security.  
Enhancements include key size reduction, the use of the Chinese Remainder Theorem (CRT) for decryption, and  
precomputation techniques. Performance was assessed in a simulated IoT environment, measuring execution  
time, memory consumption, and energy efficiency. Security considerations, including potential vulnerabilities  
of CRT-based RSA such as differential fault attacks, were addressed through redundancy and verification  
mechanisms. Comparative insights with Elliptic Curve Cryptography (ECC) and post-quantum lightweight  
schemes (e.g., Ascon, Kyber-SLH-DSA) were provided to contextualize the results. The findings show that  
optimized RSA achieves significant reductions in computational overhead and energy consumption while  
maintaining correctness, demonstrating its feasibility for low-power IoT devices. Hybrid cryptography  
approaches, combining RSAkey exchange with symmetric AES payload encryption, are recommended for future  
implementations. These results reinforce that efficient and practical public-key encryption is achievable in  
constrained IoT systems while preserving strong security.  
Keywords: RSA Optimization, IoT Security, Lightweight Cryptography, Resource-Constrained Devices,  
CRTRSA.  
INTRODUCTION  
The Internet of Things (IoT) has rapidly expanded in recent years, connecting billions of devices across domains  
such as healthcare, transportation, industry, and smart homes. These devices continuously exchange sensitive  
data, making secure communication one of the most pressing requirements of modern computing. Cryptographic  
algorithms play a central role in ensuring data confidentiality, authenticity, and integrity, but their effectiveness  
depends heavily on the ability of resource-constrained devices to execute them efficiently.  
Among public-key cryptographic systems, the RSA algorithm stands out as one of the oldest and most widely  
used methods for encryption, decryption, and digital signatures (Ma, 2024). Its strength is rooted in the  
mathematical difficulty of prime factorization, which prevents adversaries from deriving private keys from  
public information. Despite this security advantage, RSA's computational requirements are substantial.  
Operations such as key generation, encryption, and decryption involve large integer arithmetic, which demands  
significant processing power, memory, and energy resources. These demands exceed the capabilities of most IoT  
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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
nodes, which use lightweight processors with very restricted memory and energy, making heavy cryptographic  
operations difficult, such as RSA, storage, and battery life (Zhang et al., 2020).  
This mismatch between RSA's security strength and IoT's resource limitations creates a critical challenge. While  
RSA offers reliable cryptographic protection, it is often impractical for direct use in IoT systems because of its  
high computational overhead and energy demands. If left unaddressed, RSA risks being excluded from IoT  
deployments, leaving a gap between strong cryptographic standards and the realities of constrained devices.  
To address this, this study explores enhancements to the RSA algorithm with the aim of improving its  
performance in IoT environments. The research implements and evaluates a modified RSA scheme, analyzing  
its computational efficiency under varying conditions. The experimental results show that the optimized RSA  
achieves faster execution, lower memory consumption, and reduced energy usage, while preserving the security  
guarantees of the original algorithm. These findings demonstrate that RSA can remain a practical option for IoT  
security when adapted to align with device limitations without overburdening device resources.  
Related Works  
Public-key cryptography remains a cornerstone of secure communication, with the RSA algorithm (introduced  
by Rivest, Shamir, and Adleman in 1977) serving as one of its most enduring contributions. While RSA has long  
been applied in secure digital communication, supporting both encryption and authentication, its computational  
cost has motivated extensive research into some efficient or lightweight cryptographic solutions, especially as  
the Internet of Things (IoT) has grown in scale and importance.  
Recent studies have highlighted the difficulties of deploying RSA in constrained IoT environments. Zhang Li  
and Wang (2020) noted that RSA decryption, in particular, is resource-intensive and can overwhelm embedded  
devices with limited processing power. Allioui and Mourdi (2023) also highlighted that IoT deployments require  
lightweight algorithms, since delays and high power consumption can reduce system reliability. Together, these  
works underline the tension between RSA's proven security and the practical realities of IoT hardware.  
Researchers have proposed several approaches to bridge this gap. Ma (2024) showed that arithmetic level  
improvements, such as Montgomery multiplication and the Chinese Remainder Theorem (CRT), can  
significantly reduce RSA's computation time without weakening its security. Alternatives like Elliptic Curve  
Cryptography (ECC) have also been suggested because they achieve similar security levels with smaller key  
sizes. Yet, RSA still remains attractive because of its simplicity and long history of adoption.  
Other contributions have focused on tailoring RSA to modern platforms. Elamir and Zhand (2021) demonstrated  
that optimizing RSA implementations for specific processor architectures can improve both speed and energy  
use. Emam (2017) went further to demonstrate the feasibility of integrating modified RSA with IoT frameworks  
to maintain acceptable energy efficiency. These contemporary efforts reinforce the idea that RSA, though  
demanding in its original form, can be adapted for modern lightweight applications through careful optimization.  
In summary, the literature reflects a clear understanding of RSA’s computational burden but also provides  
evidence that targeted optimizations can make it viable for constrained environments. This body of work forms  
the basis for the present study, which evaluates an optimized RSA implementation with the aim of balancing  
strong security against the resource limitations of IoT devices.  
METHODOLOGY  
This study followed a structured methodology designed to evaluate the performance of an optimized RSA  
algorithm under realistic IoT constraints. The process consisted of three stages: system setup, algorithm  
optimization, and empirical evaluation using execution time, memory usage, and energy consumption as core  
metrics.  
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System Setup  
Experiments were conducted using a simulated IoT environment implemented in Python 3.11 with the  
PyCryptodome cryptographic library. The simulation emulated an ARM Cortex-M3 class microcontroller  
operating at 72 MHz with a 96 KB RAM limit, representing the architecture and constraints of low-power IoT  
devices. Standard RSA was implemented as the baseline using key sizes of 512, 1024, and 2048 bits to capture  
performance across lightweight and higher-security configurations. To ensure reproducibility and provide  
detailed methodology:  
•Simulation Environment: Python 3.11, PyCryptodome library for cryptographic operations.  
•Profiling Tools: time.perf_counter() for execution timing, memory_profiler for memory usage, and energy  
estimated using a standard MCU active-mode power model:  
퐸 = 푉 × 퐼 × 푡  
Where V = 3.3 V, I = 8–12mA, and t is the recorded execution time based on STM32 microcontroller reference  
sheets.  
•Toolchain: Compiled using GCC ARM Embedded Toolchain version 10.3.  
•Reproducibility: Each experiment was repeated three times per configuration to ensure consistency.  
Although the simulation provides controlled and repeatable measurements, it does not fully capture real hardware  
timing behavior, memory access patterns, or electromagnetic/power-side characteristics. Future work will  
involve hardware validation on platforms such as ARM Cortex-M boards, ESP32, or MSP430 microcontrollers  
to confirm performance under practical deployment conditions.  
RSA Optimization  
The standard RSA algorithm was modified to improve computational efficiency while preserving cryptographic  
correctness. The optimization focused on reducing latency and memory overhead during key generation,  
encryption, and decryption. Techniques included  
1. Streamlined modular arithmetic operations,  
2. Reduced intermediate variable storage, and  
3. Improved exponentiation routines tailored for constrained IoT environments.  
The optimized version was designed to operate within the simulated MCU limits, ensuring feasibility for  
realworld embedded deployments.  
Performance Metrics  
Performance evaluation was based on three key indicators essential to IoT systems:  
•Execution Time: duration of RSA encryption and decryption operations.  
•Memory Usage: The peak RAM consumed during algorithm execution.  
•Energy Consumption: estimated power usage based on execution time and MCU power model.  
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These metrics reflect the most important constraints affecting cryptographic deployment on embedded devices.  
Experimental Procedure  
The experimental workflow consisted of the following steps:  
1. Implemented standard RSA to establish baseline behavior.  
2. Developed and integrated optimization techniques into RSA.  
3. Executed both standard and optimized RSA across the selected key sizes (512, 1024, 2048 bits).  
4. Collected execution time, memory usage, and energy consumption for each configuration.  
5. Compared both implementations to quantify performance improvements.  
6.  
Verified result stability by repeating measurements under identical simulation parameters.  
Validation  
Correctness validation was performed by ensuring that all encrypted messages were successfully decrypted to  
their original plaintext across all key sizes. This confirmed that the optimization process did not alter RSA’s  
functional integrity or weaken its cryptographic behavior.  
Security Considerations  
The optimized RSA implementation uses the Chinese Remainder Theorem (CRT) to improve decryption  
efficiency. While CRT provides significant performance benefits, it can introduce potential vulnerabilities,  
particularly differential fault analysis (DFA) attacks, where deliberate faults during computation may reveal  
private key information.  
To mitigate these risks, recommended countermeasures include:  
•Verification of computation results using redundant CRT calculations  
•Use of fault-resistant modular exponentiation routines  
•Incorporation of consistency checks after key-dependent operations  
Hybrid cryptography strategies, such as using RSA for key exchange combined with symmetric AES encryption  
for payloads, can further reduce computational load while maintaining strong security. Future work should also  
evaluate side-channel resistance, as IoT devices often operate in physically accessible environments.  
RESULTS  
This section presents and discusses the results obtained from the implementation and evaluation of both the  
standard RSA algorithm and the optimized RSA. The analysis is organized around the three key performance  
indicators: execution time, memory usage, and energy consumption. The correctness of the optimization is also  
verified.  
Execution Time  
Execution time was measured for encryption and decryption at key sizes of 512, 1024, and 2048 bits. The results,  
summarized in Table 4.1, show that the optimized RSA consistently achieved lower execution times than the  
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standard RSA across all key sizes. At 512 bits, the improvement was modest, but the performance gap widened  
considerably at 1024 and 2048 bits. This indicates that the optimization scales well with key length, which is  
especially important for practical applications where higher key sizes are required for security.  
Table 1: Execution time of standard RSA and optimized RSA across different key sizes.  
Metric  
Standard RSA Optimized RSA  
% Improvement  
46.1%  
CPU Usage (%)  
78.5  
112.4  
927  
42.3  
68.9  
412  
75.2  
220  
192  
Memory Usage (KB)  
Execution Time (ms)  
Energy Consumption (mJ)  
Encryption Time (ms)  
Decryption Time (ms)  
38.7%  
55.6%  
147.6  
484  
49.0%  
54.5%  
484  
56.7%  
To provide clearer visualization, the results are also represented graphically. The trend is further illustrated in  
Figure 4.1, where the optimized RSA curve stays consistently below the standard RSA curve, confirming shorter  
execution times. These results indicate that the optimization reduces computational overhead, making RSA more  
practical for time-sensitive IoT applications such as sensor data encryption and authentication protocols.  
Figure 4.1: Execution time comparison between standard RSA and optimized RSA.  
Memory Usage  
The memory usage was also measured for both algorithms at the same key sizes. As expected, memory  
consumption increased with larger key sizes in both algorithms. The results, summarized in Table 4.2, reveal that  
the optimized RSA consumed less memory than the standard RSA in every case. As expected, memory  
requirements increased as key sizes grew, but the optimized version consistently reduced usage compared to the  
baseline.  
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Table 2: Memory usage of standard RSA and optimized RSA across different key sizes  
RSA  
Key Size  
(bits)  
Security Level  
Encryption/Decryption  
Speed  
Resource  
Usage  
Suitability for  
IoT  
Configuration  
Standard RSA  
2048  
High  
Slow  
High (CPU, Low (Not  
memory,  
energy)  
suitable  
for  
constrained  
devices)  
Optimized  
RSA (Reduced  
Key)  
1024  
Moderate  
Fast  
Moderate  
High  
balance  
speed  
(Good  
of  
and  
security)  
CRT-Based  
RSA  
1024–2048  
Moderate–High  
Faster decryption  
Moderate  
High  
(Efficient with  
acceptable  
security)  
ECC  
256  
High (equiv. to  
RSA 3072)  
Very Fast  
Low  
Very High  
(Alternative)  
(Ideal for IoT)  
The reduction in memory consumption is significant for IoT devices, which often operate with only a few  
kilobytes of RAM. By lowering memory demand, the optimized RSA increases the feasibility of deploying  
secure cryptographic operations in constrained environments without exhausting system resources.  
Energy Consumption  
Energy usage was estimated based on the computational effort of both algorithms. The optimized RSA showed  
reduced energy consumption compared to the standard RSA at all tested key sizes. This reduction is particularly  
important in IoT contexts, where devices rely on limited battery power.  
Table 3: Energy consumption of standard RSA and optimized RSA across different key sizes.  
Device  
Type  
Typical  
Specs  
RSA Type  
Performance  
Security  
Remarks  
Recommended  
Low-End  
Optimized RSA  
(1024-bit, CRT).  
ECC (256-bit)  
Fast  
Suitable for basic  
sensors,  
wearables, etc.  
8-bit/16-bit  
MCU,  
Moderate  
High  
IoT Devices  
encryption/decryption,  
low overhead  
<128KB RAM,  
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batterypowered  
32-bit CPU,  
Very  
resource use  
fast,  
minimal  
Ideal for long-  
term use and  
constrained power  
High-End  
Standard  
(2048-bit)  
RSA Acceptable  
speed, High  
Suitable  
for  
for  
higher overhead.  
gateways.  
IoT Devices >512KB RAM,  
High  
CRT-RSA or  
Balanced performance  
Efficient  
external power  
or charging.  
secure,  
highvolume  
processing.  
Hybrid RSA-AES  
This finding is particularly important for IoT applications, where devices frequently rely on batteries or harvested  
energy sources. Reducing energy usage directly translates into longer device lifespans, less frequent battery  
replacements, and more sustainable operation in remote or inaccessible environments.  
Security Integrity  
In addition to performance testing, the correctness of the optimized RSA was verified. All encrypted messages  
were accurately decrypted to their original plain text across all trials. This confirms that the optimization did not  
compromise RSA’s functional reliability.  
While the optimized RSA demonstrated correctness, it is important to acknowledge potential vulnerabilities  
inherent to CRT-based implementations. Differential fault analysis (DFA) attacks can exploit errors during CRT  
decryption to reveal private key information. Although no such attacks were performed in this study, mitigation  
strategies such as result verification, randomization of computations, and fault detection mechanisms are  
recommended for future work to strengthen the security posture of CRT-RSA in IoT devices.  
RESULT DISCUSSION  
Overall, the results demonstrate that the optimized RSA significantly improves execution time, memory  
efficiency, and energy consumption compared to the standard RSA. These improvements become more  
pronounced as key sizes increase, which is encouraging given that larger keys are necessary for secure realworld  
applications.  
The combination of reduced computational load, lower memory footprint, and improved energy efficiency  
positions the optimized RSA as a more suitable cryptographic solution for IoT devices. Importantly, these  
performance gains were achieved without compromising correctness or security. This balance of efficiency and  
reliability underscores the potential of RSA optimizations to extend secure communication to  
resourceconstrained environments where standard RSA would otherwise be impractical.  
Comparative Analysis  
To contextualize the performance and security of the optimized RSA, comparisons with alternative cryptographic  
schemes were considered:  
1. Elliptic Curve Cryptography (ECC): Provides equivalent security with significantly smaller key sizes,  
reducing both memory footprint and computational demand. ECC with a 256-bit key offers security  
comparable to a 3072-bit RSA key, making it highly suitable for resource-constrained IoT devices.  
2. Post-Quantum Lightweight Cryptography: Emerging schemes such as Ascon and Kyber-SLH-DSA  
hybrids provide resistance against quantum attacks while maintaining efficient performance in  
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constrained environments. Although direct benchmarking with these algorithms is beyond the current  
study, their inclusion highlights future research directions and the potential for hybrid cryptographic  
solutions in IoT.  
3. Hybrid Cryptography (RSA + AES): Another promising approach for IoT deployment is hybrid  
cryptography, where RSA is used for key exchange while symmetric algorithms like AES handle payload  
encryption. This combines the security advantages of RSA with the efficiency of symmetric encryption,  
reducing computational overhead and energy consumption for IoT nodes. Future work could explore the  
performance and security implications of such hybrid schemes alongside optimized RSA.  
CONCLUSION AND RECOMMENDATION  
Conclusion  
This study addressed the challenge of deploying RSA in resource-constrained IoT environments. Standard RSA,  
while secure, imposes high computational, memory, and energy demands that exceed the capabilities of  
lightweight devices. An optimized RSA was implemented using key size reduction, CRT-based decryption, and  
other algorithmic improvements.  
Evaluation in a simulated IoT environment showed that the optimized RSA consistently outperforms standard  
RSA across execution time, memory usage, and energy consumption metrics. All encrypted messages were  
correctly decrypted, confirming that the optimization preserved cryptographic integrity.  
The study also highlighted potential CRT-related vulnerabilities, such as differential fault attacks, and suggested  
countermeasures to enhance security. Comparative analysis with ECC and emerging post-quantum lightweight  
schemes demonstrated the broader context of efficiency versus security trade-offs in IoT deployments.  
Hybrid cryptography strategies, integrating RSA key exchange with symmetric AES payload encryption, and  
consideration of side-channel resistance are recommended for real-world applications. Future work should  
validate these results on actual microcontroller boards, expand key size testing, and explore advanced lightweight  
or post-quantum algorithms.  
Overall, the optimized RSA offers a viable solution for secure IoT communication, balancing strong security  
with efficient use of limited resources, and represents a practical step toward enabling robust cryptography in  
constrained environments.  
Recommendation  
Based on the results of this research, the following recommendations are made:  
1.  
Deployment: Apply the optimized RSA in IoT systems where strong security is needed but resources  
are limited.  
2.  
3.  
Scalability: Test larger key sizes (3072 and 4096 bits) to meet future security needs.  
Hardware validation: Implement on real IoT boards (e.g, ARM-based microcontrollers) to confirm  
results beyond simulation.  
4.  
5.  
Energy profiling: Use precise power measurement tools in future studies.  
Comparative analysis: Compare optimized RSA with other lightweight algorithms, such as ECC, for  
broader insights.  
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6.  
Hybrid cryptography and side-channel evaluation: Integrated TSA key exchange with symmetric AES  
payload encryption, and evaluate side-channel resistance to ensure resilience in physically accessible  
IoT devices.  
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